Calculation of annual spectral impact based on the monthly sums of irradiance of a reference year and the determined average monthly spectral impact assessed in Germany [32].
\r\n\t
",isbn:"978-1-80356-678-8",printIsbn:"978-1-80356-677-1",pdfIsbn:"978-1-80356-679-5",doi:null,price:0,priceEur:0,priceUsd:0,slug:null,numberOfPages:0,isOpenForSubmission:!0,isSalesforceBook:!1,isNomenclature:!1,hash:"6dcb071a2e978694b6b1cb9c20afc1a3",bookSignature:"Prof. Hai-Zhi Song",publishedDate:null,coverURL:"https://cdn.intechopen.com/books/images_new/11494.jpg",keywords:"Electric Field Effect, Nano-Materials, Electric Field Design, Antenna, Microelectronics, Optoelectronics, Electric Field Stimulation, Brain and Nerve, Electric Field Imaging, Atomic Electric Field, Space Science, Climate",numberOfDownloads:null,numberOfWosCitations:0,numberOfCrossrefCitations:null,numberOfDimensionsCitations:null,numberOfTotalCitations:null,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"March 22nd 2022",dateEndSecondStepPublish:"May 26th 2022",dateEndThirdStepPublish:"July 25th 2022",dateEndFourthStepPublish:"October 13th 2022",dateEndFifthStepPublish:"December 12th 2022",dateConfirmationOfParticipation:null,remainingDaysToSecondStep:"a month",secondStepPassed:!0,areRegistrationsClosed:!1,currentStepOfPublishingProcess:3,editedByType:null,kuFlag:!1,biosketch:"A pioneering researcher in the fields of new materials, optoelectronic devices, and quantum information processing, appointed vice director of the Science and Technology Committee of SWITP, author/co-author of more than 170 research papers, and holder of 40 patents.",coeditorOneBiosketch:null,coeditorTwoBiosketch:null,coeditorThreeBiosketch:null,coeditorFourBiosketch:null,coeditorFiveBiosketch:null,editors:[{id:"196114",title:"Prof.",name:"Hai-Zhi",middleName:null,surname:"Song",slug:"hai-zhi-song",fullName:"Hai-Zhi Song",profilePictureURL:"https://mts.intechopen.com/storage/users/196114/images/system/196114.jpg",biography:"Curriculum Vitae\n\nName: Hai-Zhi Song \nGender: male\nDate of Birth: Oct. 20, 1968\nPlace of Birth: Shanxi, China\nAffiliation and Address: \nSouthwest Institute of Technical Physics\nNo.7, Section 4, Renminnan Road, Chengdu 610041, China\nAnd\nInstitute of Fundamental and Frontier Sciences,\nUniversity of Electronic Science and Technology of China,\nNo. 4, Section 2, Jianshebei Road, Chengdu 610054, China\n\nWork Phone: +86-28-68180751, +86-28-83208728\nMobile Phone: +86-158-28239155\nFax: +86-28-83201896\nE-mail: hzsong1296@163.com, hzsong@uestc.edu.cn\n \nEducation \nSept, 1990 – July, 1995:Peking University, PhD, Thesis “Visible luminescence of porous silicon and its mechanism”, Researches on hydrogen-influenced Schottky diodes and silicon-based light-emitting materials. \nSept, 1986 – July, 1990:Nanjing University, Bachelor of Science, Thesis “Study of refractory metal silicides”, Research on Ohmic contact of semiconductors.\n\nWork Experience \nJuly, 1995 – Sept. 1997: Nanjing University, Nanjing, China, Postdoctoral Researcher, Research on silicon-based light-emitting materials. \nOct, 1997 – Sept. 1998: Catholic University Leuven, Leuven, Belgium, Visiting free Researcher, Research on amorphous semiconductors. \nOct, 1998 – Sept. 2001: Tsukuba University, Tsukuba, Japan, Assistant Professor, Research on semiconductor quantum dots. \nOct, 2001 – March 2012: Fujitsu Lab. Ltd., Atsugi, Japan, Researcher/Senior Researcher, Researches on Semiconductor Quantum Dots for Quantum Information, Semiconductor Optoelectronic Materials and Devices. \nApril, 2012 – March 2014: University of Tokyo, Tokyo, Japan, Senior Researcher, Researches on Quantum Information Processing Devices. \nApril, 2014 – now: Southwest Institute of Technical Physics, Chengdu, China, Professor, Researches on Semiconductor Optoelectronic Materials and Devices. \nJune, 2015 – now: University of Electronic Science and Technology, Chengdu, China, Professor, Researches on Nanoscaled Semiconductors and Quantum Information Processing Devices.\n \nAchievements\nSystematically studied the property of porous silicon materials and verified their mechanism; found green and ultraviolet luminescence, and clarified the multiple luminescence mechanisms of nanocrystalline-silicon embedded in SiO2, which is valuable to silicon-based optoelectronic integration; realized enhanced hole mobility in amorphous silicon, verified the existence of deep trap states in amorphous selenium, providing ways to improve amorphous optoelectronic materials. \nDiscovered lateral coupling between self-assembled quantum dots (QDs) and their tuning effect to 2D electron gas; illustrated and deeply explained the metal-insulator transition in 2D ordered QD arrays, all of which are worth in optoelectronic application of semiconductor QDs. \nDeveloped Sb-free technique to double the InAs/GaAs QD density and suppress the atomic interdiffusion, helped producing 1.3 um QD lasers, which won Japanese national prizes and had been merchandized; developed 1.06 um quantum-well lasers, which have been used to produce pure-green lasers robust against high temperature. \nFound a way to access buried QDs by scanning tunneling microscope; achieved a way to prepare diluted QDs by post-annealing and clarified its mechanisms; invented a technique to control the size and site of QDs by atomic-force microscopy lithography, and an apparatus to detect single electron spin states by optically-detected magnetic resonance; designed a few types of micropillar cavities applicable to realize 1.55 um highly-efficient, even coherent (strongly coupled) InAs/InP QD single photon sources; produced fiber-integrated photon-entangled sources, all of which are very useful to the applications of QDs in quantum information processing. \nDeveloped focal-plane single-photon avalanche detectors, providing central devices for 3D laser detecting and ranging system; explored antimonide middle- and long-wavelength infrared detectors and the surface plasmon enhancement effect in such detectors; advanced the acetone-sensing function of Eu-doped SnO2 nano-belt; found Nickle Phosphide serving as a good catalyst in hydrogen-producing. Realized a series of optoelectronic quantum devices for quantum information processing, such as fiber-integrated photon-pair-entangler, chiplet heralded single photon emitter, fiber quantum memories, quantum number generator, etc.\n\nHonor and Group Memberships \nSelected Scholar of the Recruitment Program of Global Experts, China\nEditorial member of “Laser Technology”\nEditorial member of “Journal of Electronic Science and Technology”\nEditorial member of “Internal J. Mat. Sci. Appl”\nMember of APS (American Physics Society)\nMember of OSA (Optical Society of America)\nPermanent Member of China Physical Science and Technology\nPermanent Member of the Chinese Optical Society\nTechnical committee member of PIERS, organizing a series of “quantum information processing and devices” sessions\nTechnical committee member of ICICM",institutionString:"Southwest University",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"2",totalChapterViews:"0",totalEditedBooks:"0",institution:{name:"Southwest University",institutionURL:null,country:{name:"China"}}}],coeditorOne:null,coeditorTwo:null,coeditorThree:null,coeditorFour:null,coeditorFive:null,topics:[{id:"20",title:"Physics",slug:"physics"}],chapters:null,productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"},personalPublishingAssistant:{id:"453623",firstName:"Silvia",lastName:"Sabo",middleName:null,title:"Mrs.",imageUrl:"https://mts.intechopen.com/storage/users/453623/images/20396_n.jpg",email:"silvia@intechopen.com",biography:null}},relatedBooks:[{type:"book",id:"8356",title:"Metastable, Spintronics Materials and Mechanics of Deformable Bodies",subtitle:"Recent Progress",isOpenForSubmission:!1,hash:"1550f1986ce9bcc0db87d407a8b47078",slug:"solid-state-physics-metastable-spintronics-materials-and-mechanics-of-deformable-bodies-recent-progress",bookSignature:"Subbarayan Sivasankaran, Pramoda Kumar Nayak and Ezgi Günay",coverURL:"https://cdn.intechopen.com/books/images_new/8356.jpg",editedByType:"Edited by",editors:[{id:"190989",title:"Dr.",name:"Subbarayan",surname:"Sivasankaran",slug:"subbarayan-sivasankaran",fullName:"Subbarayan Sivasankaran"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"1591",title:"Infrared Spectroscopy",subtitle:"Materials Science, Engineering and Technology",isOpenForSubmission:!1,hash:"99b4b7b71a8caeb693ed762b40b017f4",slug:"infrared-spectroscopy-materials-science-engineering-and-technology",bookSignature:"Theophile Theophanides",coverURL:"https://cdn.intechopen.com/books/images_new/1591.jpg",editedByType:"Edited by",editors:[{id:"37194",title:"Dr.",name:"Theophile",surname:"Theophanides",slug:"theophile-theophanides",fullName:"Theophile Theophanides"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"3161",title:"Frontiers in Guided Wave Optics and Optoelectronics",subtitle:null,isOpenForSubmission:!1,hash:"deb44e9c99f82bbce1083abea743146c",slug:"frontiers-in-guided-wave-optics-and-optoelectronics",bookSignature:"Bishnu Pal",coverURL:"https://cdn.intechopen.com/books/images_new/3161.jpg",editedByType:"Edited by",editors:[{id:"4782",title:"Prof.",name:"Bishnu",surname:"Pal",slug:"bishnu-pal",fullName:"Bishnu Pal"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"3092",title:"Anopheles mosquitoes",subtitle:"New insights into malaria vectors",isOpenForSubmission:!1,hash:"c9e622485316d5e296288bf24d2b0d64",slug:"anopheles-mosquitoes-new-insights-into-malaria-vectors",bookSignature:"Sylvie Manguin",coverURL:"https://cdn.intechopen.com/books/images_new/3092.jpg",editedByType:"Edited by",editors:[{id:"50017",title:"Prof.",name:"Sylvie",surname:"Manguin",slug:"sylvie-manguin",fullName:"Sylvie Manguin"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"371",title:"Abiotic Stress in Plants",subtitle:"Mechanisms and Adaptations",isOpenForSubmission:!1,hash:"588466f487e307619849d72389178a74",slug:"abiotic-stress-in-plants-mechanisms-and-adaptations",bookSignature:"Arun Shanker and B. 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In the 1970s developments such as the gene splicing method and in vitro fertilization (IVF) created concerns about the adequacy of these long-established moral obligations (Beauchamp & Childress, 2009, p. 1). In addition to technological developments, historically, horrifying medical experimentation in concentration camps (the Nuremberg trials in the late 1940s) and the following Helsinki Declaration on the protection of human subjects had influence on the establishment of ethics committees worldwide and a shift toward focusing on the moral obligation of respecting informed consent of research subjects (Andersen, 1999, pp. 11-15; Beauchamp & Childress, 2009, pp. 1, 117; Ebbesen, 2009).
The discipline of bioethics or biomedical ethics In this essay the concepts of bioethics and biomedical ethics are used interchangeable to describe the analysis and discussion of ethical problems of biomedicine.
Most research within the academic philosophical discipline of bioethics focus on theoretical reflections on the adequacy of ethical theories and principles. The principles of biomedical ethics of the American ethicists Tom L. Beauchamp & James F. Childress (2009) is an example. Beauchamp & Childress examined “considered moral judgements and the way moral beliefs cohere” and found that the general principles of beneficence, nonmaleficence, respect for autonomy, and justice play a vital role in biomedical ethics (Beauchamp & Childress, 2009, p. 13). They believe that these principles are an analytical framework and a suitable starting point for biomedical ethics (Beauchamp & Childress, 2009, p. 12). However, Beauchamp & Childress state that these four principles are not only specific for biomedical ethics; the principles form the core part of a cross cultural (universal) common morality. Beauchamp & Childress appeal to the common morality normatively by saying that the common morality establishes moral standards for everyone and failing to accept these standards is unethical. And, they appeal to the common morality descriptively by saying that it can be studied empirically whether the common morality is actually present in all cultures (Beauchamp & Childress, 2009, p. 4).
There is debate on whether the principles and method of Beauchamp & Childress are specific American and whether they can be used outside America, for instance in Europe and Asia. This essay examines these issues by introducing the theory of Beauchamp & Childress, by reviewing a Danish empirical study where Danish oncologists and Danish molecular biologists were interviewed, and lastly by outlining future perspective for broader empirical studies.
Beauchamp believes that people from different cultures share some moral rules in common. These moral rules are for instance “Tell the truth”, “Do not kill”, “Rescue persons who are in danger”, and “Do not steal”. These moral rules are not implemented the same way in all cultures, however, the norms themselves are cross cultural. According to Beauchamp, these rules are justified by more abstract general principles. There is a transparent connection between these rules and the more general principles. For example the moral rule of “Tell the truth” is justified by the general principle of respect for autonomy, the rule “Do not kill” is justified by the principle of nonmaleficence, the rule “Rescue persons who are in danger” is justified by the principle of beneficence, and lastly, the moral rule “Do not steal” is justified by the principle of justice. One rule can be justified by more than one principle; hence there is a non-linear connection between rules and principles. This shared, universal system of rules and principles constitutes what Beauchamp calls moral in the narrow sense or the common morality (Beauchamp, 1997, p. 26). He defines the common morality as “the set of norms shared by all persons committed to the objectives of morality. The objectives of morality, I will argue, are those of promoting human flourishing by counteracting conditions that cause the quality of people’s lives to worsen” (Beauchamp, 2003, p. 260). Beauchamp is aware that not everybody accepts or lives up to the demands of the common morality. This is not because these persons have a different morality; it is simply because they are immoral. Hence, the common morality is not just a morality that differs from other moralities (Beauchamp, 2003, p. 260). The common morality is “applicable to all persons in all places, and all human conduct is rightly judged by its standards” (Beauchamp, 2003, p. 260). Hence, the common morality provides an objective basis for moral judgment.
The moral rules and principles of the common morality are often so unspecific and content-thin that they only provide a basic guideline or orientation for addressing specific moral problems, for instance as to whether treatment without patient content is a moral acceptable enterprise (Beauchamp, 1997, p. 27). Practical moral problems of this kind require that the unspecific content-thin rules and principles of the common morality are made specific and implemented. Since answers to practical moral problems and the balancing of different values do often vary from one culture to another, specification and implementation of norms and principles are often done in different ways in different cultures. The universal system of rules and principles of the common morality does then form the basis or the starting point for this implementation (Beauchamp, 1997, p. 27-28). Beauchamp does not ignore that moral decision-making and practices vary from one culture to another, but they do not vary so much that the common morality is called into question. This plurality of moral decision-making and moral practices constitutes what Beauchamp calls moral in the broad sense introducing the concept of moral differences (Beauchamp, 1997, p. 27). Beauchamp believes that while the common morality or morality in the narrow sense “contains only general moral standards that are conspicuously abstract, universal, and content-thin” morality in the broad sense presents “concrete, nonuniversal, and content-rich norms” (Beauchamp, 2003, p. 261). Morality in the broad sense implements “the many responsibilities, aspirations, idealism, attitudes, and sensitivities that spring from cultural traditions, religious traditions, professional practice, institutional rules and the like” (Beauchamp, 2003, p. 261). Hence, Beauchamp argues that multiculturalism is not in opposition to universal ethical principles and he defends multiculturalism as a form of universalism (personal communication).
Beauchamp defends a moral framework of four clusters of moral principles which form the core part of the common morality. These four principles are: respect for autonomy (respecting the decision-making capacities of autonomous persons), nonmaleficence (avoiding the causation of harm), beneficence (providing benefits and balancing benefits, burdens, and risks), and justice (fairness in the distribution of benefits and risks). To interpret a principle is to tell what the principle is about and Beauchamp argues that the four principles are interpreted differently in different cultures. In figure 1 the four basic principles of the common morality are presented.
The four basic principles of the common morality. A brief formulation of the four ethical principles: respect for autonomy, beneficence, nonmaleficence, and justice (
The four ethical principles of respect for autonomy, beneficence, nonmaleficence, and justice can be used when managing complex or problematic cases of biomedicine. When the principles are used in biomedicine it is often necessary to make the principles specific for that actual case. A specification of a principle is to narrow its scope and making it action-guiding. Beauchamp & Childress explain specification as “a process of reducing the indeterminate character of abstract norms and generating more specific, action-guiding content” (Beauchamp & Childress, 2009, p. 17). Specification involves a fine-tuning of the range and scope of the principle by increasing information about that specific situation (what time, where, what persons are involved, and so forth). Each principle is prima facie binding, which means that it “must be fulfilled unless it conflicts, on a particular occasion, with an equal or stronger obligation” (Beauchamp & Childress, 2009, p.15). If principles conflict they can be justifiably overridden which is the act of balancing (meaning that none of the principles are absolute). Balancing principles tells about their weight and strength, when balancing two principles, one principle is infringed by another (Beauchamp & Childress, 2009, pp. 19-20). Beauchamp & Childress list six conditions that must be met to justify the infringement of one prima facie principle by another (figure 2). Beauchamp & Childress state that physicians’ acts of balancing and specifying ethical principles often involve “sympathetic insight, humane responsiveness, and the practical wisdom of evaluating a particular patient’s circumstance and needs” (Beauchamp & Childress, 2009, p. 22).
Conditions constraining balancing. Conditions that must be met to justify infringement of one prima facie norm in order to adhere to another (
The Danish physician and philosopher Soeren Holm states that the four principles of Beauchamp & Childress are developed from American common morality and that they reflect certain aspects of American society and therefore they are limited to America and unsuited for Europe (Holm, 1997). Two Danish ethicists Jacob Rendtorff and Peter Kemp present a European alternative to Beauchamp & Childress’ principles. Rendtorff & Kemp state that there are four ethical principles specifically suited for managing problematic cases of biomedicine in Europe, namely the principles of autonomy, dignity, integrity, and vulnerability (Rendtorff & Kemp, 2000). However, I believe that ethical principles always do contain obligations such as ‘you ought to respect …’. What Rendtorff & Kemp call principles do not contain obligations. Hence, strictly speaking, they cannot be considered as principles but as ethical concepts which can be reformulated into ethical principles. This can be done the following way: ‘Respect for autonomy’, Respect for dignity’, and so forth. Beauchamp does also argue that the so-called principles of Rendtorff & Kemp are not principles at all. For instance, Beauchamp considers integrity is a virtue and vulnerability as a property or condition of persons. Furthermore, he thinks that the concept of dignity is one of the most obscure concepts of bioethics, since nobody knows what dignity is. Moreover, as can be seen above, Beauchamp does not believe in specific European ethical principles (personal communication).
Beauchamp states that empirical research could prove him (or Rendtorff & Kemp) wrong. The hypothesis to be tested is that all persons committed to the objective of morality adhere to the common morality (and thereby to the four ethical principles, which form the basis of the common morality) (Beauchamp, 2003, p. 264). First, persons should be screened to test whether they are committed to the objectives of morality (which “are those of promoting human flourishing by counteracting conditions that cause the quality of people’s lives to worsen” (Beauchamp, 2003, p. 260)). Persons not committed to morality should then be excluded from the study. Next, it should be tested “whether cultural or individual differences emerge over the (most general) norms believed to achieve best the objectives of morality” (Beauchamp, 2003, p. 264). Beauchamp writes: “Should it turn out that the individuals or cultures studied do not share the norms that I hypothesize to comprise the common morality, then there is no common morality of the sort I claim and my particular hypothesis has been falsified” (Beauchamp, 2003, p. 264).
If it turns out that other general norms than the ones proposed by Beauchamp are shared across cultures, then the empirical study proves the presence of a common morality, however, of another sort than the one proposed by Beauchamp. Such an empirical study does not tell whether the norms of the common morality are adequate or in need of change. This is a normative question and not an empirical one (Beauchamp, 2003, p. 265). Beauchamp appeals to the common morality in both normative and nonnormative ways. The common morality has normative force meaning that it sets up moral standards for everyone and failing to accept these standards is unethical. Nonnormatively, Beauchamp claims that it can be studied empirically whether the common morality is present in all cultures. So, claims about the existence of the common morality can be justified empirically and analysis of the adequacy of the common morality involves normative investigation (Beauchamp, 2003, p. 265).
One of the aims of a Danish empirical study where oncologists and molecular biologists were interviewed was to test whether there is a difference in the ethical considerations or principles at stake between the two groups. Since this study explores part of Beauchamp’s hypothesis, he followed this study personally. This study was based on 12 semi-structured interviews with three groups of respondents: a group of oncology physicians working in a clinic at a public hospital and two groups of molecular biologists conducting basic research, one group employed at a public university and the other in private biotechnological company. The interview texts were transcribed word-for-word and analysed using a phenomenological hermeneutical method for interpreting interview texts inspired by the theory of interpretation presented by the French philosopher Paul Ricoeur. There were three steps in the data analysis. First, the texts were read several times in order to grasp their meaning as a whole. Next, themes were formulated across the whole interview material. And lastly, the themes were reflected on in relation to the literature which helped to revise, widen, and deepen the understanding of the texts (Ricoeur, 1976; Ebbesen & Pedersen 2007a).
The results of the study are summarised shortly. This empirical study indicated that oncology physicians and molecular biologists employed in a private biopharmaceutical company had the specific principle of beneficence in mind in their daily work. Both groups seemed motivated to help sick patients. According to the study, molecular biologists explicitly considered nonmaleficence in relation to the environment, the researchers’ own health, and animal models; and only implicitly in relation to patients or human subjects. In contrast, considerations of nonmaleficence by oncology physicians related to patients or human subjects. Physicians and molecular biologists both considered the principle of respect for autonomy as a negative obligation in the sense that informed consent of patients should be respected. Molecular biologists stressed that very sick patients might be constrained by the circumstances to make a certain choice. However, in contrast to molecular biologists, physicians experienced the principle of respect for autonomy as a positive obligation because the physician, in dialogue with the patient, offers a medical prognosis evaluation based upon the patients’ wishes and ideas, mutual understanding, and respect. Finally, this study disclosed a utilitarian element in the concept of justice as experienced by molecular biologists from the private biopharmaceutical company and egalitarian and utilitarian characteristics in the overall conception of justice as conceived by oncology physicians. Molecular biologists employed at a public university were, in this study, concerned with just allocation of resources; however, they did not support a specific theory of justice (Ebbesen & Pedersen 2007b, 2008a, 2008b).
This study showed that the ethical principles of respect for autonomy, beneficence, nonmaleficence, and justice as formulated by Beauchamp & Childress were related to the ethical reflections of the Danish oncology physicians and the Danish molecular biologists, and hence that they are important for Danish biomedical practice. Apparently, no empirical studies have investigated specifically the importance of the four principles previously; therefore, this empirical study contributes to an enhanced understanding of Beauchamp & Childress’ theory from a new point of view. It could be objected, however, that the study did not centre on respondents who had already been screened to assure that they are morally committed, as Beauchamp recommend. According to Beauchamp, a way of screening whether persons are committed to morality is to test whether they are committed to the principle of nonmaleficence since this principle can be seen as the most basic principle of morality (personal communication). All respondents included in the study valued nonmaleficient behaviour.
Beauchamp & Childress believe that their four basic ethical principles are included in the cross-cultural common morality (Beauchamp & Childress, 2009). However, as described above, some of Beauchamp & Childress’ opponents state that their theory has been developed from the American common morality and that it reflects certain characteristics of American society. Therefore, the theory might not be useful in other societies. Nevertheless, the results of the Danish empirical study demonstrate that the theory is related to Danish biomedical practice.
Future perspectives of the Danish empirical study are to explore whether Beauchamp & Childress’ principles are cross-cultural and thereby have a universal perspective. This could be done by investigating whether there is a difference in the ethical considerations and principles at stake between physician oncologists working in different cultural settings (e.g. Scandinavian, Southern European, Asian, and American cultures). For instance, in Japan the principle of respect for autonomy is said to be more family oriented than in America (Fan, 1997). What is needed is a qualitative investigation of Japanese culture. This future study might show that Beauchamp & Childress’ principles need reformulation to be used in specific cultural settings.
The energy demand is increasing concurrently with the increase of the world’s population and meeting the increasing energy demands including managing social, economic, and ultimate environmental issues are one of the greatest challenges of the present time. Solar energy, as one of the promising renewable energy sources, is becoming an important source of energy all over the world. Its huge development potential has attracted a lot of attention and the photovoltaic (PV) industry has been experiencing a large-scale development to replace traditional energy. Also, a significant increase in energy conversion efficiency and the decrease in the price of the solar panels along with various national policies over the world enhanced the solar PV-based energy generation with the least Levelized-cost-of-energy (LCOE). However, for getting optimum output, proper resource estimation is necessary to assess the feasibility of solar PV systems in any area. The output of any PV system’s output indeed depends on the weather of its surroundings will be elaborated in this chapter.
In contrast, there are several types including different technologies of photovoltaic modules in the market. However, the technological choices are very critical in the sense of the lack of guide and forecasting tools suited to the climates and environment of the installation sites. There have been many PV system projects going to fail due to the bad choice of PV technology where failure causes are influenced by the environmental parameters, such as heat, humidity, shadow, and dust, etc. Manufacturers provide a characteristic of PV modules measured in standard test conditions (STC), however, the performance cannot reach that level in real operating conditions. Besides, the PV module’s performances and aging strongly depend on the climate and the surrounding environment of the installation site.
The investigation of PV performance under real external conditions became an important factor as a result of increasing trends of PV capacity over the world. Particularly, the performance of the PV module influence by the number of different external issues, such as, (i) spectral irradiance, i.e., the wavelength of incident light and light intensity, the efficiency of PV certainly varied with the variations in the spectrum of sunlight [1, 2, 3, 4] and light intensity directly affect the short circuit current [5]; (ii) reflectivity of the module surface, however, the reflectivity that occurred in the module surface depends on the angle between the module surface and the incident angle [6]; and (iii) module temperature, particularly temperature of the module surface increases to 60-80 °C at noon and cause of the reduction in open-circuit voltage which also depend on the light intensity and airflow [7]. Thus, in each PV field, the factors that contribute to solar cell efficiency are different and the important considerations applied in each area are different. On the other hand, some types of PV modules show the degradation of power conversion efficiency under the long-term light exposer in the field and/or elevated temperatures. Particularly, due to the above-mentioned effects, the module efficiency and/or electrical parameters are observed to deviate from the nameplate value measured under Standard Test Conditions (STC) [8] in the real external condition. Besides, there are some other causes for which the energy production capability of a PV module is affected, such as installation angle; possible shadow, dust or snow deposition, etc. However, these mostly depend more on the details of the installation, not inherent to the module type and the physical properties of the module. It could be mention that the power output could vary as an impact of the above-listed causes while different types of the module installed in the same way; alternatively, similar types of module generate different power output due to the installation in a different way or different places. The variation of PV performance has been investigated by several authors in terms of geographical variability and technology. Some authors only focused on the effect of solar irradiation while other authors consider some of the above-mentioned factors. In this study, we also only reviewed the study that focuses on the effect of solar irradiance on the different PV technology.
Solar irradiance on different locations of the earth is shown in Figure 1 [9]. The maps highlight the global horizontal irradiation (GHI) which means that the overall irradiance from the sun reaches the earth’s horizontal surface. It is related to the diffuse horizontal irradiance (DHI) and direct normal irradiance (DNI) as follows [10],
Global horizontal irradiation (GHI) over the world [
Where θ is the solar zenith angle. Areas with a high proportion of GHI include South-East China, Northern Europe, and the tropical belt around the equator.
Since the electrical performance of PV devices is greatly affected by the incident light spectrum, hence, significant efforts have given by the PV community to develop methods and evaluate the impact of the spectral variations on the PV device performance over the last three decades. The parameters that have the highest impact on the spectrum distribution as well as on the PV module performance are (i) the air mass (AM), (ii) the perceptible water (PW), and (iii) the aerosols optical depth (AOD) [11].
The AM is a measure of the atmospheric absorption that affects the spectral content and the intensity of the solar radiation coming to the earth’s surface. The impact of AM on the solar spectral distribution is shown in Figure 2 [11]. Particularly, the solar spectral distribution just above the Earth’s atmosphere-in the relative vacuum of space is commonly referred to as an air mass zero (AM0). And the AM = 1.0 at sea level when the sun is directly overhead (zenith angle, θz = 0). As the θz increases, the path passes by the sun spectrum through the atmosphere become longer, and AM increases. The AM could estimate simply using a trigonometric function of the zenith angle:
Impact on the direct spectral irradiance of air mass (AM) simulated with the SMARTS model [
where θz is the angle of incidence or solar zenith angle.
The above equation is quite accurate for θz ≤80 degrees, however, more complex and precise models are necessary when the sun goes near the horizon. Moreover, the distribution of the outdoor solar spectrum varied during the day due to the presence of water vapors and aerosol in the air. Thus, the real spectrum at the earth’s surface is infrequent to fit with the AM1.5 standard solar spectrum as defined in standard IEC 60904–3 and/or ASTM GE173–03 [12]. Specifically, the spectral power distribution observed in the sun at an angle of about 48.2o is specified as AM 1.5 spectrums (as in Figure 3(a)). The power density of AM1.5 light is about 1,000 W/m2. The standard AM 1.5 spectrum is known as solar constant and is normally used in solar cell analysis. Figure 3(b) shows the spectral distribution of sunlight under the different air masses.
(a) The path length (in units of air mass) changes with the zenith angle (b) spectral distribution of solar energy [
Another important parameter that needs to be considered for understanding solar irradiance on the earth’s surface is the clearness index (KT). Particularly, KT is defined by the ratios of the solar radiation for a particular day and the extraterrestrial solar radiation for that day. It could also be defined by hourly as shown below:
Where H and I represent the total measured and Ho and Io are represent the extra-terrestrial solar radiation which could be calculated using several approaches [14]. This value of KT or kT lies between zero and one which contingent on atmospheric conditions. For clear sky conditions, KT is near 1 and if the sky is very cloudy and/or turbid and/or heavily overcast, KT becomes less than 0.4. Several laboratories have been developed computational models considering spectral direct beam during the clear sky and hemispherical diffused irradiances on a surface either horizontal or tilted condition for a certain location and time [15]. Other than the above parameters, the outdoor energy yield and performance of the PV modules further depend on a large number of on-site factors or local factors such as ambient temperature, wind, and rain. These undefined factors may also influence significantly amount of solar radiation that arrives on the surface of the PV module. Certainly, it is important to analyze the influences of all the above on-site environmental factors on the outdoor performance of different types of PV modules, for finding out the best-suited technology for a specific location and enabling more widespread deployment.
The electrical power generated in a solar cell or PV device can be modeled with a well-known equivalent circuit as shown in Figure 4 which includes a shunt resistance parallel with a diode and a series resistance [16].
Equivalent circuits for a solar cell in a single diode model, including series and shunt resistance [
This equivalent circuit can be used for either an individual cell, a multi-cell module, or an array consisting of multiple modules. Using this model and considering constant temperature and solar radiation, the current–voltage equation for a solar cell or module could be expressed as shown in Eq. (4).
Where, IL is the light generated current, Io is the dark saturation current, Rs is the series resistance, Rsh is the shunt resistance, A is the modified cell or module ideality factor that can be expressed as:
where Ns is the number of cells or modules that are connected in series, ni is the diode ideality factor for a cell, K is the Boltzmann constant, qe is the electron charge, T is the cell or module temperature.
Figure 5 shows the current–voltage (I-V) characteristic curves of a solar cell or a module. Particularly, the power generated by the solar cell or module is the product of the current (Imp) and voltage (Vmp). It should be noted that five parameters, such as IL, Io, Rs, Rsh, and A, determine the current and voltage generated in a cell or module, thus the impact of external factors, such as solar radiation and temperature could be analyzed from the change of these values. In general, the FF is directly affected by series resistance, and it is found that the fill factor of a solar cell decreases by about 2.5% for each 0.1 Ω increase in series resistance [17]. On the other hand, Rsh is reduced if the leakage current is increased in a solar cell. If there any light and temperature-activated defects available in a solar cell, then leakage current could be increased, alternatively Rsh could be reduced as the increase of irradiance intensity or temperature. Finally, FF and Voc will be reduced. For an ideal case, Rs = 0, Rsh = ∞ and ni = 1, the open-circuit voltage, Voc could be expressed as,
Typical current–voltage (I-V) and power-voltage characteristic curves of a solar cell.
For a very small applied voltage (V ≈ 0), the diode current, Io is negligible or zero, then from Eq. (6), we can find,
Where Isc is a short circuit current. Now Eq. (9) becomes,
The Voc and Isc rectangle description as shown in Figure 5 offers a useful means for characterizing the maximum power point [18]. The fill factor (FF) is defined as the ratio of the maximum power to the product of Voc and Isc and is less than one at all times. FF indicates the squareness of the I-V curves and can be defined from the ratios of two rectangles (Figure 5) as,
Where Pmp denotes the maximum power of the solar cell or module, Imp and Vmp are the current and the voltage values at the maximum power point, respectively. Moreover, the most significant Figure of merit for a solar cell or PV module is its power conversion efficiency, η, which is specified as,
Where Pin denoted the power of incident light that is determined by the characteristics of the light spectrum incident onto the solar cell or PV module. The power of the incident light spectrum, Pin can be express as,
Where A is the surface area of the solar cell or PV module and G is the total spectral irradiance, which could be defined as [19],
Where, f(λ) is the flux density (number of incident photon per unit area and unit time) for a specific wavelength of the photon with energy, ελ and wavelength, λ.
Particularly, the light to the electrical power conversion efficiency of a solar cell or a module is an inherent property that depends on the type of semiconductor material and the manufacturing process. However, this efficiency also depends on the environment of the installation site, especially on the hours of equivalent peak spectral irradiance in a day and/or temperature. The PV module characteristics that we find in the nameplate are typically measured at standard testing conditions (STC), the irradiance of 1000Wm−2 at AM 1.5 and 25 °C of cell temperature. In fact, these conditions hardly exist because the outdoor spectrum is far different from the STC condition, which also varied by location and season. The response to the spectral variation by different types of PV modules vastly depends on its material properties and structure. This response is primarily determined by the bandgap of the materials used in fabrication, which sets the upper wavelength limit of the spectral response (SR). More specifically, SR is depending on the PV material’s bandgap, cell thickness, and carrier transport mechanisms in the device. Secondly, device structure, means the position of the absorber material and other supporting layers has a significant effect on the spectral response. Also, the variation of electrical parameters of different types of PV module/device as an impact of various environmental factors depends on the technology (device structure and materials). On the whole, the PV device performance and SR is proportional for specific PV devices, where SR is defined as:
Where JL(λ) represents the light-generated current density for a specific wavelength “λ” and G(λ) is the spectral irradiance of the incident light measured in W/m2-nm. However, in state-of-the-art solar cell or PV modules, the spectral response is defined as the short-circuit current, Isc(λ), resulting from a single wavelength of light normalized by the maximum possible current [20, 21, 22, 23].
Where, q is the electronic charge 1.6 x 10–19 C, A is the surface area of the PV device and f(λ) is the incident photon flux (number of photons incident per unit area per second per wavelength). Besides, the SR of the PV devices is also estimated in terms of quantum efficiency (QE), which indicates that how efficiently a PV device converts the incident light to a charge carrier that flows through the external circuit [24], details on QE has been discussed next section. In that case,
In the case of PV modules, JL is approximately the same in value as the short-circuit current density (Jsc) [25]. Thus, with the help of the above equations, Jsc can be expressed as,
It could be seen in Eq. (16) that Jsc can be estimated by the SR for PV modules which certainly have prime importance in evaluating PV materials and device characteristics. Particularly, the degree to which the SR and the incident irradiance spectrum varies gives rise to a spectral effect on the device current and efficiency. The SR of different types of the module at AM1.5G spectrum (up to 1300 nm) is shown in Figure 6 to confirm the response is different for different technologies [10]. As seen in Eq. (16), Isc is affected by the spectrum. Particularly, the spectrum variations are also influenced the other PV output parameters, viz. FF, Voc, and η. To determine the magnitudes of these effects on different technology-based PV devices, various performance review studies were carried out [26, 27, 28, 29, 30, 31].
Spectral response characteristics of different solar module technologies, modified from [
Particularly, The SR shows represent the current produced by a solar cell for per watt of irradiance at each wavelength of the photon. As seen in Figure 7 that SR towards the higher wavelength region is lower because photons in this region have energy less than the material bandgap threshold. As a result, the effect of spectral variation on the output of PV devices is most pronounced in narrow SR technologies such as a-Si and CdTe. Especially narrowest SR is seen for the a-Si that is also discussed in the literature [32, 33, 34, 35]. For simplification of SR and PV performance, research is commonly used one-dimensional terms, such as spectral mismatch factor (MMF) [32, 33, 34, 36], the useful fraction (UF) [37], average photon energy (APE) [38, 39]. In the case of MMF and UF, their values should be a known factor for a specific module understudy, however, the SR data is not available publicly and analysis complexity arises. Besides, APE is denoted by the unit of an electron volt (eV) which signifies the average incoming photon energy. The equation for calculating is as follow:
(a) variation of EQE, IQE, and reflectance with the wavelength of a c-Si solar cell (collected and modified from Wikipedia), (b) EQE of different PV solar cell technology [
Where, E(λ) represents the energy of the incident photon and f(λ) is the incident photon flux at wavelength λ, and pλ and qλ are the integration limits indicate the lower and higher absorption wavelength, which are 300 and 1200 nm as shown in Figure 7. Particularly, APE varies on a daily and seasonal basis due to the increase of air mass at sunrise and sunset compared to noon and in winter compared to summer. For example, when the sun is above the horizon, the spectral irradiance is red-shifted and the APE becomes low. APE rises again to a high around noon during the day. Moreover, the APE is higher in the summer months than in winter because the zenith angle of the sun is higher in summer. Besides, the atmospheric water, cloud cover, and/or aerosol content affect the APE due to light absorption and scattering. For most of the PV modules, the APE effect on performance seems to be linear. The spectral photon flux density denoted in joules can be expressed as below for a specific wavelength λ:
where ‘h’ is the Planck constant and ‘c’ is the light velocity in vacuum.
The SR and QE are conceptually similar to each other. Particularly, SR is the ratio of the generated current in a solar cell per unit incident power, while QE denoted the ratio of the number of generated carriers and the number of the incident photon on the solar cell. In another way, the QE of a solar cell represents the amount of current the cell produces for a particular wavelength of an incident photon. Knowing the QE of a particular PV technology is important because by integrating QE for the whole solar spectrum, the current generation capability of PV solar cells could be realized. Interestingly, the QE value could exceed 100% for a PV solar cell in the case of multiple excitation and generation (MEG). In that case, one incident photon could generate several electron–hole pairs as an impact of multiple excitations. The MEG properties are typically seen in quantum-dot solar cells [40]. However, all the incident photons on the cell surface cannot be absorbed due to surface optical properties, such as absorption and reflection. Thus, QE is divided into two terms, (i) external QE (EQE) and (ii) internal QE (IQE) which simply differ by the photons reflection properties of a PV solar cell. In the case of EQE, all photons that impinge on the cell surface are taken into account, while in the case of IQE, only photons that are absorbed (not reflected) by the solar cell are considered. The graphical representation of EQE and IQE is shown in Figure 7.
High EQE is a precondition for high-power PV applications, which depends on the absorption coefficient of the absorber material of a PV solar cell, the carrier excitation quality, and carrier recombination rate or the amount of electron transport to the electrodes. The mentioned QE in Eq. (15) is typically EQE, which is directly related to the current generation by a solar cell [41]:
Where, with q is the charge of electron and φλ(λ) the incident spectral flux density, indicating the incident number of photons of wavelength λ on the cell surface per unit of area, per unit of time and EQE could be defined as:
The relation between IQE and EQE could be defined as:
Where L is the total optical loss that occurred in a solar cell either through reflection or transmission or both. Particularly, for maximizing EQE, the optical loss should be minimized. To reduce the optical loss, anti-reflection coating, and back-reflection coating is applied in the current PV technologies.
Solar irradiance and surface air temperature are two key factors for investigating the PV module performance. Particularly, the increase in solar irradiation is a cause of the increase in air temperature and vice versa. On the other hand, the increase in solar irradiance is proportionally increased the power output of the PV module, however, module output decrease with the increase of temperature [42]. Usually, the output and temperature of the PV modules are considered to be linear. The effect of temperature mostly depends on the absorber material and its quality. From the module electrical properties, the temperature effect could be realized by observing the variation of the device parameters:
In the case of Isc and FF, there is very little change that occurred with temperature for crystalline silicon and thin-film devices. Alternatively, the Voc is highly dependent on the temperature variation, which can be described via the Voc as calculated from the one diode model as shown below:
And,
Where VT is known as thermal voltage, T is the solar cell temperature, k is the Boltzmann constant, q is the elemental charge q, n is the ideality factor and I0 is the diode saturation current. From the above diode equation, it could seem that the Voc is positively changing with the temperature, because the above-simplified diode equation typically overlooked the parasitic factors, such as solar cell series and shunt resistance. Particularly, this parasitic resistance is changed significantly over thermal variation [43] and greatly impacts the voltage and diode saturation current as reported elsewhere [44]. For understanding the impact of temperature on Voc, we have to consider the temperature-dependent diode saturation current, which in turn:
Where B is a temperature-independent empirical factor but controlled by the quality of absorber material, γ is also an empirical factor that relies on the specific carrier loss mechanism and Eg is the absorber material bandgap. The influence of irradiance and module temperature can be explored by combining the data according to these dependencies. The resulting matrix can then be used to model the annual yield for various technologies at different locations [45]. The main uncertainties, in this case, are kWp standardization and input irradiance [46].
As there are several uncertainty factors are involving, for the easy and efficient deployment of PV solar cell system, it is essential to measure and develop a model for the spectral distribution of solar radiation. Colle et al. [47] have shown that there has a linear relationship between the uncertainty of solar irradiation and the uncertainty of solar thermal and PV systems. This is a big challenge in the 21st century to develop a more efficient and robust model that could reduce the solar radiation misprint include will need fewer input parameters, will have smaller residual and can be used in a wide variety of conditions.
Indeed, the solar spectrum depends on the place, time, and condition of the atmosphere. The global solar spectrum may be divided into two spectrum models, one for direct beam radiation and the other for diffuse radiation. Particularly, the spectrum of solar incident radiation wavelengths on the PV modules corresponds to the appropriate spectral response range of the PV cells. Several reports on the effect of spectral irradiance variation and PV solar cell performance can be found elsewhere [48, 49]. The longer irradiation hours provided the better annual average electricity outputs [50]. The effect of solar spectral irradiation on the yield of several PV technologies has been documented by Nann and Emery at four separate locations [51]. Eke et al., on the other hand, found that the spectrum variance had a very limited effect on the low bandgap absorber content in PV solar cells [52]. Figures 6 and 7 shows the spectral response characteristics and EQE of different PV technologies which indicate that how the performance of PV module could change upon the variation spectral distribution.
Several solar spectrum models, including SPECTRAL2 [53], LOWTRAN2 [54], REST2 [55], and SMARTS2 [56], have been developed yet to date over time for clear skies. These models are usually computer programs developed to evaluate the shortwave spectrum components of surface solar irradiance in the range of 280 to 4000 nm. Some of them have high spectral resolutions, however, they need very complex calculations making them less efficient. In the case of LOWTRAN(2), detailed inputs are needed, which increases the execution time and creates some performance limitations, that’s why the use of this model is limited in engineering applications [57]. On the other hand, even a low number of parameters are needed for SPECTRAL2, however, the mean deviation associated with different aerosol models is higher than SMART2 [58]. On the other hand, transmittance parameterizations based on the SMARTS spectral model are used to build the high-performance REST2 model [57]. Particularly, more updated parametric functions and constants are used in the SMARTS2 model, for which it has a higher resolution and is showing lower deviation in the spectral analysis. SMARTS program is written in FORTRAN and depends on simplifications of the radiative transfer equation which allow very quick calculations of the irradiance of the surface. The newest versions, such as SMARTS2.9.2 and SMARTS 2.9.5 are hosted by NREL.
The SMART model uses different inputs to define the conditions of the atmosphere under which the irradiance spectra are to be measured. Ideal conditions can also be selected by the user, based on various potential model atmospheres and aerosol models. Moreover, it is also possible to determine practical conditions as inputs, based, for example, on aerosol and water vapor data supplied by a sun photometer [59]. Besides, the spectrally integrated (or ‘broadband’) irradiance values are given by this model, which can later be compared with measurements from a pyranometer (for diffuse or global radiation) or pyrheliometer (for direct radiation). Solar geometry is another vital input in this model in addition to the atmospheric condition, which is typically specified by the position of the sun (zenith angle and azimuth), the location, the air mass (AM), or by specific time and date. More details on the usage of the SMARTS model for PV applications can be found elsewhere [60, 61, 62, 63]. Particularly, this model is frequently employed to evaluate PV modules’ efficiency and mismatch factors in real-world conditions [64, 65, 66]. Figure 8 shows the direct normal irradiance spectra with SMART 2.9.5 for different air mass.
Direct normal irradiance spectra calculated with SMARTS 2.9.5 for increasing air mass (0 to 10), using the same atmospheric conditions as the ASTM G173 standard. Air mass 0 corresponds to the extraterrestrial spectrum, marked as top of atmosphere (TOA), modified from [
Crystalline silicon (c-Si) is the most prevalent PV technology on the market (c-Si). In considering crystal size and crystallinity, c-Si can be divided into two major categories, mono or single-crystalline Si (sc-S) and multi or polycrystalline Si (mc-Si). The power conversion efficiency of sc-Si is higher than mc-Si solar cells, alternatively, sc-Si is costly than mc-Si. The typical efficiency of commercial c-Si modules is between 11% and 20% which power generation varies by temperature (temperature coefficients) in the range of 0.3–0.5%/K [68]. Commercial c-Si modules consisting of 200–500 μm thick PV cells that are connected in series and/or parallel for attaining expected voltage and current. It is important to note that c-Si solar cells or PV modules can generate electrical energy for a wide range of the spectrum (350–1200 nm) as illustrated in Figure 9 [69]. However, the absorption coefficient of c-Si is below 104 cm−1 for all wavelengths larger than 500 nm as shown in Figure 9. This means that all the potential photons below 500 nm are absorbed close to the surface of the cell. Thus, it is important for the c-Si solar cell that the active region has to be located near the cell surface for absorbing all potential photons and achieving optimum efficiency. Also, it could be seen in Figure 9 that the absorption coefficient is below 2.0 x 104 for wavelength above 650 nm. As the absorption coefficient of c-Si is below 103 for wavelengths above 700 nm which indicates that photons in this range can penetrate the bulk and generate electron–hole pairs. However, their contribution to the photocurrent is very hard in the case of conventional c-Si solar cells. Thus, for collecting these bulk carriers, the configuration of conventional c-Si structure modified, by names they are passivated emitter and rear contact (PERC) [70], passivated emitter and rear locally-diffused PERL [71], interdigitated back-contact (IBC) c-Si [72] solar cells.
Absorption spectrum of Si, CdTe, and CIGS solar cells, modified from [
As it has been mentioned earlier that the response to spectral variation by different types of PV modules vastly depends on its material properties and structure, c-Si solar cells also showed different characteristics depending on the irradiation properties. Several studies have been reported on the in-field energy output analysis of c-Si PV systems by Panchula et al. [73] based in Ontario, Canada; Dolara et al. [74] based in Tuscania, Italy; Fiances et al. [75] Based on a different place in Peru, Kazem et al. [76] based on the desert area of Sohar, Oman, Fuentes et al. [77] and Muñoz et al. [78] under warm climate of Spain, Bahaidarah et al. [79] based on Dhahran, Saudi Arabia and Edalati et al. [80] based on Kerman, Iran. In the above reports, they typically estimate the performance of the system based only on average monthly or yearly insolation and performance ratio varied by the location ranging from around 0.7 to 0.85. Fiances et al. [75] studied different Si technology includes sc-Si, mc-Si, a-Si, and μc-Si PV modules in the climate of Peru, and finalize that a-Si/μc-Si PV modules perform much better than others with an annual performance ratio of 0.97. Ahmed Ghitas [81] reported the effects of the spectral variations on the mc-Si module performance based on outdoor measurements in daily irradiation changes. They only consider cloud-free days in Helwan, Egypt in their measurements and also did not consider the temperature effect. The variation of Voc, Jsc, and power concerning radiation intensity is shown in Figure 10. It is evident from Figure 10 that the most affected device parameter is Isc, and output power in the case of the mc-Si PV module.
(a) Daily profile of the measured solar module short circuit current, open-circuit voltage, and electrical output power, (b) daily profile of incident solar radiation along with module output power, and (c) spectral irradiance variation versus time (a.ms) on a clear sky measurement day [
Eke and Demircan [82] have been studied mc-Si PV module performance based on winter (January) and Summer (August) for Mugla, Turkey. The operating temperature at this location is 50.5 °C in January and 80.5 °C on August 16. The power generation of the module is 30% lesser in summer than winter because of the significant difference in operating temperature. The power generation every day in January and August is shown in Figure 11. Bora et al. [83] also studied the pc-Si PV module along with a-Si, HIT-Si PV modules under the climate condition of the different parts of India. They find that all these three types of Si-based PV modules produce the highest energy yield in the cold and sunny zone.
PV module performance in January (a) and august (b) 2008 for Mugla, Turkey environment [
It is important to mention that the energy yield analysis of a PV system is incomplete if their low light condition analysis is missing. Reich et al. [84] have reported the performance of c-Si at low light conditions, however, the impact of temperature is missing as they conducted the study focusing on indoor performance. The finalized that the obtained efficiency via indoor measurement and rated efficiency has a significant difference. Certainly, temperature is a dominant factor in the performance of the PV system in outdoor conditions. It should be noted that solar irradiance and ambient temperature are proportional. Chander et al. [85], and Atsu and Dhaundiyal [86] studied output yield using a detailed model that includes temperature and wind speed variation. Chander et al. [85] reported that the performance parameters of the sc-Si module such as Voc, Pmax, FF, and efficiency are decreased with temperature while the Jsc is increased. Bahaidarah et al. [73] also suggested that for achieving the highest PV performance yield in Saudi Arabia, a suitable and uniform cooling system is necessary due to the climatic conditions. A detailed study on performance variation by low light conditions along with the temperature variation effect has been presented by Pervaiz and Khan [87]. In their modeling, they used various insulation profiles for a different location in the US collected from NREL. They reported that the energy harvesting of a PV system for a specific location depends on the average peak sunlight hours of that location as shown in Figure 12. The use of the following equation for calculating energy difference concerning the variation of Equivalent Peak Sunlight Hours (EPSH).
Energy difference (D) in percent for Washington, Seattle, and Austin for years 2000–2003 [
Where Ei is the energy harvested during one year considering a constant efficiency and Ec is the energy harvested incorporating a change in efficiency. The finalized that the reduction in energy yield is reliant on the EPSH of a region where reduction factor could range from 1.5 to 5% for various regions concerning the value of the EPSH.
Cotfas and Cotfas [88] have been studied details on the performance of sc-Si and a-Si PV modules under the natural condition via years of observation, in Brasov, Romania. They reported that the average Pmax of the sc-Si module is two times greater than the a-Si module, however, on clear winter days, the values even increase near to three times greater. Also, at low irradiance, under 100 W/m2, the power gain is of sc-Si is 1.9 times greater than a-Si. The gain is over 1.9 times even for very low irradiance, under 100 W/m2. The detailed performance of the a-Si PV module including other thin-film modules as an impact of irradiance and temperature are covered in the next section. Under the Mediterranean climatic conditions of the north of Athens, Greece [89], the performance of the p-Si photovoltaic system has been investigated. There is a linear relationship between the module surface temperature and the irradiance where the average temperature about 49.9 °C in summer and 16.8 °C in winter. The efficiency of the p-Si module has been significantly dropped in summer where it ranging from 6.2% to 10.4% concerning the module temperature.
The SR of PV cells depends on the absorption coefficient and/or bandgap of the absorber materials. Similarly, the performance variation by increase or decrease of temperature also depends on the bandgap [90]. The semiconductor material with a wider bandgap, such as 1.04–1.68 eV for CIGS [91], 1.45–1.5 eV for CdTe [92, 93], and (1.7–1.9 eV for a-Si [94] shows higher temperature resistance to the increase of module temperature. As a consequence, they have a lower temperature coefficient than sc-Si and pc-Si PV modules [95], and thus, device performance is significantly affected by the temperature. The details on the effects of irradiance, spectrum, and temperature on thin-film PV modules were investigated by Gottschalk et al. [96] under the UK environment. It has been reported that the performance of a-Si is highly spectral dependent as shown in Figure 13. The relative change in short circuit current (Isc) is +10% to −20% observed for a-Si whereas the change is only ±3% for c-Si and CIGS. Environmental effects have also been shown to cause up to 15% of losses to the annual PV production. The spectral impact on different PV technologies for all single months has been investigated under the German climate condition [32]. Similar to the other reports, the spectral impact changes more for bigger bandgap a-Si PV modules as shown in Table 1. The average gains over the year are 3.4% for a-Si, 1.1% for c-Si, 0.6% for CIGS, and 2.4% for CdTe. It has been reported that CIGS and c-Si modules exhibit high gains in winter and a-Si and CdTe shows an advantage in summer attributed mostly to spectrum variation [32]. The study carried in the Netherlands [97] showed that low irradiance caused a decrease in annual energy yield of 1.2% for the CIGS modules and 1% for CdTe. This experimental study also indicated a strong effect of spectral variation on the performance of the a-Si modules.
Calculated spectral effects for the devices under test in the UK environment. The graph compares the normalized ISC divided by the irradiance measured with the pyrometer [
Gi [kWh] average monthly irradiation from the reference period | Average, relative monthly spectral impact | |||||
---|---|---|---|---|---|---|
a-Si (%) | CdTe (%) | c-Si (%) | High-eff. c-Si (%) | CIGS (%) | ||
1 | 38 | −2.0 | 1 | 1.9 | 2.4 | 2.6 |
2 | 65 | −1.3 | 0.1 | 1 | 1.4 | 1.6 |
3 | 122 | 0.1 | 0.6 | 0.7 | 0.8 | 0.9 |
4 | 141 | 3.5 | 1.9 | 1.2 | 0.9 | 0.4 |
5 | 166 | 4.2 | 2.3 | 1.5 | 0.9 | 0.3 |
6 | 166 | 5.1 | 2.8 | 1.4 | 0.8 | 0 |
7 | 184 | 5.3 | 3.4 | 1.5 | 0.8 | 0 |
8 | 168 | 5.3 | 3.5 | 1.6 | 0.9 | 0.1 |
9 | 136 | 4.3 | 3.1 | 1.5 | 1 | 0.4 |
10 | 91 | 2.8 | 3 | 1.9 | 1.7 | 1.3 |
11 | 43 | 0.8 | 2.3 | 2.1 | 2.2 | 2.1 |
12 | 35 | −2.2 | 1.8 | 2.4 | 3 | 3.3 |
Calculation of annual spectral impact based on the monthly sums of irradiance of a reference year and the determined average monthly spectral impact assessed in Germany [32].
The detail on performance variation by the influence of temperature of the different types of PV modules has been conducted by Gutkowski et al. under the low insolation climate of Poland [95]. They observed a significant difference in performance by different PV modules at temperatures 15-48 °C as shown in Figure 14(a). It is clear from Figure 14(a) that under real conditions of the high-temperature region, the power generated by CIGS thin-film technologies is higher compare to the pc-Si PV modules. Ozden et al. [98] also experimentally investigate the a-Si and CdTe thin-film PV module performance under the Turkey climate zone along with sc-Si and mc-Si. They found a significant difference in performance in that module for the sunny and cloudy days as shown in Figure 14(b). The output performance of sc-Si and mc-Si is found to be the same, but the output difference between CdTe and sc-Si modules is 60% for a sunny day and which reduces to 35% for a cloudy day indicating the impact of irradiance as well as temperature on these technologies. Moreover, the performance ratio (PR) of sc-Si is in the range of 70%–90%, a-Si is about 70% and CdTe is only 42%–72%. Alternatively, Kesler et al. [99] also conducted a performance analysis between the c-Si and thin film for another location, Antalya, Turkey, and reported that performance of the both technology is very close to each other. Even they specified the reason is the high ambient temperature of that area, however, the rated efficiency of that technologies may play an important role in this case, which means that if the rated efficiency is almost the same, their performance will be close to each other.
(a) Normalized DC power generated by the PV systems of each studied technology [
Sharma et al. [100] studied three different PV technologies, such as a-Si, pc-Si, and HIT under the tropical climate of India. They found that the best-suited PV technology for this climate is HIT and a-Si. The overall performance ratio for a-Si is 90% and for pc-Si is 83% in this region as shown in Figure 15. Interestingly, the energy yield of a-Si is 14% greater during summer, but 6% lower in winter. The effect of seasonal which in turn the effect of irradiance and temperature on the performance of a-Si may be related to its thermal annealing process [101]. The HIT modules have consistently performed better (≥ 4–12%) than p-Si over the year. Aste et al. [102] investigate PV module performance under temperate climatic conditions (Italy) where the more distinct seasonal change and/or wide temperature variation have occurred. They found that a-Si is much more sensitive to the seasonal solar spectrum rather than c-Si and HIT technology. The highest 93% of performance ratio has been reported for c-Si in this study. However, the c-Si technology has also shown seasonal variation as an exceptional case [75] and the performance ratio found 20% lower in summer than in winter as a role of temperature variation. In summer, the a-Si/mc-Si stack cell showed higher performance than the other technologies tested in this study, which may be due to its low-temperature coefficient and thermal annealing.
Comparison of measured monthly and yearly performance ratio of each technology array tested in Indian climate condition [
The assessment carried in the Netherlands [103] showed that the CIGS modules are strongly affected by irradiance and temperature variations with a decrease in annual energy yield of 1.2%. Moreover, CdTe modules also exhibited a decrease in energy yield of about 1.0%. This experimental study also showed a significant influence of spectral variation on the efficiency of a-Si modules. Zdyb and Gutkowski studied four different types of PV modules, such as pc-Si, a-Si, CIGS, and CdTe at high latitude under East Poland climate conditions [104]. In their study, a-Si and CIGS shows the gain in performance ratio (about to 73.4% for a-Si and 90.7% for CIGS) during summer sunny and warm environment. The increase of performance ratio of a-Si PV modules has also been reported by Makrides et al. [101] studied under the Cyprus environment. On the other hand, the performance ratio of pc-Si PV modules exhibited over 80% except for December and always remain the highest among the investigated PV modules over the year as shown in Figure 16.
Performance ratio for each studied PV technology investigated in East Poland (data collected in 2018) [
The effect of spectral irradiance distribution on the performance of a-Si/mc-Si stacked photovoltaic modules has been analyzed by Minemoto et al. [105] installed at Kusatsu-city (Japan). Their study revealed that these stacked PV modules are extremely spectrally sensitive compared to pc-Si PV modules installed on the same site. Akhmad et al. [106] have been compared the performance of poly-silicon (pc-Si) and amorphous silicon (a-Si) at Kobe, Japan, and found a-Si modules are better for this region. K. Nishioka et al. [107] compared sc-Si, pc-Si module, and heterojunction silicon at Nara Institute of Science and Technology (NAIST) under Japanese climate. They reported that the HIT technology is better suited for this region due to its low-temperature dependency. Poissant [108] has evaluated four different novels PV module technologies, (i) H-Si, (ii) IBC, (iii) a-Si/uc-Si, and (iv) c-Si under the climate of Canada. His study confirmed that the heterojunction silicon and a-Si/uc-Si technologies are less affected by temperature than the other two crystalline silicon technologies. Canete et al. [109] also performed a comparative study of four different photovoltaic module technologies, (i) amorphous silicon (a-Si), (ii) tandem structure of amorphous silicon- microcrystalline silicon (a-Si/mc-Si), (iii) polycrystalline silicon module (pc-Si) and (iv) cadmium telluride (CdTe). Their results show that the performance of thin-film modules is better than that of pc-Si modules for the location of Southern Spain. The performances of c-Si and a-Si PV modules under South Africa climate conditions have been evaluated by Maluta and Sankaran [110]. They found that both technologies give a similar and suitable performance for the climate of this region. Three different PV technologies (monocrystalline, polycrystalline, and amorphous silicon) have been evaluated under the desert climate by M. Shaltout et al. [111]. They reported that the polycrystalline silicon cells are more suitable in such a climate. All these above-mentioned studies indicate the difficulty when it comes to choosing the appropriate PV technology for a given site. Thus, the prediction of PV energy potentials before installation helps us to understand the economic advantages associated with it and for policy regulation for electric utilities.
Table 2 shows the summary of a few reported works for finding out the best PV technology by location and its climate. It should be noticed that the results reported by the various researcher as mentioned above are very difficult to compare because the work has been conducted focusing on different locations and various time scales (instantaneous, monthly, annual), different energy effects, and even the works are different by used metrics and calculation. However, it is well agreed that the impact of spectral irradiance variations on PV device performance mostly depends on its spectral response, which in turn depends on its absorber material properties and quality. Moreover, the influence of spectral irradiance on PV performance is dependent on installation sites, for instance, the spectral distribution, climate, environment, latitude, longitude, albedo, etc. of the location. Besides, the spectral distribution of specific sites again depends on the cloudiness, water-vapor and aerosol content in the sky of that sites. The analysis considering all the above factors certainly will be too difficult, thus, the researcher considers only some of the factors for simplifying their work.
Author(s) | Location | Environmental Parameters | Tested Technologies | Best Perform Technology |
---|---|---|---|---|
Dirnberger et al., 2015 [32] | Breisgau, Germany | Maritime climate, 5-25 °C, 1,117 kW/m2/year (approx.) | a- Si, sc-Si, CIGS and CdTe | a-Si |
Francis et al., 2019 [75] |
|
|
| a-Si/μc-Si |
Edalati et al., 2015 [81] | Kerman, Iran | Dry climate 68.64–198.72 kW/m2, 20 °C | sc-Si, and pc-Si | pc-Si |
Bora et al., 2018 [83] | Different parts of India | 0.82–0.87 kW/m2/day not mentioned | a-Si, HIT, and pc- Si | All (cold and sunny zone) |
Cotfas and Cotfas, 2019 [88] | Brasov, Romania | Temperate-continental climate, 2.1–1.82 Wh/m2/day, −4.0 – 24 °C | sc-Si and a-Si | sc-Si |
Louwen et al., 2016 [89] | Utrecht, Netherlands | Oceanic climate, 20.5–29.5 °C, 950–1050 W/m2 | SHJ, a- Si, sc-Si, pc-Si, CIGS, CIS and CdTe | sc-Si and SHJ |
Gulkowski et al., 2019 [95] | Lublin, Poland | Temperate climate, 950–1250 (kWh/m2)/year, 15–48 °C | CdTe, CIGS, and pc-Si | CIGS |
Aste et al., 2014 [94] | Milan, Italy | Temperate climatic, 1270 kW/m2/year, −5-32 °C | c-Si, a-Si/uc-Si, HIT | HIT |
Zdyb and Gulkowski, 2020 [103] | Lublin, Poland | Temperate climate, 950–1250 (kWh/m2)/year, 15–48 °C | pc-Si, a-Si, CIGS, and CdTe | pc-Si and CIGS |
Makrides et al., 2018 [104] | Cyprus | Mediterranean climate, 1988–2054 kWh/m2, 10-40 °C | sc-Si, pc-Si, a-Si, CIGS and CdTe | a-Si |
Minemoto et al., 2007 [105] | Kusatsu-city, Japan | Subtropical climate, 200 kW/m2, 9-33 °C | pc-Si, and a-Si | pc-Si |
Poissant, 2009 [108] | Montreal, Canada | Continental climate, 950–1050 W/m2, max. 20 to 22 °C | SHJ, IBC, a-Si/uc-Si, and c-Si | a-Si/uc-Si |
Cañete et al., 2014 [109] | Southern Spain | Dry Mediterranean climate, 3.7–7.4 kWh/m2/day, 15–30 °C | a-Si, a-Si/μc-Si CdTe, and pc-Si | a-Si and CdTe |
Summary of few reported works for finding out the best PV technology by location and climate.
The weather and/or solar irradiance of the earth is significantly different from one location to another. Again, solar irradiance varies for a specific location by season and/or common weather phenomenon, such as dust, rain, wind, cloud, fog, and snow, etc. Thus, every year solar irradiance also not the same in amount and as an impact of the above factors, the energy yield of different PV technology is affected differently and prediction is very complicated. However, numerous studies could help us to predict which PV technology is better suited for a certain location. It should be noticed that all the incident solar radiations absorbed by PV cells are not able to convert into electricity, some of them are increase temperature, thus the performance varied. As discussed in this book chapter, most of the study showed that summer months when irradiation becomes high that leads to an increase of module temperature, a-Si technology show better performance than c-Si PV modules. It may be due to the metastable defects generated during the dangling bond compensation are decreased upon module temperature increase and as a result, the module performs better in elevated temperature. Also, CIGS PV modules show similar behavior to the a-Si PV modules. The performance gain observed in CIGS technology in summer or at elevated temperatures may be related to the larger bandgap and lower temperature coefficient. Particularly, the optical bandgap of CIGS thin film is higher than a-Si and the higher bandgap has a lower temperature coefficient. Also, CIGS modules can convert the blue light part of the solar spectrum due to a larger bandgap that may assist to perform better in hot summer. Alternatively, c-Si have a narrow bandgap, as the defect density increases upon high irradiance and high temperature in hot summer, the dark saturation current and/or leakage current is increased. Consequently, the performance decrease in summer. However, it has been seen that c-Si perform very in high irradiance with cold weather. It should be noticed that the module with a higher leakage current is highly affected by low irradiance. Since a-Si solar cells inherently have high defect density and/or high leakage current than c-Si solar cells, thus the power gain by c-Si at very low irradiance is significantly higher than a-Si as discussed in the above section. Overall, CdTe modules are performed much poorer than others probably due to the consequence of early degradation of the module as reported in the previous section. All these above-mentioned studies specify the difficulty of choosing an appropriate PV technology for a given site. Thus, the prediction of PV energy potentials before installation is very important concerning the economic advantages and for policy regulation for electric utilities.
The authors wish to thank the Ministry of Higher Education of Malaysia (MoHE) for providing the Long Term Research Grant Scheme (LRGS) with the code of LRGS/1/2019/UKM-UNITEN/6/2 to support this research. The authors also acknowledge the publication support from the iRMC of Universiti Tenaga Nasional (@UNITEN), Malaysia. The authors would also like to acknowledge the Faculty of Engineering, University of Malaya (@UM) for other supports.
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Extreme weather conditions and changes in humidity rates significantly affect the concrete compressive strength development. Concrete as one of the substantial material used in residential buildings and infrastructures is subjected to a massive strength change under extreme weather conditions. For understanding, the different concrete’s behavioral aspects, various commercial cement types under different temperatures, and humidity rates are investigated in this chapter. The experiments are aimed to investigate the concrete strength development over time when the material is cast at lower to mild temperatures and different humidity index rates. Results show that reducing the curing temperature more than 15° could result in 20% reduction in total compressive strength, while decreasing humidity rates by 50% leads to less than 10% drop in ultimate strength. To understand the strength developing process, maturity tests are conducted. It is shown that concrete is not able to reach to the expected ultimate strength if the temperature is significantly low regardless of curing time. The effect of temperature change during the curing process is more tangible on strength development compared to cement type and humidity rate values.",book:{id:"8757",slug:"compressive-strength-of-concrete",title:"Compressive Strength of Concrete",fullTitle:"Compressive Strength of Concrete"},signatures:"Alireza Farzampour",authors:null},{id:"51720",doi:"10.5772/64574",title:"Microstructure of Concrete",slug:"microstructure-of-concrete",totalDownloads:4840,totalCrossrefCites:15,totalDimensionsCites:19,abstract:"Concrete is a composite material that consists of a binding medium and aggregate particles and can be formed in several types. It may be considered to consist of three phases: a cement paste, the aggregate, and the interfacial transition zone (ITZ) between them. In addition to ordinary Portland cement, the essential components of the base of concrete are aggregates and water. For practical requirements, additives and admixtures can be added to these raw materials to improve some desirable characteristics. The following requirements should be considered in producing high performance concrete (HPC): (i) low water/cement (w/c) ratio; (ii) fine aggregate; (iii) large quantity of mineral additives, silica fume, and fly ash; (iv) high dosage of superplasticizer; and (v) high-pressure steam curing. The microstructure of high performance concrete (HPC) is more homogenous than that of normal concrete (NC) due to the physical and chemical contribution of the additives (silica fume and fly ash) as well as it is less porous due to reduced w/c ratio with the addition of a superplasticizer. Inclusion of additives (individually or in combination) helped in improving the strength and durability of concrete mixes due to the additional reduction in porosity of cement paste and an improved interface between it and the aggregate.",book:{id:"5214",slug:"high-performance-concrete-technology-and-applications",title:"High Performance Concrete Technology and Applications",fullTitle:"High Performance Concrete Technology and Applications"},signatures:"Ameer A. Hilal",authors:[{id:"180518",title:"Dr.",name:"Ameer",middleName:null,surname:"Hilal",slug:"ameer-hilal",fullName:"Ameer Hilal"}]},{id:"51861",doi:"10.5772/64779",title:"Concretes with Photocatalytic Activity",slug:"concretes-with-photocatalytic-activity",totalDownloads:2832,totalCrossrefCites:8,totalDimensionsCites:15,abstract:"This chapter is a short review about the modified concretes with photocatalytic activity. In the beginning, the photocatalysis process is explained; the authors are focused on the mechanism of organic contamination and nitrogen oxide decomposition. Next the three main methods for concretes modification are presented: the first group is when the concrete is covered by thin layer of TiO2 materials, e.g., paints or TiO2 suspensions. The second group is the concretes with thick layer of photoactive concrete on the top. The third group constitutes concretes modified in mass with TiO2. The two main methods for photocatalytic activity of the modified concrete determination were shown: an air purification by a nitrogen oxide decomposition and the self-cleaning properties by dyes decomposition. Also in this chapter the mechanical properties of the modified concrete are presented. In the end, the examples of the buildings made of photocatalytic concretes are shown.",book:{id:"5214",slug:"high-performance-concrete-technology-and-applications",title:"High Performance Concrete Technology and Applications",fullTitle:"High Performance Concrete Technology and Applications"},signatures:"Magdalena Janus and Kamila Zając",authors:[{id:"180824",title:"Associate Prof.",name:"Magdalena",middleName:null,surname:"Janus",slug:"magdalena-janus",fullName:"Magdalena Janus"}]},{id:"51409",doi:"10.5772/64386",title:"Application of Polypropylene Fibrillated Fibres for Reinforcement of Concrete and Cement Mortars",slug:"application-of-polypropylene-fibrillated-fibres-for-reinforcement-of-concrete-and-cement-mortars",totalDownloads:2423,totalCrossrefCites:2,totalDimensionsCites:6,abstract:"Polypropylene fibres have been applied for reinforcement of cement mortars and concrete for many years. The fibres restrict crack propagation and positively affect several concrete parameters. To improve the adhesion of polypropylene to cement matrix, geometrically deformed or modified fibres are commonly used. Good results are obtained by application of fibrillated fibres with the net-like structure obtained from the polypropylene types. The fibrillated polypropylene fibres were produced. The fibres were chopped to specified lengths and used for the reinforcement of concrete and cement mortars. The parameters of fresh concrete and mechanical parameters of reinforced concrete and mortar were determined. It was stated that the fibres do not affect the compressive strength of the reinforced concrete and mortar. The beneficial effect of fibres on the compressive strength of concrete is revealed after freezing and thawing cycles. The fibres influence the bending strength of the mortars. For mortars reinforced with fibrillated fibres a significant increase in the bending strength is observed. The increase in the bending strength results from enhanced interfacial adhesion and mechanical anchoring, which results from opening of the network structure and splitting of fibrillated fibres.",book:{id:"5214",slug:"high-performance-concrete-technology-and-applications",title:"High Performance Concrete Technology and Applications",fullTitle:"High Performance Concrete Technology and Applications"},signatures:"Jan Broda",authors:[{id:"104226",title:"Prof.",name:"Jan",middleName:null,surname:"Broda",slug:"jan-broda",fullName:"Jan Broda"}]},{id:"68188",doi:"10.5772/intechopen.88057",title:"Compressive Strength of Lightweight Concrete",slug:"compressive-strength-of-lightweight-concrete",totalDownloads:1713,totalCrossrefCites:3,totalDimensionsCites:6,abstract:"This chapter has been prepared with the hope that its readers will become interested in lightweight concrete (LWC). Therefore, after a brief background of lightweight concrete, different types of LWC will be introduced and then LWC made of lightweight aggregates (LWA) will be specifically discussed. Compressive strength and density of LWC are the main points of interest in this chapter. In addition to conventional compression test, a nondestructive test (NDT) method will be used to assess the compressive strength of a variety of lightweight concrete mixes. A case study has been designed and conducted including an experimental program on the LWC made of expanded glass aggregate. The experimental program includes about 150 specimens, incorporating different unit weight for the entire specimens. In the end, it can be observed that the properties of LWC depend on the properties of the used LWA, and therefore for each specific type of lightweight aggregate, a brand new equation will be required for prediction of concrete compressive strength. The author hopes that the present chapter and the discussed case study on LWC would attract the attention of researchers to the importance of LWC in the future of construction industry.",book:{id:"8757",slug:"compressive-strength-of-concrete",title:"Compressive Strength of Concrete",fullTitle:"Compressive Strength of Concrete"},signatures:"Saman Hedjazi",authors:null}],mostDownloadedChaptersLast30Days:[{id:"51720",title:"Microstructure of Concrete",slug:"microstructure-of-concrete",totalDownloads:4841,totalCrossrefCites:15,totalDimensionsCites:19,abstract:"Concrete is a composite material that consists of a binding medium and aggregate particles and can be formed in several types. It may be considered to consist of three phases: a cement paste, the aggregate, and the interfacial transition zone (ITZ) between them. In addition to ordinary Portland cement, the essential components of the base of concrete are aggregates and water. For practical requirements, additives and admixtures can be added to these raw materials to improve some desirable characteristics. The following requirements should be considered in producing high performance concrete (HPC): (i) low water/cement (w/c) ratio; (ii) fine aggregate; (iii) large quantity of mineral additives, silica fume, and fly ash; (iv) high dosage of superplasticizer; and (v) high-pressure steam curing. The microstructure of high performance concrete (HPC) is more homogenous than that of normal concrete (NC) due to the physical and chemical contribution of the additives (silica fume and fly ash) as well as it is less porous due to reduced w/c ratio with the addition of a superplasticizer. Inclusion of additives (individually or in combination) helped in improving the strength and durability of concrete mixes due to the additional reduction in porosity of cement paste and an improved interface between it and the aggregate.",book:{id:"5214",slug:"high-performance-concrete-technology-and-applications",title:"High Performance Concrete Technology and Applications",fullTitle:"High Performance Concrete Technology and Applications"},signatures:"Ameer A. Hilal",authors:[{id:"180518",title:"Dr.",name:"Ameer",middleName:null,surname:"Hilal",slug:"ameer-hilal",fullName:"Ameer Hilal"}]},{id:"70930",title:"The Influence of Interfacial Transition Zone on Strength of Alkali-Activated Concrete",slug:"the-influence-of-interfacial-transition-zone-on-strength-of-alkali-activated-concrete",totalDownloads:900,totalCrossrefCites:2,totalDimensionsCites:2,abstract:"A process of structure formation taking place in the interfacial transition zone (ITZ) “cement stone-aggregate” was studied on a variety of concretes made with artificial and real aggregates. The study of these processes in the case of artificial aggregate prepared from a mixture of clay loam and alkali-activated slag cement showed that not only active SiO2 and Na2O but also other substances of both cement and aggregate are involved in the formation of the ITZ. This results in the formation of alkaline and alkaline-alkali-earth aluminosilicate hydrates which strengthen the ITZ and improve strength and durability of the concrete. Thus, the alkali-silica reaction (ASR) transforms from a destructive one (negative effect) into a constructive one (positive effect). The study on the ITZ in the alkali-activated cement concretes made with real alkali-susceptible aggregates selected from crushed basalt rock, glassy waste product from basalt fiber production, crushed perlite rock, and expanded perlite suggested to make a conclusion on the possibility to prevent the destructive processes in the ITZ through the addition of the metakaolin additive into the cement composition in quantities of 5–10% by mass. These conclusions were supported by the long-term testing of strength of these concretes, by measuring the deformations “shrinkage-expansion” as well as the results of study on hardness of the ITZ.",book:{id:"8757",slug:"compressive-strength-of-concrete",title:"Compressive Strength of Concrete",fullTitle:"Compressive Strength of Concrete"},signatures:"Pavel Krivenko, Oleh Petropavlovskyi, Oleksandr Kovalchuk and Oleksandr Gelevera",authors:null},{id:"68188",title:"Compressive Strength of Lightweight Concrete",slug:"compressive-strength-of-lightweight-concrete",totalDownloads:1713,totalCrossrefCites:3,totalDimensionsCites:6,abstract:"This chapter has been prepared with the hope that its readers will become interested in lightweight concrete (LWC). Therefore, after a brief background of lightweight concrete, different types of LWC will be introduced and then LWC made of lightweight aggregates (LWA) will be specifically discussed. Compressive strength and density of LWC are the main points of interest in this chapter. In addition to conventional compression test, a nondestructive test (NDT) method will be used to assess the compressive strength of a variety of lightweight concrete mixes. A case study has been designed and conducted including an experimental program on the LWC made of expanded glass aggregate. The experimental program includes about 150 specimens, incorporating different unit weight for the entire specimens. In the end, it can be observed that the properties of LWC depend on the properties of the used LWA, and therefore for each specific type of lightweight aggregate, a brand new equation will be required for prediction of concrete compressive strength. The author hopes that the present chapter and the discussed case study on LWC would attract the attention of researchers to the importance of LWC in the future of construction industry.",book:{id:"8757",slug:"compressive-strength-of-concrete",title:"Compressive Strength of Concrete",fullTitle:"Compressive Strength of Concrete"},signatures:"Saman Hedjazi",authors:null},{id:"51409",title:"Application of Polypropylene Fibrillated Fibres for Reinforcement of Concrete and Cement Mortars",slug:"application-of-polypropylene-fibrillated-fibres-for-reinforcement-of-concrete-and-cement-mortars",totalDownloads:2423,totalCrossrefCites:2,totalDimensionsCites:6,abstract:"Polypropylene fibres have been applied for reinforcement of cement mortars and concrete for many years. The fibres restrict crack propagation and positively affect several concrete parameters. To improve the adhesion of polypropylene to cement matrix, geometrically deformed or modified fibres are commonly used. Good results are obtained by application of fibrillated fibres with the net-like structure obtained from the polypropylene types. The fibrillated polypropylene fibres were produced. The fibres were chopped to specified lengths and used for the reinforcement of concrete and cement mortars. The parameters of fresh concrete and mechanical parameters of reinforced concrete and mortar were determined. It was stated that the fibres do not affect the compressive strength of the reinforced concrete and mortar. The beneficial effect of fibres on the compressive strength of concrete is revealed after freezing and thawing cycles. The fibres influence the bending strength of the mortars. For mortars reinforced with fibrillated fibres a significant increase in the bending strength is observed. The increase in the bending strength results from enhanced interfacial adhesion and mechanical anchoring, which results from opening of the network structure and splitting of fibrillated fibres.",book:{id:"5214",slug:"high-performance-concrete-technology-and-applications",title:"High Performance Concrete Technology and Applications",fullTitle:"High Performance Concrete Technology and Applications"},signatures:"Jan Broda",authors:[{id:"104226",title:"Prof.",name:"Jan",middleName:null,surname:"Broda",slug:"jan-broda",fullName:"Jan Broda"}]},{id:"51780",title:"High-Performance Concrete and Fiber-Reinforced High- Performance Concrete under Fatigue Efforts",slug:"high-performance-concrete-and-fiber-reinforced-high-performance-concrete-under-fatigue-efforts",totalDownloads:2321,totalCrossrefCites:2,totalDimensionsCites:4,abstract:"Fatigue is the process of mechanical degradation of a material, which leads to its collapse. Repeated load applications with a maximum value lower than the one that provokes the static failure of the material, causes internal damage in the material that, progressively, reduces its mechanical capacity until it finally collapses. The increasingly widespread use of high-strength concretes permits the construction of more lightweight structures. This implies that the variable loads (which are the causes of fatigue) represent an ever larger percentage of the total load. In consequence, fatigue is an increasingly important factor in concrete structures. In some cases, it even begins to be the dimensioning load of the structure. In addition, the presence of fibers within the concrete modifies the fatigue response of the concrete. In this chapter, the classic theory of fatigue is presented in detail and the most recent developments in the study of concrete fatigue are discussed.",book:{id:"5214",slug:"high-performance-concrete-technology-and-applications",title:"High Performance Concrete Technology and Applications",fullTitle:"High Performance Concrete Technology and Applications"},signatures:"Miguel A. Vicente, Jesús Mínguez, José A. Martínez and Dorys C.\nGonzález",authors:[{id:"181643",title:"Prof.",name:"Miguel",middleName:null,surname:"Vicente",slug:"miguel-vicente",fullName:"Miguel Vicente"},{id:"182032",title:"Prof.",name:"Jesus",middleName:null,surname:"Minguez",slug:"jesus-minguez",fullName:"Jesus Minguez"},{id:"182033",title:"Prof.",name:"Jose Antonio",middleName:null,surname:"Martinez",slug:"jose-antonio-martinez",fullName:"Jose Antonio Martinez"},{id:"182034",title:"Prof.",name:"Dorys",middleName:null,surname:"Gonzalez",slug:"dorys-gonzalez",fullName:"Dorys Gonzalez"}]}],onlineFirstChaptersFilter:{topicId:"1348",limit:6,offset:0},onlineFirstChaptersCollection:[],onlineFirstChaptersTotal:0},preDownload:{success:null,errors:{}},subscriptionForm:{success:null,errors:{}},aboutIntechopen:{},privacyPolicy:{},peerReviewing:{},howOpenAccessPublishingWithIntechopenWorks:{},sponsorshipBooks:{sponsorshipBooks:[],offset:8,limit:8,total:0},allSeries:{pteSeriesList:[{id:"14",title:"Artificial Intelligence",numberOfPublishedBooks:9,numberOfPublishedChapters:89,numberOfOpenTopics:6,numberOfUpcomingTopics:0,issn:"2633-1403",doi:"10.5772/intechopen.79920",isOpenForSubmission:!0},{id:"7",title:"Biomedical Engineering",numberOfPublishedBooks:12,numberOfPublishedChapters:104,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2631-5343",doi:"10.5772/intechopen.71985",isOpenForSubmission:!0}],lsSeriesList:[{id:"11",title:"Biochemistry",numberOfPublishedBooks:32,numberOfPublishedChapters:318,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2632-0983",doi:"10.5772/intechopen.72877",isOpenForSubmission:!0},{id:"25",title:"Environmental Sciences",numberOfPublishedBooks:1,numberOfPublishedChapters:12,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2754-6713",doi:"10.5772/intechopen.100362",isOpenForSubmission:!0},{id:"10",title:"Physiology",numberOfPublishedBooks:11,numberOfPublishedChapters:141,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2631-8261",doi:"10.5772/intechopen.72796",isOpenForSubmission:!0}],hsSeriesList:[{id:"3",title:"Dentistry",numberOfPublishedBooks:8,numberOfPublishedChapters:129,numberOfOpenTopics:2,numberOfUpcomingTopics:0,issn:"2631-6218",doi:"10.5772/intechopen.71199",isOpenForSubmission:!0},{id:"6",title:"Infectious Diseases",numberOfPublishedBooks:13,numberOfPublishedChapters:113,numberOfOpenTopics:3,numberOfUpcomingTopics:1,issn:"2631-6188",doi:"10.5772/intechopen.71852",isOpenForSubmission:!0},{id:"13",title:"Veterinary Medicine and Science",numberOfPublishedBooks:11,numberOfPublishedChapters:106,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2632-0517",doi:"10.5772/intechopen.73681",isOpenForSubmission:!0}],sshSeriesList:[{id:"22",title:"Business, Management and Economics",numberOfPublishedBooks:1,numberOfPublishedChapters:19,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2753-894X",doi:"10.5772/intechopen.100359",isOpenForSubmission:!0},{id:"23",title:"Education and Human Development",numberOfPublishedBooks:0,numberOfPublishedChapters:5,numberOfOpenTopics:1,numberOfUpcomingTopics:1,issn:null,doi:"10.5772/intechopen.100360",isOpenForSubmission:!0},{id:"24",title:"Sustainable Development",numberOfPublishedBooks:0,numberOfPublishedChapters:15,numberOfOpenTopics:5,numberOfUpcomingTopics:0,issn:null,doi:"10.5772/intechopen.100361",isOpenForSubmission:!0}],testimonialsList:[{id:"6",text:"It is great to work with the IntechOpen to produce a worthwhile collection of research that also becomes a great educational resource and guide for future research endeavors.",author:{id:"259298",name:"Edward",surname:"Narayan",institutionString:null,profilePictureURL:"https://mts.intechopen.com/storage/users/259298/images/system/259298.jpeg",slug:"edward-narayan",institution:{id:"3",name:"University of Queensland",country:{id:null,name:"Australia"}}}},{id:"13",text:"The collaboration with and support of the technical staff of IntechOpen is fantastic. The whole process of submitting an article and editing of the submitted article goes extremely smooth and fast, the number of reads and downloads of chapters is high, and the contributions are also frequently cited.",author:{id:"55578",name:"Antonio",surname:"Jurado-Navas",institutionString:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRisIQAS/Profile_Picture_1626166543950",slug:"antonio-jurado-navas",institution:{id:"720",name:"University of Malaga",country:{id:null,name:"Spain"}}}}]},series:{item:{id:"14",title:"Artificial Intelligence",doi:"10.5772/intechopen.79920",issn:"2633-1403",scope:"Artificial Intelligence (AI) is a rapidly developing multidisciplinary research area that aims to solve increasingly complex problems. In today's highly integrated world, AI promises to become a robust and powerful means for obtaining solutions to previously unsolvable problems. This Series is intended for researchers and students alike interested in this fascinating field and its many applications.",coverUrl:"https://cdn.intechopen.com/series/covers/14.jpg",latestPublicationDate:"June 11th, 2022",hasOnlineFirst:!0,numberOfPublishedBooks:9,editor:{id:"218714",title:"Prof.",name:"Andries",middleName:null,surname:"Engelbrecht",slug:"andries-engelbrecht",fullName:"Andries Engelbrecht",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRNR8QAO/Profile_Picture_1622640468300",biography:"Andries Engelbrecht received the Masters and PhD degrees in Computer Science from the University of Stellenbosch, South Africa, in 1994 and 1999 respectively. He is currently appointed as the Voigt Chair in Data Science in the Department of Industrial Engineering, with a joint appointment as Professor in the Computer Science Division, Stellenbosch University. Prior to his appointment at Stellenbosch University, he has been at the University of Pretoria, Department of Computer Science (1998-2018), where he was appointed as South Africa Research Chair in Artifical Intelligence (2007-2018), the head of the Department of Computer Science (2008-2017), and Director of the Institute for Big Data and Data Science (2017-2018). In addition to a number of research articles, he has written two books, Computational Intelligence: An Introduction and Fundamentals of Computational Swarm Intelligence.",institutionString:null,institution:{name:"Stellenbosch University",institutionURL:null,country:{name:"South Africa"}}},editorTwo:null,editorThree:null},subseries:{paginationCount:6,paginationItems:[{id:"22",title:"Applied Intelligence",coverUrl:"https://cdn.intechopen.com/series_topics/covers/22.jpg",isOpenForSubmission:!0,editor:{id:"27170",title:"Prof.",name:"Carlos",middleName:"M.",surname:"Travieso-Gonzalez",slug:"carlos-travieso-gonzalez",fullName:"Carlos Travieso-Gonzalez",profilePictureURL:"https://mts.intechopen.com/storage/users/27170/images/system/27170.jpeg",biography:"Carlos M. Travieso-González received his MSc degree in Telecommunication Engineering at Polytechnic University of Catalonia (UPC), Spain in 1997, and his Ph.D. degree in 2002 at the University of Las Palmas de Gran Canaria (ULPGC-Spain). He is a full professor of signal processing and pattern recognition and is head of the Signals and Communications Department at ULPGC, teaching from 2001 on subjects on signal processing and learning theory. His research lines are biometrics, biomedical signals and images, data mining, classification system, signal and image processing, machine learning, and environmental intelligence. He has researched in 52 international and Spanish research projects, some of them as head researcher. He is co-author of 4 books, co-editor of 27 proceedings books, guest editor for 8 JCR-ISI international journals, and up to 24 book chapters. He has over 450 papers published in international journals and conferences (81 of them indexed on JCR – ISI - Web of Science). He has published seven patents in the Spanish Patent and Trademark Office. He has been a supervisor on 8 Ph.D. theses (11 more are under supervision), and 130 master theses. He is the founder of The IEEE IWOBI conference series and the president of its Steering Committee, as well as the founder of both the InnoEducaTIC and APPIS conference series. He is an evaluator of project proposals for the European Union (H2020), Medical Research Council (MRC, UK), Spanish Government (ANECA, Spain), Research National Agency (ANR, France), DAAD (Germany), Argentinian Government, and the Colombian Institutions. He has been a reviewer in different indexed international journals (<70) and conferences (<250) since 2001. He has been a member of the IASTED Technical Committee on Image Processing from 2007 and a member of the IASTED Technical Committee on Artificial Intelligence and Expert Systems from 2011. \n\nHe has held the general chair position for the following: ACM-APPIS (2020, 2021), IEEE-IWOBI (2019, 2020 and 2020), A PPIS (2018, 2019), IEEE-IWOBI (2014, 2015, 2017, 2018), InnoEducaTIC (2014, 2017), IEEE-INES (2013), NoLISP (2011), JRBP (2012), and IEEE-ICCST (2005)\n\nHe is an associate editor of the Computational Intelligence and Neuroscience Journal (Hindawi – Q2 JCR-ISI). He was vice dean from 2004 to 2010 in the Higher Technical School of Telecommunication Engineers at ULPGC and the vice dean of Graduate and Postgraduate Studies from March 2013 to November 2017. He won the “Catedra Telefonica” Awards in Modality of Knowledge Transfer, 2017, 2018, and 2019 editions, and awards in Modality of COVID Research in 2020.\n\nPublic References:\nResearcher ID http://www.researcherid.com/rid/N-5967-2014\nORCID https://orcid.org/0000-0002-4621-2768 \nScopus Author ID https://www.scopus.com/authid/detail.uri?authorId=6602376272\nScholar Google https://scholar.google.es/citations?user=G1ks9nIAAAAJ&hl=en \nResearchGate https://www.researchgate.net/profile/Carlos_Travieso",institutionString:null,institution:{name:"University of Las Palmas de Gran Canaria",institutionURL:null,country:{name:"Spain"}}},editorTwo:null,editorThree:null},{id:"23",title:"Computational Neuroscience",coverUrl:"https://cdn.intechopen.com/series_topics/covers/23.jpg",isOpenForSubmission:!0,editor:{id:"14004",title:"Dr.",name:"Magnus",middleName:null,surname:"Johnsson",slug:"magnus-johnsson",fullName:"Magnus Johnsson",profilePictureURL:"https://mts.intechopen.com/storage/users/14004/images/system/14004.png",biography:"Dr Magnus Johnsson is a cross-disciplinary scientist, lecturer, scientific editor and AI/machine learning consultant from Sweden. \n\nHe is currently at Malmö University in Sweden, but also held positions at Lund University in Sweden and at Moscow Engineering Physics Institute. \nHe holds editorial positions at several international scientific journals and has served as a scientific editor for books and special journal issues. \nHis research interests are wide and include, but are not limited to, autonomous systems, computer modeling, artificial neural networks, artificial intelligence, cognitive neuroscience, cognitive robotics, cognitive architectures, cognitive aids and the philosophy of mind. \n\nDr. Johnsson has experience from working in the industry and he has a keen interest in the application of neural networks and artificial intelligence to fields like industry, finance, and medicine. \n\nWeb page: www.magnusjohnsson.se",institutionString:null,institution:{name:"Malmö University",institutionURL:null,country:{name:"Sweden"}}},editorTwo:null,editorThree:null},{id:"24",title:"Computer Vision",coverUrl:"https://cdn.intechopen.com/series_topics/covers/24.jpg",isOpenForSubmission:!0,editor:{id:"294154",title:"Prof.",name:"George",middleName:null,surname:"Papakostas",slug:"george-papakostas",fullName:"George Papakostas",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002hYaGbQAK/Profile_Picture_1624519712088",biography:"George A. Papakostas has received a diploma in Electrical and Computer Engineering in 1999 and the M.Sc. and Ph.D. degrees in Electrical and Computer Engineering in 2002 and 2007, respectively, from the Democritus University of Thrace (DUTH), Greece. Dr. Papakostas serves as a Tenured Full Professor at the Department of Computer Science, International Hellenic University, Greece. Dr. Papakostas has 10 years of experience in large-scale systems design as a senior software engineer and technical manager, and 20 years of research experience in the field of Artificial Intelligence. Currently, he is the Head of the “Visual Computing” division of HUman-MAchines INteraction Laboratory (HUMAIN-Lab) and the Director of the MPhil program “Advanced Technologies in Informatics and Computers” hosted by the Department of Computer Science, International Hellenic University. He has (co)authored more than 150 publications in indexed journals, international conferences and book chapters, 1 book (in Greek), 3 edited books, and 5 journal special issues. His publications have more than 2100 citations with h-index 27 (GoogleScholar). His research interests include computer/machine vision, machine learning, pattern recognition, computational intelligence. \nDr. Papakostas served as a reviewer in numerous journals, as a program\ncommittee member in international conferences and he is a member of the IAENG, MIR Labs, EUCogIII, INSTICC and the Technical Chamber of Greece (TEE).",institutionString:null,institution:{name:"International Hellenic University",institutionURL:null,country:{name:"Greece"}}},editorTwo:null,editorThree:null},{id:"25",title:"Evolutionary Computation",coverUrl:"https://cdn.intechopen.com/series_topics/covers/25.jpg",isOpenForSubmission:!0,editor:{id:"136112",title:"Dr.",name:"Sebastian",middleName:null,surname:"Ventura Soto",slug:"sebastian-ventura-soto",fullName:"Sebastian Ventura Soto",profilePictureURL:"https://mts.intechopen.com/storage/users/136112/images/system/136112.png",biography:"Sebastian Ventura is a Spanish researcher, a full professor with the Department of Computer Science and Numerical Analysis, University of Córdoba. Dr Ventura also holds the positions of Affiliated Professor at Virginia Commonwealth University (Richmond, USA) and Distinguished Adjunct Professor at King Abdulaziz University (Jeddah, Saudi Arabia). Additionally, he is deputy director of the Andalusian Research Institute in Data Science and Computational Intelligence (DaSCI) and heads the Knowledge Discovery and Intelligent Systems Research Laboratory. He has published more than ten books and over 300 articles in journals and scientific conferences. Currently, his work has received over 18,000 citations according to Google Scholar, including more than 2200 citations in 2020. In the last five years, he has published more than 60 papers in international journals indexed in the JCR (around 70% of them belonging to first quartile journals) and he has edited some Springer books “Supervised Descriptive Pattern Mining” (2018), “Multiple Instance Learning - Foundations and Algorithms” (2016), and “Pattern Mining with Evolutionary Algorithms” (2016). He has also been involved in more than 20 research projects supported by the Spanish and Andalusian governments and the European Union. He currently belongs to the editorial board of PeerJ Computer Science, Information Fusion and Engineering Applications of Artificial Intelligence journals, being also associate editor of Applied Computational Intelligence and Soft Computing and IEEE Transactions on Cybernetics. Finally, he is editor-in-chief of Progress in Artificial Intelligence. He is a Senior Member of the IEEE Computer, the IEEE Computational Intelligence, and the IEEE Systems, Man, and Cybernetics Societies, and the Association of Computing Machinery (ACM). Finally, his main research interests include data science, computational intelligence, and their applications.",institutionString:null,institution:{name:"University of Córdoba",institutionURL:null,country:{name:"Spain"}}},editorTwo:null,editorThree:null},{id:"26",title:"Machine Learning and Data Mining",coverUrl:"https://cdn.intechopen.com/series_topics/covers/26.jpg",isOpenForSubmission:!0,editor:{id:"24555",title:"Dr.",name:"Marco Antonio",middleName:null,surname:"Aceves Fernandez",slug:"marco-antonio-aceves-fernandez",fullName:"Marco Antonio Aceves Fernandez",profilePictureURL:"https://mts.intechopen.com/storage/users/24555/images/system/24555.jpg",biography:"Dr. Marco Antonio Aceves Fernandez obtained his B.Sc. (Eng.) in Telematics from the Universidad de Colima, Mexico. He obtained both his M.Sc. and Ph.D. from the University of Liverpool, England, in the field of Intelligent Systems. He is a full professor at the Universidad Autonoma de Queretaro, Mexico, and a member of the National System of Researchers (SNI) since 2009. Dr. Aceves Fernandez has published more than 80 research papers as well as a number of book chapters and congress papers. He has contributed in more than 20 funded research projects, both academic and industrial, in the area of artificial intelligence, ranging from environmental, biomedical, automotive, aviation, consumer, and robotics to other applications. He is also a honorary president at the National Association of Embedded Systems (AMESE), a senior member of the IEEE, and a board member of many institutions. His research interests include intelligent and embedded systems.",institutionString:"Universidad Autonoma de Queretaro",institution:{name:"Autonomous University of Queretaro",institutionURL:null,country:{name:"Mexico"}}},editorTwo:null,editorThree:null},{id:"27",title:"Multi-Agent Systems",coverUrl:"https://cdn.intechopen.com/series_topics/covers/27.jpg",isOpenForSubmission:!0,editor:{id:"148497",title:"Dr.",name:"Mehmet",middleName:"Emin",surname:"Aydin",slug:"mehmet-aydin",fullName:"Mehmet Aydin",profilePictureURL:"https://mts.intechopen.com/storage/users/148497/images/system/148497.jpg",biography:"Dr. Mehmet Emin Aydin is a Senior Lecturer with the Department of Computer Science and Creative Technology, the University of the West of England, Bristol, UK. His research interests include swarm intelligence, parallel and distributed metaheuristics, machine learning, intelligent agents and multi-agent systems, resource planning, scheduling and optimization, combinatorial optimization. Dr. Aydin is currently a Fellow of Higher Education Academy, UK, a member of EPSRC College, a senior member of IEEE and a senior member of ACM. In addition to being a member of advisory committees of many international conferences, he is an Editorial Board Member of various peer-reviewed international journals. He has served as guest editor for a number of special issues of peer-reviewed international journals.",institutionString:null,institution:{name:"University of the West of England",institutionURL:null,country:{name:"United Kingdom"}}},editorTwo:null,editorThree:null}]},overviewPageOFChapters:{paginationCount:19,paginationItems:[{id:"82196",title:"Multi-Features Assisted Age Invariant Face Recognition and Retrieval Using CNN with Scale Invariant Heat Kernel Signature",doi:"10.5772/intechopen.104944",signatures:"Kamarajugadda Kishore Kumar and Movva Pavani",slug:"multi-features-assisted-age-invariant-face-recognition-and-retrieval-using-cnn-with-scale-invariant-",totalDownloads:6,totalCrossrefCites:0,totalDimensionsCites:0,authors:null,book:{title:"Pattern Recognition - New Insights",coverURL:"https://cdn.intechopen.com/books/images_new/11442.jpg",subseries:{id:"26",title:"Machine Learning and Data Mining"}}},{id:"82063",title:"Evaluating Similarities and Differences between Machine Learning and Traditional Statistical Modeling in Healthcare Analytics",doi:"10.5772/intechopen.105116",signatures:"Michele Bennett, Ewa J. Kleczyk, Karin Hayes and Rajesh Mehta",slug:"evaluating-similarities-and-differences-between-machine-learning-and-traditional-statistical-modelin",totalDownloads:6,totalCrossrefCites:0,totalDimensionsCites:0,authors:null,book:{title:"Machine Learning and Data Mining - Annual Volume 2022",coverURL:"https://cdn.intechopen.com/books/images_new/11422.jpg",subseries:{id:"26",title:"Machine Learning and Data Mining"}}},{id:"81791",title:"Self-Supervised Contrastive Representation Learning in Computer Vision",doi:"10.5772/intechopen.104785",signatures:"Yalin Bastanlar and Semih Orhan",slug:"self-supervised-contrastive-representation-learning-in-computer-vision",totalDownloads:28,totalCrossrefCites:0,totalDimensionsCites:0,authors:null,book:{title:"Pattern Recognition - New Insights",coverURL:"https://cdn.intechopen.com/books/images_new/11442.jpg",subseries:{id:"26",title:"Machine Learning and Data Mining"}}},{id:"79345",title:"Application of Jump Diffusion Models in Insurance Claim Estimation",doi:"10.5772/intechopen.99853",signatures:"Leonard Mushunje, Chiedza Elvina Mashiri, Edina Chandiwana and Maxwell Mashasha",slug:"application-of-jump-diffusion-models-in-insurance-claim-estimation-1",totalDownloads:9,totalCrossrefCites:0,totalDimensionsCites:0,authors:null,book:{title:"Data Clustering",coverURL:"https://cdn.intechopen.com/books/images_new/10820.jpg",subseries:{id:"26",title:"Machine Learning and Data Mining"}}}]},overviewPagePublishedBooks:{paginationCount:9,paginationItems:[{type:"book",id:"7723",title:"Artificial Intelligence",subtitle:"Applications in Medicine and Biology",coverURL:"https://cdn.intechopen.com/books/images_new/7723.jpg",slug:"artificial-intelligence-applications-in-medicine-and-biology",publishedDate:"July 31st 2019",editedByType:"Edited by",bookSignature:"Marco Antonio Aceves-Fernandez",hash:"a3852659e727f95c98c740ed98146011",volumeInSeries:1,fullTitle:"Artificial Intelligence - Applications in Medicine and Biology",editors:[{id:"24555",title:"Dr.",name:"Marco Antonio",middleName:null,surname:"Aceves Fernandez",slug:"marco-antonio-aceves-fernandez",fullName:"Marco Antonio Aceves Fernandez",profilePictureURL:"https://mts.intechopen.com/storage/users/24555/images/system/24555.jpg",biography:"Dr. Marco Antonio Aceves Fernandez obtained his B.Sc. (Eng.) in Telematics from the Universidad de Colima, Mexico. He obtained both his M.Sc. and Ph.D. from the University of Liverpool, England, in the field of Intelligent Systems. He is a full professor at the Universidad Autonoma de Queretaro, Mexico, and a member of the National System of Researchers (SNI) since 2009. Dr. Aceves Fernandez has published more than 80 research papers as well as a number of book chapters and congress papers. He has contributed in more than 20 funded research projects, both academic and industrial, in the area of artificial intelligence, ranging from environmental, biomedical, automotive, aviation, consumer, and robotics to other applications. He is also a honorary president at the National Association of Embedded Systems (AMESE), a senior member of the IEEE, and a board member of many institutions. 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He is currently a principal researcher in data analytics and optimisation at TECNALIA (Spain), a visiting fellow at the Basque Center for Applied Mathematics (BCAM) and a part-time lecturer at the University of the Basque Country (UPV/EHU). His research interests gravitate on the use of descriptive, prescriptive and predictive algorithms for data mining and optimization in a diverse range of application fields such as Energy, Transport, Telecommunications, Health and Industry, among others. In these fields he has published more than 240 articles, co-supervised 8 Ph.D. theses, edited 6 books, coauthored 7 patents and participated/led more than 40 research projects. 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In recent years, the application of chemistry to biological molecules has gained significant interest in medicinal and pharmacological studies. This topic will be devoted to understanding the interplay between biomolecules and chemical compounds, their structure and function, and their potential applications in related fields. Being a part of the biochemistry discipline, the ideas and concepts that have emerged from Chemical Biology have affected other related areas. This topic will closely deal with all emerging trends in this discipline.",annualVolume:11411,isOpenForSubmission:!0,coverUrl:"https://cdn.intechopen.com/series_topics/covers/15.jpg",editor:{id:"441442",title:"Dr.",name:"Şükrü",middleName:null,surname:"Beydemir",fullName:"Şükrü Beydemir",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y00003GsUoIQAV/Profile_Picture_1634557147521",institutionString:null,institution:{name:"Anadolu University",institutionURL:null,country:{name:"Turkey"}}},editorTwo:{id:"13652",title:"Prof.",name:"Deniz",middleName:null,surname:"Ekinci",fullName:"Deniz Ekinci",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002aYLT1QAO/Profile_Picture_1634557223079",institutionString:null,institution:{name:"Ondokuz Mayıs University",institutionURL:null,country:{name:"Turkey"}}},editorThree:null,editorialBoard:[{id:"219081",title:"Dr.",name:"Abdulsamed",middleName:null,surname:"Kükürt",fullName:"Abdulsamed Kükürt",profilePictureURL:"https://mts.intechopen.com/storage/users/219081/images/system/219081.png",institutionString:null,institution:{name:"Kafkas University",institutionURL:null,country:{name:"Turkey"}}},{id:"241413",title:"Dr.",name:"Azhar",middleName:null,surname:"Rasul",fullName:"Azhar Rasul",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRT1oQAG/Profile_Picture_1635251978933",institutionString:null,institution:{name:"Government College University, Faisalabad",institutionURL:null,country:{name:"Pakistan"}}},{id:"178316",title:"Ph.D.",name:"Sergey",middleName:null,surname:"Sedykh",fullName:"Sergey Sedykh",profilePictureURL:"https://mts.intechopen.com/storage/users/178316/images/system/178316.jfif",institutionString:null,institution:{name:"Novosibirsk State University",institutionURL:null,country:{name:"Russia"}}}]},{id:"17",title:"Metabolism",keywords:"Biomolecules Metabolism, Energy Metabolism, Metabolic Pathways, Key Metabolic Enzymes, Metabolic Adaptation",scope:"Metabolism is frequently defined in biochemistry textbooks as the overall process that allows living systems to acquire and use the free energy they need for their vital functions or the chemical processes that occur within a living organism to maintain life. Behind these definitions are hidden all the aspects of normal and pathological functioning of all processes that the topic ‘Metabolism’ will cover within the Biochemistry Series. Thus all studies on metabolism will be considered for publication.",annualVolume:11413,isOpenForSubmission:!0,coverUrl:"https://cdn.intechopen.com/series_topics/covers/17.jpg",editor:{id:"138626",title:"Dr.",name:"Yannis",middleName:null,surname:"Karamanos",fullName:"Yannis Karamanos",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002g6Jv2QAE/Profile_Picture_1629356660984",institutionString:null,institution:{name:"Artois University",institutionURL:null,country:{name:"France"}}},editorTwo:null,editorThree:null,editorialBoard:[{id:"243049",title:"Dr.",name:"Anca",middleName:null,surname:"Pantea Stoian",fullName:"Anca Pantea Stoian",profilePictureURL:"https://mts.intechopen.com/storage/users/243049/images/system/243049.jpg",institutionString:null,institution:{name:"Carol Davila University of Medicine and Pharmacy",institutionURL:null,country:{name:"Romania"}}},{id:"203824",title:"Dr.",name:"Attilio",middleName:null,surname:"Rigotti",fullName:"Attilio Rigotti",profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institutionString:null,institution:{name:"Pontifical Catholic University of Chile",institutionURL:null,country:{name:"Chile"}}},{id:"300470",title:"Dr.",name:"Yanfei (Jacob)",middleName:null,surname:"Qi",fullName:"Yanfei (Jacob) Qi",profilePictureURL:"https://mts.intechopen.com/storage/users/300470/images/system/300470.jpg",institutionString:null,institution:{name:"Centenary Institute of Cancer Medicine and Cell Biology",institutionURL:null,country:{name:"Australia"}}}]},{id:"18",title:"Proteomics",keywords:"Mono- and Two-Dimensional Gel Electrophoresis (1-and 2-DE), Liquid Chromatography (LC), Mass Spectrometry/Tandem Mass Spectrometry (MS; MS/MS), Proteins",scope:"With the recognition that the human genome cannot provide answers to the etiology of a disorder, changes in the proteins expressed by a genome became a focus in research. Thus proteomics, an area of research that detects all protein forms expressed in an organism, including splice isoforms and post-translational modifications, is more suitable than genomics for a comprehensive understanding of the biochemical processes that govern life. The most common proteomics applications are currently in the clinical field for the identification, in a variety of biological matrices, of biomarkers for diagnosis and therapeutic intervention of disorders. From the comparison of proteomic profiles of control and disease or different physiological states, which may emerge, changes in protein expression can provide new insights into the roles played by some proteins in human pathologies. Understanding how proteins function and interact with each other is another goal of proteomics that makes this approach even more intriguing. Specialized technology and expertise are required to assess the proteome of any biological sample. Currently, proteomics relies mainly on mass spectrometry (MS) combined with electrophoretic (1 or 2-DE-MS) and/or chromatographic techniques (LC-MS/MS). MS is an excellent tool that has gained popularity in proteomics because of its ability to gather a complex body of information such as cataloging protein expression, identifying protein modification sites, and defining protein interactions. The Proteomics topic aims to attract contributions on all aspects of MS-based proteomics that, by pushing the boundaries of MS capabilities, may address biological problems that have not been resolved yet.",annualVolume:11414,isOpenForSubmission:!0,coverUrl:"https://cdn.intechopen.com/series_topics/covers/18.jpg",editor:{id:"200689",title:"Prof.",name:"Paolo",middleName:null,surname:"Iadarola",fullName:"Paolo Iadarola",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bSCl8QAG/Profile_Picture_1623568118342",institutionString:null,institution:{name:"University of Pavia",institutionURL:null,country:{name:"Italy"}}},editorTwo:{id:"201414",title:"Dr.",name:"Simona",middleName:null,surname:"Viglio",fullName:"Simona Viglio",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRKDHQA4/Profile_Picture_1630402531487",institutionString:null,institution:{name:"University of Pavia",institutionURL:null,country:{name:"Italy"}}},editorThree:null,editorialBoard:[{id:"72288",title:"Dr.",name:"Arli Aditya",middleName:null,surname:"Parikesit",fullName:"Arli Aditya Parikesit",profilePictureURL:"https://mts.intechopen.com/storage/users/72288/images/system/72288.jpg",institutionString:null,institution:{name:"Indonesia International Institute for Life Sciences",institutionURL:null,country:{name:"Indonesia"}}},{id:"40928",title:"Dr.",name:"Cesar",middleName:null,surname:"Lopez-Camarillo",fullName:"Cesar Lopez-Camarillo",profilePictureURL:"https://mts.intechopen.com/storage/users/40928/images/3884_n.png",institutionString:null,institution:{name:"Universidad Autónoma de la Ciudad de México",institutionURL:null,country:{name:"Mexico"}}},{id:"81926",title:"Dr.",name:"Shymaa",middleName:null,surname:"Enany",fullName:"Shymaa Enany",profilePictureURL:"https://mts.intechopen.com/storage/users/81926/images/system/81926.png",institutionString:"Suez Canal University",institution:{name:"Suez Canal University",institutionURL:null,country:{name:"Egypt"}}}]}]}},libraryRecommendation:{success:null,errors:{},institutions:[]},route:{name:"chapter.detail",path:"/chapters/18390",hash:"",query:{},params:{id:"18390"},fullPath:"/chapters/18390",meta:{},from:{name:null,path:"/",hash:"",query:{},params:{},fullPath:"/",meta:{}}}},function(){var e;(e=document.currentScript||document.scripts[document.scripts.length-1]).parentNode.removeChild(e)}()