IntechOpen Book Series will also publish a program of research-driven Thematic Edited Volumes that focus on specific areas and allow for a more in-depth overview of a particular subject.
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IntechOpen Book Series will be launching regularly to offer our authors and editors exciting opportunities to publish their research Open Access. We will begin by relaunching some of our existing Book Series in this innovative book format, and will expand in 2022 into rapidly growing research fields that are driving and advancing society.
With the desire to make book publishing more relevant for the digital age and offer innovative Open Access publishing options, we are thrilled to announce the launch of our new publishing format: IntechOpen Book Series.
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Designed to cover fast-moving research fields in rapidly expanding areas, our Book Series feature a Topic structure allowing us to present the most relevant sub-disciplines. Book Series are headed by Series Editors, and a team of Topic Editors supported by international Editorial Board members. Topics are always open for submissions, with an Annual Volume published each calendar year.
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After a robust peer-review process, accepted works are published quickly, thanks to Online First, ensuring research is made available to the scientific community without delay.
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Our innovative Book Series format brings you:
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Topic Focused Publications - Each topic showcases high impact subject areas
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Renowned Editorial Expertise - Series Editors, Topic Editors, and a team of international Board Members that permanently support each Book Series
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Fast Publishing - quick turnaround which is unique for book publishing
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The benefit of ISSN and ISBN for increased citation and indexing possibilities
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IntechOpen Book Series will also publish a program of research-driven Thematic Edited Volumes that focus on specific areas and allow for a more in-depth overview of a particular subject.
\n\n
IntechOpen Book Series will be launching regularly to offer our authors and editors exciting opportunities to publish their research Open Access. We will begin by relaunching some of our existing Book Series in this innovative book format, and will expand in 2022 into rapidly growing research fields that are driving and advancing society.
We invite you to explore our IntechOpen Book Series, find the right publishing program for you and reach your desired audience in record time.
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Note: Edited in October 2021
\n'}],latestNews:[{slug:"intechopen-supports-asapbio-s-new-initiative-publish-your-reviews-20220729",title:"IntechOpen Supports ASAPbio’s New Initiative Publish Your Reviews"},{slug:"webinar-introduction-to-open-science-wednesday-18-may-1-pm-cest-20220518",title:"Webinar: Introduction to Open Science | Wednesday 18 May, 1 PM CEST"},{slug:"step-in-the-right-direction-intechopen-launches-a-portfolio-of-open-science-journals-20220414",title:"Step in the Right Direction: IntechOpen Launches a Portfolio of Open Science Journals"},{slug:"let-s-meet-at-london-book-fair-5-7-april-2022-olympia-london-20220321",title:"Let’s meet at London Book Fair, 5-7 April 2022, Olympia London"},{slug:"50-books-published-as-part-of-intechopen-and-knowledge-unlatched-ku-collaboration-20220316",title:"50 Books published as part of IntechOpen and Knowledge Unlatched (KU) Collaboration"},{slug:"intechopen-joins-the-united-nations-sustainable-development-goals-publishers-compact-20221702",title:"IntechOpen joins the United Nations Sustainable Development Goals Publishers Compact"},{slug:"intechopen-signs-exclusive-representation-agreement-with-lsr-libros-servicios-y-representaciones-s-a-de-c-v-20211123",title:"IntechOpen Signs Exclusive Representation Agreement with LSR Libros Servicios y Representaciones S.A. de C.V"},{slug:"intechopen-expands-partnership-with-research4life-20211110",title:"IntechOpen Expands Partnership with Research4Life"}]},book:{item:{type:"book",id:"3245",leadTitle:null,fullTitle:"A Comprehensive Survey of International Soybean Research - Genetics, Physiology, Agronomy and Nitrogen Relationships",title:"A Comprehensive Survey of International Soybean Research",subtitle:"Genetics, Physiology, Agronomy and Nitrogen Relationships",reviewType:"peer-reviewed",abstract:"Soybean is the most important oilseed and livestock feed crop in the world. These dual uses are attributed to the crop's high protein content (nearly 40% of seed weight) and oil content (approximately 20%); characteristics that are not rivaled by any other agronomic crop. Across the 10-year period from 2001 to 2010, world soybean production increased from 168 to 258 million metric tons (54% increase). Against the backdrop of soybean's striking ascendancy is increased research interest in the crop throughout the world. Information in this book presents a comprehensive view of research efforts in genetics, plant physiology, agronomy, agricultural economics, and nitrogen relationships that will benefit soybean stakeholders and scientists throughout the world. We hope you enjoy the book.",isbn:null,printIsbn:"978-953-51-0876-4",pdfIsbn:"978-953-51-4259-1",doi:"10.5772/45867",price:159,priceEur:175,priceUsd:205,slug:"a-comprehensive-survey-of-international-soybean-research-genetics-physiology-agronomy-and-nitrogen-relationships",numberOfPages:626,isOpenForSubmission:!1,isInWos:1,isInBkci:!0,hash:"3df988c24d0849fa18b82a63f62ad860",bookSignature:"James E. Board",publishedDate:"January 2nd 2013",coverURL:"https://cdn.intechopen.com/books/images_new/3245.jpg",numberOfDownloads:75764,numberOfWosCitations:11,numberOfCrossrefCitations:85,numberOfCrossrefCitationsByBook:10,numberOfDimensionsCitations:234,numberOfDimensionsCitationsByBook:14,hasAltmetrics:1,numberOfTotalCitations:330,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"February 28th 2012",dateEndSecondStepPublish:"March 20th 2012",dateEndThirdStepPublish:"June 16th 2012",dateEndFourthStepPublish:"July 16th 2012",dateEndFifthStepPublish:"October 15th 2012",currentStepOfPublishingProcess:5,indexedIn:"1,2,3,4,5,6,8,9",editedByType:"Edited by",kuFlag:!1,featuredMarkup:null,editors:[{id:"28828",title:"Prof.",name:"James",middleName:null,surname:"Board",slug:"james-board",fullName:"James Board",profilePictureURL:"https://mts.intechopen.com/storage/users/28828/images/3420_n.jpg",biography:"James Board is a Professor of Agronomy in the School of Plant, Environmental, and Soil Sciences in the Louisiana State University Agricultural Center in Baton Rouge, Louisiana, USA. He obtained a Ph.D. in plant physiology from the University of California at Davis in 1978, and shortly thereafter assumed his current position. He has been working on soybean production and physiology at this institution for the last 32 years and has also taught crop ecological/physiological classes across this period. 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1. Introduction
The very first nano-scientist was a Roman potter, who made the Lycurgus Cup as the oldest known application of nanomaterials (fifth-fourth century B.C.). This cup was made from so-called “gold-ruby glass” containing tiny gold droplets (5–60 nm in size). Therefore, the glass appeared green in daylight (reflected light), but red when light was transmitted from the inside of the vessel [1]. In spite of the fact that we do not know the name of the potter, which is based on nano-research without the knowledge of nanoparticles, Richard Feynman opened “nano-window of twenty-first century” with his lecture “There’s plenty of room at the bottom”. This lecture came to be looked upon as the starting point of nanoscience as we are already living in [2]. In 1974, Taniguchi used the term “Nanotechnology” for the first time. This term was defined as the technology, where dimensions, within the range of 0.1–100 nm, play a key role. At the nanolevel, gravity is less an issue while the strength of materials is a bigger one and also quantum size effect is a key aspect. Due to the unique size-dependent spectroscopic, electronic, and thermal features and also chemical properties, and ability to be functionalized, arising from the small sizes and large surface-to-volume ratio, nanomaterials found their applications not only in electronics, physics, and engineering but also in natural sciences. Although nanomaterials are greatly affecting numerous scientific fields, it can be perceived differently. In chemistry, the range of sizes has been associated with colloid solutions, micelles, polymeric molecules, and also large molecules, or aggregates of number of molecules. Recently, structures such as carbon nanotubes, silicon nanorods, and semiconductor quantum dots have been emerged as particularly interesting classes of nanomaterials. In physics and electrical engineering, nanoscience is most often associated with quantum behavior, and the behavior of electrons and photons in nanoscale structures. Biochemistry and biology is interested in nanostructures such as cells components. The most widely investigated biological structures including DNA, viruses, and subcellular organelles can be considered as nanostructures [3].
1.1. From nano-pottery to modern analytical tools
It is obvious that “nano” influences the whole scientific world including instrumental analytical chemistry. Due to above-mentioned unique properties, not only new approaches and assays are being developed, but also standard techniques have been upgraded and capillary electrophoresis (CE) belongs to the group of these highly affected methods. In 1981, and since then, this powerful analytical technique progressed significantly not only in instrumentation, but also in method development, data acquisition, and processing. The group of applications has also widened markedly. The applications of CE are covering huge number of analytes from inorganic ions [4, 5, 6, 7, 8] and organic molecules [9, 10, 11] to biomolecules such as proteins [12, 13, 14] and DNA [15, 16, 17]. The golden era of CE was in 1990s, during the Human Genome Project [18]. The sequencing of the whole human genome was successfully finished in 2006 identifying all 20,000–25,000 genes (approximately) in human DNA and determining the sequences of 3 billion base pairs that make up human DNA.
Next great boom of CE begun due to the micro-total analysis system (μTAS) concept [19]. Due to the relatively simple instrumentation and ease of miniaturization of CE, the fast growth of attention in microfluidics and particularly in chip-based CE [20, 21, 22, 23] was observed. Even though CE provides rapid results with high efficiency and resolution, and sample consumption is low; advantages of high number of theoretical plates can be diminished by relatively low sensitivity of commonly used photometric detection systems [24]. Therefore, new approaches improving these weak sites are investigated and the use of nanomaterials is widely tested.
2. Capillary electrophoresis
Capillary electrophoresis is an extremely powerful microcolumn separation technique, separating molecules based on their mobilities in the electric field. Its main advantages include high separation efficiency, short time of analysis, and low consumption of chemicals.
Classical CE separation takes place in a fused silica capillary with internal diameter of 20–100 μm, where the voltage of up to ±30 kV is applied. The scheme of the setup is shown in Figure 1.
Figure 1.
Scheme of CE setup.
Diversity of detection modalities applicable in CE is very wide. Optical detection methods including photometric and fluorimetric detection are probably the most common ones currently used in CE; however, electrochemical detection including amperometric and contactless conductometric detection have unparalleled advantages. Especially for analysis of small inorganic ions, which do not absorb light, electrochemical detection is an alternative to the indirect optical approach. Also, popularity of mass spectrometric (MS) detection coupled to CE increased rapidly in past few decades.
From the very beginning, electromigration methods benefited from the use of certain sieving media, such as paper or gel. Moreover, since the separations have been transferred to capillary and/or chip, the addition of some kind of “stationary phase”, sieving media or pseudo-stationary phase increased the number of applications. This step led to rise of several electrophoretic methods such as capillary electrochromatography or capillary micellar electrokinetic chromatography.
Low sensitivity, which is probably the main weakness of CE in connection with the most wide spread detection method—spectrophotometric detection—is caused by the short optical path-length (given by the capillary diameter) and the low sample volume that is injected. Therefore, a preconcentration step is usually used for analysis of relatively diluted sample solutions. The injected sample solution should have low salt concentration to enable the sample stacking process. Otherwise the electro-osmotic flow can be altered, and the unfavorable detector background signal may be observed. Two main methods are used for sample pretreatment and preconcentration: (i) an electrophoretic method and (ii) a chromatographic technique. Electrophoretic techniques are based on differences in the electrophoretic mobilities of the analytes. Four main types of these techniques have been presented: transient isotachophoresis [25, 26], stacking [27, 28, 29], sweeping [30, 31, 32], and dynamic pH junction [33, 34]. On the other hand, chromatographic techniques rely on analyte sorption on a surface of the stationary phase. Chromatographic techniques allow for loading of large volumes followed by preconcentration on a sorbent and subsequent elution into a small volume of solvent, resulting in lower limits of detection.
For such applications, nanomaterials are excellent candidates because, compared to bulk materials, nanomaterials offer significantly higher surface-to-volume ratios, and therefore provide higher sorption capacity and thus better extraction efficiencies. As an example, may serve the comparison of surface area of carbon microparticles with 60 μm in diameter of (0.01 mm2) and the surface area of carbon nanoparticles with 60 nm in diameter (11.3 mm2). Similar to the increase in the surface area, the reactivity is also increased by approximately three orders of magnitude. Not only the surface area, but also the chemical affinity may be beneficial. For example, gold nanoparticles provide excellent extraction power due to their high affinity for thiol-containing compounds.
Similarly, magnetic separation is a method using magnetism for the efficient separation mediated by paramagnetic and superparamagnetic particles. This technique takes advantage of the option of surface modification of magnetic nanoparticles to enable so-called immunoextraction. Such particles may be modified by either antibodies for specific capture of the target analyte or by oligonucleotide fragments having sequences complementary to the desired nucleic acid. Magnetic particles can be immobilized using an external magnetic field and interfering compounds are removed from the solution [35].
3. Capillary electrophoresis for analysis of nanomaterials
The field of nanomaterials (e.g. metal or polymeric nanoparticles and carbon nanomaterials) is one of the most attractive and quickly emerging, while these materials have often valuable properties for various applications. The synthesis, however, is problematic especially from batch-to-batch repeatability point of view and, sometimes, techniques enabling characterization of nanomaterial properties and composition are absent. Even within a single batch, the polydispersity of the particles and the variability of their properties may present insurmountable problem for reliable application [36].
The conventional methods evaluating the size distribution are transmission electron microscopy and/or size exclusion chromatography. However, these methods have disadvantages including high instrumental costs, time consuming and laborious sample preparation, and high requirements on an operator, because of interpretation of the results. Therefore conventional or microfluidic CE is a good alternative for characterization of colloids and nanomaterials. Review articles focusing on electrophoretic separation of nanoparticles has been published in 2004 by Rodriguez and Armstrong [37], later by Surugau and Urban [38], Pyell [39], Lopez-Lorente et al. [40], and in 2017 by Aleksenko et al. [41]. Microfluidic format used in nanoparticle separation was reviewed by Salafi et al. [42]. More focused review article about CE analysis of poly(amidoamine) dendrimeric structures was prepared by Shi et al. [43]. Paper summarizing the application of separation techniques (including CE) of gold nanoparticles [44, 45] and QDs [46, 47] analysis are also accessible.
One of the main advantages of nanomaterials is that their surface can be easily functionalized and modified with various molecules potentially applicable for interactions with other molecules. Therefore, CE can (i) monitor the interaction between nanomaterial and analyte, (ii) monitor the interaction between two analytes facilitated by the nanomaterial, and (iii) monitor the interaction between two analytes expressed as a change in the signal of the nanomaterial.
4. Nanomaterials enhancing performance of capillary electrophoresis
4.1. Enhancement of separation
Nowadays, an increasing number of researchers perform CE separations in short capillaries (units of centimeters) instead of microfluidic chips [48, 49]. In such capillaries, fast and efficient separations are carried out without complicated chip preparation requiring expensive facilities (e.g. clean rooms and lithography). Compared with microchip-based high-speed CE systems, short capillary-based high-speed CE systems take advantage of simple structure, easy fabrication, and low costs.
The disadvantage, however, is in lowered resolution connected with short separation length. This obstacle can be solved either by injection of extremely low sample volumes (picoliters) or by additional selectivity given by stationary of pseudo-stationary phases of various natures (e.g. micelles, nanoparticles, nanostructures, etc.), which significantly eliminate the adsorption of highly abundant proteins on the capillary wall [50, 51, 52, 53]. Nanomaterials have been proven to be effective (pseudo)stationary phase due to their beneficial properties, such as large surface–to-volume ratio and easy modification. The most commonly used nanomaterials are carbon nanotubes [54]. However, other structures including nanoparticles [55, 56], nanofibres [57], and/or nanorods [58, 59] have been utilized for these purposes. On the other hand, surface-binding method uses interaction between analyte with the surface of fixed nanostructures such as monoliths, nanopillars, immobilized nanoparticles, and/or other nanomaterials. All of these types have already been employed in coupling with in either capillary-based CE or microfluidic CE. Immobilized nanomaterials, either deposited on capillary wall as a thin layer coating or packed within the capillary, are commonly utilized as stationary phases for capillary electrochromatography. The (pseudo)stationary phases enable a broad range of functionalities offering a variety of interactions [60] (Figure 2).
The efficiency of separation of two compounds is defined as resolution (RS). It can be affected by alternating the electrophoretic mobility of the analytes and their electrophoretic mobilities. RS can be calculated according to the equation (1):
RS=√NμelA−μelB4μav+μEOFE1
where N is the number of theoretical plates, μelA and μelB are electrophoretic mobilities of the analytes, μav is the mean electrophoretic mobility of analyte A and B, and μEOF is mobility of electro-osmotic flow.
Figure 2.
Approaches for separation performance enhancement by nanomaterials. (A) Physically adsorbed opentubular phase, (B) covalently bound opentubular phase, (C) co-polymerized opentubular pahse, (D) full-filling sieving matrix, (E) mobile pseudo-stationary phase.
4.2. Enhancement of detection
Laser-induced fluorescence detection is (and most likely will be also in the future) the most sensitive detection technique among the optical detection modes following chemical separation. It has exceptionally low limits of detection (10−13 M) [61] and good detection selectivity in cases of sample analysis with rather complex matrices. Simultaneously, this selectivity could be perceived as a limitation because the majority of analytes lacks the desired fluorescent properties, and therefore, derivatization by some fluorescent label is needed.
Optical detection in association with nanomaterials is mainly connected with quantum dots due to their application as a fluorescent labels in laser-induced fluorescence detection [62, 63, 64, 65]. An indirect laser-induced fluorescence mode of detection by means of CdTe quantum dots has been demonstrated and therefore determination of small organic acids in food with detection limits in the range of tenths of mg/L was enabled [64]. Moreover, determination of pesticide and antibiotic residues in vegetables [66, 67] and in foods [68] has been described. Chen and Fung presented laser-induced fluorescence detection using immobilized QDs to determine organophosphate pesticides (mevinphos, phosalone, methidathion, and diazinon) in vegetable samples [69]. Detection limits of the method were in the range of tens of μg/kg.
Besides photoluminescence detection, chemiluminescence (CL) and electrochemiluminescence detection are also benefiting from properties of nanomaterials [70]. CL detection is based on measurement of electromagnetic radiation released after excitation of the electron by chemical reaction. The main advantages of CL are in the absence of undesired background signals, improved sensitivity, and wide linear dynamic range. Moreover, no excitation sources and/or optical filters are essential; therefore the instrumentation is simple, robust, and relatively low cost. In such instruments, metal-based nanoparticles can be used as catalysts, reductants, fluorophores, or acceptors of energy. Metal nanoparticles, such as gold, silver, platinum, semiconductors, and magnetic types, provide beneficial properties for CL detection [71].
Electrochemical detection in CE can be carried out in three modes: potentiometric, amperometric, and conductometric. Potentiometric and conductometric detectors provide good sensitivity and on contrary, amperometric detection is selective and can be tuned to the analyte of interest. One of the main differences of this approach compared to the optical detection modes is that the electrochemical detection is mostly performed by off-column, end-capillary, and therefore, in destructive arrangement.
The use of nanomaterials for electrochemical detection covers a remarkably broad field. Due to their electrochemical properties, nanomaterials have been applied for electrochemical analysis of many analytes, comprising of nucleic acids [72, 73, 74], proteins [75, 76], secondary metabolites [77, 78], and/or metals [79]. The key roles delivered by nanoparticles include biomolecule immobilization, catalysis of electrochemical reactions, enhancement of electron transfer between electrode surfaces and proteins, biomolecule labeling, and even use as a reactant [80]. In addition to the relatively low financial demands of electrochemical detection in comparison to optical instrumentation, advantages such as the possibility of miniaturization and in-field applications are vital. Number of reviews covering this topic has been published. For example, Pumera and Escarpa [81] summarized the different approaches for constructing nanomaterial-based detectors for conventional CE and microchip electrophoresis and mostly focused on three main types of nanomaterials, that is, carbon nanotubes, nanoparticles, and nanorods, in various designs. The work by Garcia-Carmona focusses on highlighting the electrochemical detection enhancement in CE, chip electrophoresis, and paper-based microfluidic devices [82].
In our opinion, it is highly unlikely that nanomaterials will wholly substitute such well-established approaches as organic dyes for fluorescent labeling. However, nanomaterials offer new options for a broad range of applications. The electrochemical detection particularly benefits from use of nanomaterials that enable increasingly sensitive detection.
5. Conclusion
There is no doubt that nanomaterials are extremely valuable tool for analytical applications enhancing highly the efficiency of extraction techniques, increasing significantly the resolution of separations, and improving greatly the capabilities of detection systems. There are a lot of key features of instruments used for clinical purposes including being easy to use and robust. In spite of the great advantages of capillary electrophoresis, robustness and repeatability of measurements belong to its weaknesses, which represent an obstacle for using of capillary electrophoretic instrumentation in clinical practice with one exception represented by DNA sequencer. Utilization of nanomaterials in capillary electrophoresis is opening new perspective in the field of clinical usage because these advanced materials can lower detection limits on one side and enhance the separation effectiveness on the other side. Nevertheless, this is at the beginning and waiting for exploration.
From the CE point of view, NMs such as liposomes and dendrimes have abilities to improve the separation part of the CE analysis and QDs, on the other hand, they can significantly improve the detection part. However, there are several members of the nanomaterial family, which can improve both of those—carbon nanotubes and metal nanoparticles. At the same time, CE is an effective technique for NMs characterization, evaluation, and/or observation (Figure 3).
Figure 3.
Summary of applications of nanomaterials in capillary electrophoresis.
The symbiosis of CE and nanomaterials is beneficial not only for analytical chemists and material scientists, but also for biochemists and molecular biologists, because it leads to the development of new, more effective, and more sensitive methods.
The combination with the simplicity of miniaturization is opening the opportunities for portable and point-of-care applicable instrumentation suitable for personalized diagnostics. Moreover the separation power of electrophoretic analysis, even increased by nanomaterial-based stationary and pseudo-stationary phased in combination with advances in microfluidics, promises effective analyses of complex biological samples.
Acknowledgments
Financial support was provided by Grant agency of Czech Republic (GACR 16-23647Y) and project CEITEC 2020 (LQ1601) with financial support from the Ministry of Education, Youth and Sports of the Czech Republic under the National Sustainability Programme II.
\n',keywords:"capillary electrophoresis, nanomaterials, separation efficiency, sensitivity",chapterPDFUrl:"https://cdn.intechopen.com/pdfs/57884.pdf",chapterXML:"https://mts.intechopen.com/source/xml/57884.xml",downloadPdfUrl:"/chapter/pdf-download/57884",previewPdfUrl:"/chapter/pdf-preview/57884",totalDownloads:1137,totalViews:169,totalCrossrefCites:0,totalDimensionsCites:0,totalAltmetricsMentions:0,introChapter:null,impactScore:0,impactScorePercentile:39,impactScoreQuartile:2,hasAltmetrics:0,dateSubmitted:"June 29th 2017",dateReviewed:"October 27th 2017",datePrePublished:"December 20th 2017",datePublished:"April 18th 2018",dateFinished:"November 29th 2017",readingETA:"0",abstract:"Nanomaterials are attracting an interest of many researches. All this attention is due the unique physical and chemical properties of nanomaterials differing significantly from the bulk materials mainly due to their size in range of nanometers. Capillary electrophoresis (CE) is a powerful, well-established analytical technique that provides numerous valuable benefits over other separation methods including high-performance liquid chromatography. The connection between CE and nanotechnology can be approached by two strategies: (i) CE analysis of nanomaterials and (ii) nanomaterials for CE improvement. The first perspective focuses on uses of CE as a method for characterization employed during nanomaterial production and modification as well as for monitoring their properties and interactions with other molecules. The second viewpoint deals with applications of nanomaterials for improving CE performance, mainly by enhancing efficiency of separation using nanomaterials as a stationary or pseudo-stationary phase and by enhancing detection sensitivity and/or selectivity in both optical and electrochemical detection. Moreover, applications of nanomaterials for sample preparation before CE analysis will be mentioned. This chapter aims at highlighting the symbiosis of CE and nanotechnology as a combination of modern, progressive field with well-known and reliable analytical method.",reviewType:"peer-reviewed",bibtexUrl:"/chapter/bibtex/57884",risUrl:"/chapter/ris/57884",book:{id:"6408",slug:"novel-nanomaterials-synthesis-and-applications"},signatures:"Vojtech Adam and Marketa Vaculovicova",authors:[{id:"142677",title:"Dr.",name:"Vojtech",middleName:null,surname:"Adam",fullName:"Vojtech Adam",slug:"vojtech-adam",email:"vojtech.adam@mendelu.cz",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:{name:"Mendel University Brno",institutionURL:null,country:{name:"Czech Republic"}}},{id:"177390",title:"Dr.",name:"Marketa",middleName:null,surname:"Vaculovicova",fullName:"Marketa Vaculovicova",slug:"marketa-vaculovicova",email:"Marketa.Ryvolova@seznam.cz",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:null}],sections:[{id:"sec_1",title:"1. Introduction",level:"1"},{id:"sec_1_2",title:"1.1. From nano-pottery to modern analytical tools",level:"2"},{id:"sec_3",title:"2. Capillary electrophoresis",level:"1"},{id:"sec_4",title:"3. Capillary electrophoresis for analysis of nanomaterials",level:"1"},{id:"sec_5",title:"4. Nanomaterials enhancing performance of capillary electrophoresis",level:"1"},{id:"sec_5_2",title:"4.1. Enhancement of separation",level:"2"},{id:"sec_6_2",title:"4.2. Enhancement of detection",level:"2"},{id:"sec_8",title:"5. Conclusion",level:"1"},{id:"sec_9",title:"Acknowledgments",level:"1"}],chapterReferences:[{id:"B1",body:'Wagner FE, Haslbeck S, Stievano L, Calogero S, Pankhurst QA, Martinek P. Before striking gold in gold-ruby glass. Nature. 2000;407:691-692'},{id:"B2",body:'Yadugiri VT, Malhotra R. ‘Plenty of room’—fifty years after the Feynman lecture. Current Science. 2010;99:900-907'},{id:"B3",body:'Whitesides GM. Nanoscience, nanotechnology, and chemistry. 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Department of Chemistry and Biochemistry, Mendel University in Brno, Czech Republic
Central European Institute of Technology, Brno University of Technology, Czech Republic
Department of Chemistry and Biochemistry, Mendel University in Brno, Czech Republic
Central European Institute of Technology, Brno University of Technology, Czech Republic
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1. Introduction
The environmental issues associated with residual dye content or residual color in treated textile effluents are always a concern for each textile operator that directly discharges, sewage treatment works as well as commercial textile operations to meet the requirements of color and residual dye imposed on the discharge of treated effluent [1]. In watercourses higher than 1.0 mg/L, dye concentrations induced by direct discharges of textile effluents, treated or not, can give rise to public enforcement. High concentrations of fabric dyes in water bodies halt the reoxygenation potential of the receiving water and cutoff sunlight, thereby disrupting biological activity in aquatic life as well as the aquatic plant or algae photosynthesis process [2]. Presence of dye is accepted as an esthetic issue in watercourses rather than as an eco-toxic hazard. The public appears to know the blue, green and brown color of the rivers, but the color ‘non-natural’ as red and purple usually causes the most concern. Due to their long-term existence in the environment (i.e., half-life of several years), accumulation in sediments and particularly in fish or other aquatic life forms, decomposition of contaminants in carcinogenic or mutagenic compounds, and also their low aerobic biodegradability, the polluting effects of dyes on the aquatic environment may also result in toxic effects. The majority of dyes are nonbiodegradable due to their artificial origin or chemical composition, possess carcinogenic activity, and induce asthma, dermatitis, inflammation of the skin, and various tissue changes. In addition, various azo dyes, primarily aromatic compounds, show toxicity both acute and chronic. High potential health risk is caused by adsorption of azo dyes and their breakdown products (toxic amines) through the gastrointestinal tract, body, lungs, and hemoglobin adduct formation as well as blood formation disturbance [3].
There are about 700,000 tons of colors, approaching 10,000 forms, often used as color operators in most of projects. The use of colors in characteristic media is disturbing considering their heavy workload, poisonous content, and bioaccumulative ability in living beings. In particular, the azo dyes that are most advertised and that cause cancer, need to be taken seriously. The current status of cationic and anionic dyes is audited here. For this reason, common adsorbents are commonly used, such as activated carbon, chitosan, composite, and natural waste. Various dangerous engineered dyes (cationic and anionic) have been fabricated with high creation rate. To dispose of their negative effects, the broad utilization of composite was watched for oxidative debasement/expulsion of colors from wastewater. In cationic dye, methylene blue, precious stone violet, Splendid Blue-R, and Rhodamine-B, while in anionic dye, Methyl orange, Congo red, Alizarin red S and Eosin Y, are broadly treated with composite.
Adsorption methods are used as procedures of high quality for the removal of dissolved organic contaminants from industrial wastewater, such as dyes. The fiber, pulp and paper industries are stated to use large quantities of a number of colors; such chemicals can be used in many wastewater factories that generating vast amounts of sprayed, toxic and even cancerous wastewater, causing serious hazard to aquatic living organisms. It is well known that dye effluents from the production of dyestuffs and fabric industries may have toxic effects on microbial organisms and may be toxic and/or cancerous to mammalian animals. Most of the dyes used in textile industries are resistant to light and not biodegradable. These are also resistant to aerobic digestion [4]. Because of simple design, adsorption has advantages over other methods and can entail low investment in terms of both initial and necessary land costs. The adsorption method is commonly used to treat industrial wastewater from organic and inorganic contaminants, and the researchers are paying close attention to it. The search for low-cost adsorbents with pollutant-binding capabilities has intensified in recent years. Locally available materials such as natural materials, agricultural waste, and industrial waste can be used as adsorbents at low cost. For groundwater and wastewater treatment, the activated carbon produced from these materials can be used as an adsorbent [5]. Natural hydroxyapatite derived from bio-waste, bovine and camel bones in general. To remove the natural hydroxyapatite, three separate methods are applied: thermal decomposition, subcritical water, and alkaline hydrothermal processes. Results from many physiochemical analyses have shown that all the methods used are capable of removing the organic compounds present in bovine bones and producing pure bio-ceramic hydroxyapatite with an average yield of 65% [6]. A composite material is made by consolidating at least two materials—frequently ones that have altogether different properties. The two materials cooperate to give the composite novel properties. In any case, inside the composite you can without much of a stretch differentiate the distinctive materials one from the other as they do not break up or mix into each other [7]. One of the biggest advantages of the composite is it can be formed into entangled shapes more effortlessly than most different materials. This gives fashion designers the versatility to build any form or structure. In addition, composites are light in weight, contrasted with most woods and metals, possess high strength, dimensional stability, and are nonmagnetic. Composites contain no metals; hence, they are not attractive. They can be utilized around touchy electronic gear. The absence of attractive impedance permits huge magnets utilized as a part of MRI (Magnetic Resonance Imaging) hardware to perform better. Composites are utilized as a part of both the hardware lodging and table. Also, the development of the room utilizes composite rebar to strengthen the solid dividers and floors in the healing center [8].
In this chapter, our team will investigate the performance of (polymer/hydroxyapatite) composite for removal of methylene blue as cationic dye from aqueous system.
2. Materials and methods
2.1 Synthesis of composite resins
Polyacrylonitrile co-acrylic acid apatite resins, P(AN-co-AA)-HAP, were synthesized by radical copolymerization in DMF solution in the presence of (BPO) as follows: In three-neck round flask equipped with nitrogen, thermometer, and mechanical shaker, AN and AA (mass ratio of 4:1) were dissolved in the DMF (mass ratio of total monomer to DMF 4:11) solution 1. Different types of as-prepared natural HAP produced from camel bone with appropriate amount were dispersed in DMF and sonicated for 30 min then added to solution 1 in the three-neck flask and stirred under nitrogen purging. The initiator BPO was transferred to the reaction mixture with weight ratio of total monomers of 1:450. The solution was stirred until all substances were completely dispersed and monomers dissolved. After passing nitrogen to the solution for 1 h, the polymerization was performed in an airtight device at 60°C for 3 h till complete polymerization. After complete polymerization, the obtained composite was washed several times with water and acetone to remove the residual monomers and initiators thoroughly. The final co-polymer-HAP composites P(AN-AA)-HAP were dried at 60°C till complete dryness and ground to the specified particle size.
Different types of the as-prepared natural HAP camel bone samples were used as follows:
Resin
HAP preparation temp. oC
HAP preparation gas
HAP content % in the composite
R1
700°C for N2 and 900°C for CO2 with surface area 122.56 m2/g
Passing N2 gas for 2 h (1 h for rising temperature to reach to desired temperature and 1 h for holding) then passing CO2 gas for 1 h
14%
R2
500°C for N2 and 900°C for CO2 was surface area 94.88 m2/g
R3
900°C for N2 and 900°C for CO2 was surface area 124.35 m2/g
2.2 Sorption studies
The sorption experiments were carried out on solutions containing methylene blue dye with the prepared sorbents in batch as well as column techniques.
2.2.1 Batch experiments
Batch experiments were conducted with 100 ml of methylene blue solution of concentration 1 × 10−5 M in 250-ml stoppered bottles containing 0.1 g of the composite material at pH 5.5. The mixture was shaken by a mechanical water shaker thermostated at 25 ± 1°C (except when studying the effect of temperature). The parameters affecting the sorption process were studied by varying any one of the parameters and keeping the other parameters constant. These factors include composite particle size, equilibrium time, dose, temperature, and the initial metal ion concentration. The solid material was separated from solution by centrifuge and the dyes concentration in the solution was determined. Methylene blue was determined spectrophotometrically using UV-visible spectrophotometer.
The amount of dye retained in the solid phase (qe) (mg/g) was calculated using this relation:
qe=vmC0−Cemg/gE1
where v is the volume of aqueous solutions (ml), m is the weight of solid material used (g), and C0and Ce are the initial and equilibrium concentration (M) of MB dye.
The sorption of dye solution was calculated using the relation:
Sorption%=C0−CeC0×100E2
The distribution coefficient (Kd) of the dye between the aqueous phase and the solid phase is calculated from the relation:
Kd=vmC0−CeCeE3
Kd=qeCeE4
2.2.2 Column studies
Column studies were conducted using glass column of dimensions 20 cm length and 1.2 cm of internal diameter and 0.4 g of sorbent of particle size 30 mesh was introduced as slurry in the column. A 1000-ml solution containing 1 × 10−5 M of MB added sample was passed through HAP. All the experiments were carried out at room temperature. The sample solution was collected after different volumes. Amounts of MB in each volume were determined using UV/VIS spectrophotometry. The breakthrough sorption capacity of HAP was obtained in column using the equation:
Qe=Ci−CembvE5
where Ci and Ce denote the initial and equilibrium (at breakthrough) dye concentration (M) respectively. bv was the breakthrough volume of the MB solution in liters, and m was the mass of the adsorbent used (g).
Desorption of solutes from the loaded column was carried out by elution using (H2SO4 + H2O2), HCL, NaOH, CH3COOH, C2O4H2, and C6H8O7. From the start of the experiment, effluent samples at different volumes were collected at the bottom of the column for analysis. The percentage desorption of solutes was obtained in column using the equation:
Desorption%=CeCi×100E6
3. Results and discussions
This chapter is divided into four parts. The first one deals with characterization of the synthesized sorbent materials, R1. The second and third parts are concerned with the removal of MB dye respectively from aqueous solution by the investigated sorbents. Capacities of the sorbent materials for removal of the studied dye were investigated. The fourth part deals with column studies (Figure 1).
Figure 1.
(a) Infrared spectrum of the HAP samples and (b) infrared spectrum of the synthesized R1 and R1/MB.
3.1 Characterization of the sorbent materials
3.1.1 X-ray diffraction (XRD), Fourier transform infrared (FTIR), and scanning electron microscopy (SEM) measurements
The IR-spectra revealed wide bands of H▬O▬H lattice water in the regions 1600–1700 cm−1 and 3200–3600 cm−1 and an [OH]▬ stretching mode band at 3350 cm−1 for HAP at physical activation at 500°C. The bands at 1097 cm−1 and 1029 cm−1 were assigned for (PO4)3−. Also the bands at 960, 603, and 562 cm−1 are due to (PO4)3−. The (PO4)3− vibrational bands depend on the activation temperature. The sharpness of the peaks at 603 cm−1 and 562 cm−1 indicates a well crystallized HAP. Characteristic vibration bands of the C▬O in the carbonate group were observed at 1418–1456 cm−1. New peaks were observed for composite resin (R1) at 2006 cm−1 and peak of phosphate is slightly shifted to 1042, 592, and 560 cm−1, while the loaded resin R1 with MB dye showed a broad peak of the phosphate at 560 cm−1 and the stretching mode of vibration for OH group was observed at 3340 cm−1 as shown in the spectra. As can be seen from the morphologies of particles in the SEM images, there is a distribution of small particles and large agglomerates. These agglomerates are consisted of very fine particles that are welded together and the powders displayed a significant level of agglomeration. Forty-point BET surface area analyses were done to study the effect of polymer on the surface area of the natural hydroxyapatite. The natural HAP surface area was found to be 122.56 m2/g, while composite shaped reaches 218.48 m2/g. The XRD analyses revealed straight base lines and sharp peaks confirming that hydroxyapatite was formed in all samples, and the produced calcium phosphate was well crystallized. On the other hand, Figure 2(a–c) XRD analysis of HAP samples indicates that the samples are in the crystalline phase. In addition, XRD pattern shows a broad reflection peak at the range of 31.7–32.8 of 2 values, which correspond to the characteristic peak of hydroxyapatite. The XRD patterns of polymer/supported HAP composite resins with 14% HAP (R1) show that the characteristic peaks of HAP disappeared after the interaction between the polymer and HAP. This finding explains the interaction of the polymer within the HAP active groups (Figure 3).
Figure 2.
(a) X-ray diffraction of the synthesized HAP, (b) X-ray diffraction of the synthesized R1, and (c) X-ray diffraction of R1 after sorption the of MB.
Figure 3.
SEM micrographs for the natural HAP and prepared resins before and after MB dye loading.
The thermogravimetric analysis (TGA) measurements were performed in flowing nitrogen gas up on the prepared resins R1 as show in Figure 4. The thermal decomposition of the HAP-polymer composites illustrates that up to 350°C, 5 % weight loss occurred followed by three steps up to 800°C. It is clear that the presence of HAP with the polymer increases the thermal stability and delays the polymer thermal decomposition.
Figure 4.
TGA thermogram for R1.
The thermal decomposition of apatite content depends on its hydroxide and phosphate content; both are related to the change in apatite mass upon heating. After 800°C a replacement of ▬OH− occurred, resulting in water evolution. The weight loss after 800°C was attributed to the ▬OH− content [9]. The calcium phosphates containing HPO4 undergo weight loss between 400 and 700°C due to formation of pyrophosphate and evolution of water. It is reported that after 700°C the calcium pyrophosphate reacts with HAP to produce TCP and water.
3.2 Sorption investigations of methylene blue dye
3.2.1 Batch investigations
Batch experiments were carried out to find out the optimum conditions for the removal of MB dye from aqueous solution by the synthesized sorbents. Different parameters affecting the sorption of MB dye were separately studied, such as particle size of sorbent, shaking time, sorbent weight, temperature, and MB dye concentration.
3.2.1.1 Effect of shaking time
The effect of shaking time on the removal of 1 × 10−5 M MB dye from aqueous solution using 0.1 g of each the sorbents used was investigated in the range 1–120 min at 25 ± 1°C. The results illustrated in Figure 5 show an increase in the removal percentage (uptake) of MB dye from aqueous solution with shaking time up to 60 min, which then remains constant with further increase of shaking time. A plateau is seen to be reached for all curves representing that the adsorbent is saturated at this time. Therefore, equilibrium time of 60 min was chosen in the subsequent studies.
Figure 5.
Effect of shaking time on the adsorption of MB from aqueous solutions using apatite resins.
3.2.1.2 Effect of particle size
The effect of particle size on the removal efficiency of 1 × 10−5M MB dye from aqueous solution using 0.1 g of selected sorbents was studied at different sorbent particle sizes in the range (0.063–4) mesh at 25 ± 1°C, the removal of MB dye was found to increase from 22.39 to 82.5% as the sorbent particle size increased from (4–0.063) mesh, see Figure 6. The higher sorption with smaller sorbent particles may be attributed to the fact that smaller particles provide a larger surface area. Hence, selected sorbents with particle size of 0.063 mesh has been chosen for further experiments.
Figure 6.
Effect of particle size on the adsorption of MB from aqueous solutions onto apatite resins.
3.2.1.3 Effect of sorbent weight
The results for the removal of 1 × 10−5 M MB dye from aqueous solution using the investigated sorbents with respect to sorbents’ weight are shown in Figure 7 in the range 0.01–0.3 g/50 ml of 1 × 10−5 M MB dye solution at 25 ± 1°C. The results obtained show that when increasing sorbents’ weight from 0.01 to 0.3 g, the removal of MB dye from aqueous solution increases and remains constant with further increase of sorbents’ weight up to 0.2 g. This can be due to the availability of more surface functional groups and surface area at higher sorbent weight. The removal percentage of MB dye becomes constant from 0.2 to 0.3 g. This may be referred to the aggregation of the sorbent particles at high concentration of MB dye. Such aggregation would lead to decrease in the total surface area available for metal ion sorption.
Figure 7.
Effect of resin dose on the adsorption of MB from aqueous solutions onto apatite resins.
3.2.2 Kinetics of adsorption
The amount adsorbed of dye onto the polymeric resin was studied with time for estimating the adsorption mechanism. The adsorption of dye with time shows that mixing period of 10 min is optimum for attaining the equilibrium with respect to R1and R2, while attaining the equilibrium with R3 takes 60 min. These findings reflect a fast kinetic for adsorption of MB onto the prepared resins, especially R1 and R2.
Different kinetic models were applied on the obtained results and the kinetic parameters were determined. The kinetic models correlate the amount adsorbed of dye with time. Lagergren presented the following equation for pseudo-first-order reactions [10]:
dqtdt=k1qe−qtE7
where qe and qt are the dye concentration in solid phase at equilibrium and at time t, respectively, and k1 is the model constant (min−1). The linear form of the above equation was obtained by integration at the borders (qt = 0 to qt = qt and t = 0 to t = t) as:
logqe−qt=logqe−k1t2.303E8
The rate constant k1 was determined from the plot of log(qe − qt) with t as shown in Figure 8 while the value of qe was determined from the intercept. The model variables with the coefficient are given in Table 1.
Figure 8.
Pseudo-first-order model kinetic plot for the sorption of MB onto the synthesized sorbents R1.
Adsorption system
Kinetic model
Parameters
R2
SD
MB-R1
Pseudo first order
k1 = 1.718 qe = 0.607
0.994
0.0163
Pseudo second order
K2 = 2.18 qe = 2.73
0.987
0.133
Elovich
β = 5.98 α = 8.72
0.978
0.0376
Intra-particle
kid = 3.168 C = 2.93
0.991
0.834
Table 1.
Kinetic models’ variables for adsorption of MB onto R1.
The plots in the figures above show linear fit with correlation coefficient (R) of 0.994 for R1. The values of calculated adsorption capacity qe and the linear regression coefficient clarify that the studied kinetic model kinetic model could not fit with the experimental results for adsorption of MB onto R1.
Second-order kinetic model, which describes the chemical adsorption is given by [11].
dqtdt=k2qe−qt2E9
where k2 is the model constant (g/mg min). The above equation could be integrated at the border (qt = 0 to qt = qt at t = 0 to t = t) to give:
tqt=1k2qe2+tqeE10
The model variables were calculated from the plot of t/qt with t as shown in Figure 9. The plot showed a linear relation, and the model parameters with the correlation coefficient R2 are given in Table 1.
Figure 9.
Pseudo-second-order model kinetic plot for the sorption of MB onto the synthesized sorbents R1.
The results of the studied kinetic model clarify that the experimental results for adsorption of MB onto R1, R2, and R3 could be described by kinetic model supporting chemical adsorption. The MB sorption could be represented favorably on the composite resins by the pseudo-second order kinetic model. This finding refers to the participation of chemical adsorption within the adsorption mechanism for MB onto R1.
Elovich kinetic model was applied upon the results to explain mainly the chemisorptions onto heterogeneous solid surfaces. The linearized form of Elovich model equation is given in [12].
qt=1βlnαβ+1βlogtE11
where α and β are model parameters representing the starting sorption rate (g mg−1 min−2) and the leaching constant (mg g−1 min−1), correspondingly. The model parameters were calculated from the linear fit of qt vs. log(t) plot, shown in Figure 10, and are presented in Table 1.
Figure 10.
Elovich model kinetic plot for the sorption of MB onto the synthesized sorbents R1.
The value of the Elovich constant (α and β) for the adsorption of MB on R1 predicate the effect of adsorbent dose and the possibility of performing sorption-desorption regeneration cycles of adsorbent. The value of correlation coefficient (R) reflects a poor fit of Elovich model with the experimental results. It could be inferred that both chemical and surface adsorption mechanisms are participating in the studied systems.
Intraparticle diffusion model was studied to explain the influence of transfer of dye from solution to solid surface of adsorbent on the reaction. The adsorption reaction could be affected by film diffusion, pore diffusion, surface diffusion, and/or adsorption on pore surface. The studied batch experiment was performed with shaking; therefore, the transfer of adsorbate particles could be described by diffusion coefficient that gives a considerable fitting with the experimental results. Weber model could be studied to explain the intraparticle diffusion’s influence on the reaction by the following equation [13]:
qt=kidt0.5+CE12
where kid is the Webber model constant (mg g−1 min−0.5) and C is a constant (mg g−1) connected to the depth of the boundary layer, reflecting the boundary layer effect.
If the adsorption takes place within multilayer adsorbent, the adsorbate particles have to spread within the interior pores of solid materials. The model parameters were obtained from the plot of qt vs. t1/2, shown in Figure 11, and are presented in Table 1.
Figure 11.
Intraparticle model kinetic plot for the sorption of MB onto the synthesized sorbent R1.
The results in Figure 11 show two linear regions referring to the participation of at least two steps in the reaction. The linearity in the first region refers to a diffusion of dye into macro-pores of adsorbent, while the second linear region shows that the adsorbate particles diffuse within a micro-pore of adsorbent. The third region refers to mesoporous of adsorbent. The data obtained show that the synthesized sorbent has different pores.
The results in the figures reflect a variation of particle migration rate between different stages of sorption. The deviation of straight lines from the origin (when extrapolated), reflects that the diffusion within pore is not only the rate determining step. The model variables for adsorption of MB using both R1, were given in Table 1. These results indicate that Webber diffusion model could not be considered as the controlling mechanism in the adsorption reaction.
3.2.3 Adsorption isotherm
The adsorption of MB onto R1 was studied at different initial dye concentrations (within the range 1–50 mg/L). The removal percentage and the adsorbed amount of MB are presented against the starting dye concentration in Figure 12. The results show that the amount of MB retained on the solid adsorbent increases with increasing dye concentration.
Figure 12.
Langmuir-1 isotherm plot for the sorption of MB onto the synthesized sorbent R1.
Different isotherm models were studied for describing the adsorption mechanism controlling the reaction. Langmuir isotherm model [13] was studied for adsorption of MB onto R1, which is expressed as:
Ceqe=1KL+CeqmaxE13
where Ce is the dye concentration in solution after experiment (mg/L), qe is dye concentration on the solid resin (mg/g), and qmax and KL are model parameters connected to maximum adsorbed amount (mg/g) and adsorption energy, correspondingly. A plot of Ce vs. Ce/qe is presented in Figure 12 and the model variables were determined from the plot and are given with coefficient R in Table 2.
Model
Resin
Parameter
R
SD
Langmuir
R1
qmax = 25.77 KL = 16.18
0.975
0.0418
Freundlich
R1
1/n = 0.617 Kf = 6.102
0.988
0.104
Dubinin-Radushkevich
R1
β = −0.093 qmax = 10.39 ES = 2.318
0.979
0.359
Table 2.
Adsorption isotherm models’ parameters for MB-R systems.
R values for the adsorption systems were found to be 0.975, indicating less compatibility with Langmuir isotherm. This finding prove that monolayer chemical adsorption on the homogeneous surface is not participate in the adsorption process.
Freundlich isotherm model [13] was applied on the experimental results, which is described by the equation:
logqe=logkf+1nlogCeE14
where kf (mg/g) and n are model constants, indicating the adsorption capacity and favorability nature of the adsorption process. Freundlich model constants were determined from the linear fit of log qe vs. log Ce plot in Figure 13 and are given with the correlation coefficient in Table 2.
Figure 13.
Freundlich model isotherm plot for the sorption of MB onto the synthesized sorbent R1.
The values of R of Freundlich plots for MB-R system showed bad fit of the experimental results with Freundlich isotherm model.
Dubinin-Radushkevich (D-R) adsorption isotherm model was studied; it describes adsorption onto porous solid surfaces, and is described by the following equation [13]:
lnqe=lnqmax−βε2E15
where β is the D-R model constant (mol2/kJ2), qmax is the constant referring to the maximum adsorbed amount (mg/g), and ε is Polanyi potential (ε = RTln(1 + 1/Ce)). The D-R model constants were obtained from the linear fit of the plot of ln qe vs. ε2 (Figure 14) and are given with correlation coefficient in Table 2. The adsorption free energy (ES) is calculated as:
Figure 14.
Dubinin-Radushkevich model isotherm plot for the sorption of MB onto the synthesized sorbent R1.
ES=−2β−1/2E16
The calculated mean adsorption free energy (ES) from D-R model for adsorption of MB using R1 was found to be 8.03 kJ/mol. These values reflect that physical adsorption is a participating mechanism.
3.2.4 Effect of temperature
The effect of temperature on the removal efficiency of 1 × 10−5 M MB dye from aqueous solution using 0.1 g of each investigated sorbents was studied at different temperatures ranging from 25 to 50°C. It is observed from the results that the removal of MB dye increases slightly with increasing temperature, see Figure 15. This behavior indicates that the sorption process of MB dye from aqueous solution using all selected sorbents is an endothermic process. The increase in the sorption efficiency of MB dye by the sorbents used at high temperature may be attributed to the increase of MB dye mobility and decrease of the retarding forces acting on the diffusing dye.
Figure 15.
Effect of temperature on the adsorption of MB from aqueous solution onto R1.
3.2.5 Adsorption thermodynamics
The thermodynamic parameters corresponding to dye sorption on the prepared resins were assessed using Van’t Hoff equation [14] (Table 3).
Adsorption system
Temperature (°K)
ΔH° (kJ mol −1)
ΔG°(kJ mol−1)
ΔS° (J K−1 mol−1)
SD
R1-MB
298
44.991
6.961
172.81
0.257
313
−7.850
323
−11.626
Table 3.
Thermodynamic parameters for sorption of MB onto R1.
logKd=∆S°2.303R−∆H°2.303RTE17
where kd is the distribution coefficient of the solute ions, ΔS° is the entropy change (J mol−1 K−1), R is the ideal gas constant (8.314 J mol−1 K−1), and T is the absolute temperature. A plot of log kd vs. 1/T was constructed as shown in Figure 16 from which the slope of the straight line equal −(ΔH°)/2.303; consequently, the value of apparent enthalpy change (ΔH°) for the overall system was calculated. The values of other thermodynamic parameters are calculated at different temperatures, using the following equations:
Figure 16.
Effect of temperature on the sorption of MB by the synthesized sorbent R1.
ΔGo=−2.303RTlogkdE18
ΔGo=ΔHo−TΔS°E19
3.2.6 Column studies
Sorption dynamics of MB in a fixed bed flow through a sorption column is eventually conducted for multiple reuse of the sorbent. Column sorption studies of MB on the R1 beads at room temperature were investigated using aqueous solution of 1 × 10−5 M influent concentrations (Ci). Experimental breakthrough curve was studied using flow rate 0.2 ml/min. It is obtained by plotting the ratios of effluent concentration to initial concentration versus the volume of the effluent, see Figure 17. It was observed that the column gets saturated after passing 1 l of MB solution. The estimated breakthrough sorption capacity (Qe) was 79.65 mg/g for MB.
Figure 17.
Breakthrough curve of MB dye with R1.
Once the column reached exhaustion, efficient elution of adsorbed solute from resin in column is essential to ensure the recovery of dye as well as the reuse of resin for repeated adsorption/desorption cycles. Desorption of MB from R1 was studied using different concentrations of sulfuric acid and hydrogen peroxide.
Desorption curve shown in Figure 18 was obtained by plotting the effluent concentration (Ce) versus elution volume from the column at a flow rate of 0.2 ml/min. The result obtained shows that 93.79% recovery was achieved for MB by 1:1 W/W H2SO4 and H2O2.
Figure 18.
Dynamic desorption curve of MB from R1 by H2O2 and H2SO4.
4. Conclusions
In the current study, the removal of MB dye from aqueous solution was investigated by three prepared composite resins and the following conclusions can be drawn:
The prepared composite resins can potentially be applied for removal of MB dye from aqueous solutions.
The adsorption mechanism was suggested based on applying different isotherm models and kinetic models.
From the data obtained for the uptake of MB dye by practical experiment, good match was found with calculated values obtained from isotherm models.
Working on the composite is more advanced than working on HAP alone because:
The spontaneous reaction was carried out at low temperatures while HAP was carried out with spontaneous reaction at high temperatures.
The surface area and mechanical strength for composite are higher than the surface area and mechanical strength of HAP alone.
Different inorganic and organic solutions were studied for regeneration of composite.
Aqueous solution containing mixture of sulfuric acid and hydrogen peroxide of 1:1 w/w showed the maximum release for the adsorbed dyes with 87.46% for methylene blue dye.
Acknowledgments
The authors extend their appreciation to the Research and Development Grants Program for National Research Institutions and Centers (GRANTS) at King Abdulaziz City for Science and Technology (KACST) for supporting this work through research groups program under grant number 1-18-01-010-0002.
\n',keywords:"blue dyes, composite polymeric-apatite resins, cationic dyes, environmental purification",chapterPDFUrl:"https://cdn.intechopen.com/pdfs/71867.pdf",chapterXML:"https://mts.intechopen.com/source/xml/71867.xml",downloadPdfUrl:"/chapter/pdf-download/71867",previewPdfUrl:"/chapter/pdf-preview/71867",totalDownloads:675,totalViews:0,totalCrossrefCites:1,dateSubmitted:"November 11th 2019",dateReviewed:"March 9th 2020",datePrePublished:"April 22nd 2020",datePublished:"September 30th 2020",dateFinished:"April 21st 2020",readingETA:"0",abstract:"Removal of cationic dyes from industrial effluents is still a big and challenging subject in the field of environmental purification. Millions of tons of cationic dyes are consumed by the textile, rubber, paper, and plastic industries. These dyes have thousands of different chemical structures. Most of them have special properties, such as high hydrophilicity and stability to light or heat. Adsorption is commonly used as a technique for removing dyes. Removal of cationic dyes by adsorption is a promising approach because of its low performance cost and easy technical access. The amount adsorbed of the dye onto the polymeric resin is studied with time for estimating the adsorption mechanism. The adsorption of dye with time shows that mixing period of 10 min is optimum for attaining equilibrium with respect to R1 and R2, while attaining equilibrium with R3 takes 60 min. This findings represent a rapid kinetic for adsorption of MB, particularly R1, on the prepared resins. Different kinetic models were applied on the obtained results and the kinetic parameters were determined. The kinetic models correlate the amount adsorbed of dye with time. The values of calculated adsorption capacity qe and the linear regression coefficient clarify that the studied kinetic model could not fit with the experimental results for adsorption of MB onto R1, R2, and R3. The results of the studied kinetic model clarify that the experimental results for adsorption of MB onto R1, R2, and R3 could be described by kinetic model supporting chemical adsorption. The sorption of MB could be favorably described by the pseudo-second-order kinetic model onto the composite resins. This finding refers to the participation of chemical adsorption within the adsorption mechanism for MB onto R1, R2, and R3.",reviewType:"peer-reviewed",bibtexUrl:"/chapter/bibtex/71867",risUrl:"/chapter/ris/71867",signatures:"Nasser S. Awwad, Adel A. El-Zahhar and Jamila A.M. Alasmary",book:{id:"9203",type:"book",title:"Chemistry and Technology of Natural and Synthetic Dyes and Pigments",subtitle:null,fullTitle:"Chemistry and Technology of Natural and Synthetic Dyes and Pigments",slug:"chemistry-and-technology-of-natural-and-synthetic-dyes-and-pigments",publishedDate:"September 30th 2020",bookSignature:"Ashis Kumar Samanta, Nasser S. Awwad and Hamed Majdooa Algarni",coverURL:"https://cdn.intechopen.com/books/images_new/9203.jpg",licenceType:"CC BY 3.0",editedByType:"Edited by",isbn:"978-1-78985-998-0",printIsbn:"978-1-78985-997-3",pdfIsbn:"978-1-83968-758-7",isAvailableForWebshopOrdering:!0,editors:[{id:"42763",title:"Prof.",name:"Ashis Kumar",middleName:null,surname:"Samanta",slug:"ashis-kumar-samanta",fullName:"Ashis Kumar Samanta"}],productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"}},authors:[{id:"145209",title:"Prof.",name:"Nasser",middleName:"S",surname:"Awwad",fullName:"Nasser Awwad",slug:"nasser-awwad",email:"nsawwad20@yahoo.com",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/145209/images/system/145209.jpg",institution:{name:"King Khalid University",institutionURL:null,country:{name:"Saudi Arabia"}}},{id:"319709",title:"Dr.",name:"Adel A.",middleName:null,surname:"El-Zahhar",fullName:"Adel A. El-Zahhar",slug:"adel-a.-el-zahhar",email:"adelelzahhar@yahoo.com",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:{name:"King Khalid University",institutionURL:null,country:{name:"Saudi Arabia"}}},{id:"319710",title:"Dr.",name:"Jamila A.M.",middleName:null,surname:"Alasmary",fullName:"Jamila A.M. Alasmary",slug:"jamila-a.m.-alasmary",email:"jameelah03@gmail.com",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:{name:"King Khalid University",institutionURL:null,country:{name:"Saudi Arabia"}}}],sections:[{id:"sec_1",title:"1. Introduction",level:"1"},{id:"sec_2",title:"2. Materials and methods",level:"1"},{id:"sec_2_2",title:"2.1 Synthesis of composite resins",level:"2"},{id:"sec_3_2",title:"2.2 Sorption studies",level:"2"},{id:"sec_3_3",title:"2.2.1 Batch experiments",level:"3"},{id:"sec_4_3",title:"2.2.2 Column studies",level:"3"},{id:"sec_7",title:"3. Results and discussions",level:"1"},{id:"sec_7_2",title:"3.1 Characterization of the sorbent materials",level:"2"},{id:"sec_7_3",title:"3.1.1 X-ray diffraction (XRD), Fourier transform infrared (FTIR), and scanning electron microscopy (SEM) measurements",level:"3"},{id:"sec_8_3",title:"3.1.2 Thermogravimetric analysis (TGA) measurements",level:"3"},{id:"sec_10_2",title:"3.2 Sorption investigations of methylene blue dye",level:"2"},{id:"sec_10_3",title:"3.2.1 Batch investigations",level:"3"},{id:"sec_10_4",title:"3.2.1.1 Effect of shaking time",level:"4"},{id:"sec_11_4",title:"3.2.1.2 Effect of particle size",level:"4"},{id:"sec_12_4",title:"3.2.1.3 Effect of sorbent weight",level:"4"},{id:"sec_14_3",title:"Table 1.",level:"3"},{id:"sec_15_3",title:"Table 2.",level:"3"},{id:"sec_15_4",title:"3.2.4 Effect of temperature",level:"4"},{id:"sec_17_3",title:"Table 3.",level:"3"},{id:"sec_18_3",title:"3.2.6 Column studies",level:"3"},{id:"sec_21",title:"4. Conclusions",level:"1"},{id:"sec_22",title:"Acknowledgments",level:"1"}],chapterReferences:[{id:"B1",body:'Zaharia C, Suteu C, Muresan A. Proceedings of International Conference on Environmental Engineering and Management. 2011;4:121'},{id:"B2",body:'Zaharia C, Suteu D, Muresan A, Muresan R. Environmental Engineering and Management Journal. 2009;6:1359'},{id:"B3",body:'Börnick H, Schmidt TC. J. Anal. Environ. 2006;9:181'},{id:"B4",body:'Doulati AF, Badii K, Yousefi Limaee N, Mahmoodi NM, Arami M, Shafaei SZ, et al. Dyes and Pigments. 2007;73:178'},{id:"B5",body:'Hassan SSM, Awwad NS, Aboterika AHA. Journal of Hazardous Materials. 2008;154:992-997'},{id:"B6",body:'Barakat NAM, Khila MS, Omrand AM, Sheikhd FA, Kima HY. Journal of Materials Processing Technology. 2009;209(2):3408'},{id:"B7",body:'El-Zahhar AA, Awwad NS. Journal of Environmental Chemical Engineering. 2016;4:633-638'},{id:"B8",body:'Awwad NS, Alshahrani AM, Saleh KA, Hamdy MS. Molecules. 2017, 1947;22(12). DOI: 10.3390/molecules22121947'},{id:"B9",body:'TÕnsuaadu K, Agris Gross K, Plūduma L, Veiderma M. Journal of Thermal Analysis and Calorimetry. 2012;110:647'},{id:"B10",body:'Lagergren S. Kungliga Svenska Ventenskapsakademiens Handlingar. 1898;24:1'},{id:"B11",body:'Ho YS, McKay E. Canadian Journal of Chemical Engineering. 1998;76:822'},{id:"B12",body:'Ho YS, McKay G. Science and Technology. 2002;20:797'},{id:"B13",body:'Dada AO, Olalekan AP, Olatunya AM, DADA O. Journal of Applied Chemistry. 2012;3:38'},{id:"B14",body:'El-Zahhar AA, Abdel-Aziz HM, Siyam T. Journal of Radioanalytical and Nuclear Chemistry. 2006;267(3):657'}],footnotes:[],contributors:[{corresp:"yes",contributorFullName:"Nasser S. Awwad",address:"aawwad@kku.edu.sa",affiliation:'
Faculty of Science, Department of Chemistry, King Khalid University, Saudi Arabia
'},{corresp:null,contributorFullName:"Adel A. El-Zahhar",address:null,affiliation:'
Faculty of Science, Department of Chemistry, King Khalid University, Saudi Arabia
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He has both an MS and Ph.D. in Biomedical Engineering. He was previously a research scientist at the University of California Los Angeles (UCLA) and visiting professor and researcher at the University of North Dakota. He is currently working in artificial intelligence and its applications in medical signal processing. In addition, he is using digital signal processing in medical imaging and speech processing. Dr. Asadpour has developed brain-computer interfacing algorithms and has published books, book chapters, and several journal and conference papers in this field and other areas of intelligent signal processing. He has also designed medical devices, including a laser Doppler monitoring system.",institutionString:"Kaiser Permanente Southern California",institution:null},{id:"169608",title:"Prof.",name:"Marian",middleName:null,surname:"Găiceanu",slug:"marian-gaiceanu",fullName:"Marian Găiceanu",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/169608/images/system/169608.png",biography:"Prof. Dr. Marian Gaiceanu graduated from the Naval and Electrical Engineering Faculty, Dunarea de Jos University of Galati, Romania, in 1997. He received a Ph.D. (Magna Cum Laude) in Electrical Engineering in 2002. Since 2017, Dr. Gaiceanu has been a Ph.D. supervisor for students in Electrical Engineering. He has been employed at Dunarea de Jos University of Galati since 1996, where he is currently a professor. Dr. Gaiceanu is a member of the National Council for Attesting Titles, Diplomas and Certificates, an expert of the Executive Agency for Higher Education, Research Funding, and a member of the Senate of the Dunarea de Jos University of Galati. He has been the head of the Integrated Energy Conversion Systems and Advanced Control of Complex Processes Research Center, Romania, since 2016. He has conducted several projects in power converter systems for electrical drives, power quality, PEM and SOFC fuel cell power converters for utilities, electric vehicles, and marine applications with the Department of Regulation and Control, SIEI S.pA. (2002–2004) and the Polytechnic University of Turin, Italy (2002–2004, 2006–2007). He is a member of the Institute of Electrical and Electronics Engineers (IEEE) and cofounder-member of the IEEE Power Electronics Romanian Chapter. He is a guest editor at Energies and an academic book editor for IntechOpen. He is also a member of the editorial boards of the Journal of Electrical Engineering, Electronics, Control and Computer Science and Sustainability. Dr. Gaiceanu has been General Chairman of the IEEE International Symposium on Electrical and Electronics Engineering in the last six editions.",institutionString:'"Dunarea de Jos" University of Galati',institution:{name:'"Dunarea de Jos" University of Galati',country:{name:"Romania"}}},{id:"4519",title:"Prof.",name:"Jaydip",middleName:null,surname:"Sen",slug:"jaydip-sen",fullName:"Jaydip Sen",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/4519/images/system/4519.jpeg",biography:"Jaydip Sen is associated with Praxis Business School, Kolkata, India, as a professor in the Department of Data Science. His research areas include security and privacy issues in computing and communication, intrusion detection systems, machine learning, deep learning, and artificial intelligence in the financial domain. He has more than 200 publications in reputed international journals, refereed conference proceedings, and 20 book chapters in books published by internationally renowned publishing houses, such as Springer, CRC press, IGI Global, etc. Currently, he is serving on the editorial board of the prestigious journal Frontiers in Communications and Networks and in the technical program committees of a number of high-ranked international conferences organized by the IEEE, USA, and the ACM, USA. He has been listed among the top 2% of scientists in the world for the last three consecutive years, 2019 to 2021 as per studies conducted by the Stanford University, USA.",institutionString:"Praxis Business School",institution:null},{id:"320071",title:"Dr.",name:"Sidra",middleName:null,surname:"Mehtab",slug:"sidra-mehtab",fullName:"Sidra Mehtab",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y00002v6KHoQAM/Profile_Picture_1584512086360",biography:"Sidra Mehtab has completed her BS with honors in Physics from Calcutta University, India in 2018. She has done MS in Data Science and Analytics from Maulana Abul Kalam Azad University of Technology (MAKAUT), Kolkata, India in 2020. Her research areas include Econometrics, Time Series Analysis, Machine Learning, Deep Learning, Artificial Intelligence, and Computer and Network Security with a particular focus on Cyber Security Analytics. Ms. Mehtab has published seven papers in international conferences and one of her papers has been accepted for publication in a reputable international journal. She has won the best paper awards in two prestigious international conferences – BAICONF 2019, and ICADCML 2021, organized in the Indian Institute of Management, Bangalore, India in December 2019, and SOA University, Bhubaneswar, India in January 2021. Besides, Ms. Mehtab has also published two book chapters in two books. Seven of her book chapters will be published in a volume shortly in 2021 by Cambridge Scholars’ Press, UK. Currently, she is working as the joint editor of two edited volumes on Time Series Analysis and Forecasting to be published in the first half of 2021 by an international house. Currently, she is working as a Data Scientist with an MNC in Delhi, India.",institutionString:"NSHM College of Management and Technology",institution:{name:"Association for Computing Machinery",country:{name:"United States of America"}}},{id:"226240",title:"Dr.",name:"Andri Irfan",middleName:null,surname:"Rifai",slug:"andri-irfan-rifai",fullName:"Andri Irfan Rifai",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/226240/images/7412_n.jpg",biography:"Andri IRFAN is a Senior Lecturer of Civil Engineering and Planning. He completed the PhD at the Universitas Indonesia & Universidade do Minho with Sandwich Program Scholarship from the Directorate General of Higher Education and LPDP scholarship. He has been teaching for more than 19 years and much active to applied his knowledge in the project construction in Indonesia. His research interest ranges from pavement management system to advanced data mining techniques for transportation engineering. He has published more than 50 papers in journals and 2 books.",institutionString:null,institution:{name:"Universitas Internasional Batam",country:{name:"Indonesia"}}},{id:"314576",title:"Dr.",name:"Ibai",middleName:null,surname:"Laña",slug:"ibai-lana",fullName:"Ibai Laña",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/314576/images/system/314576.jpg",biography:"Dr. Ibai Laña works at TECNALIA as a data analyst. He received his Ph.D. in Artificial Intelligence from the University of the Basque Country (UPV/EHU), Spain, in 2018. He is currently a senior researcher at TECNALIA. His research interests fall within the intersection of intelligent transportation systems, machine learning, traffic data analysis, and data science. He has dealt with urban traffic forecasting problems, applying machine learning models and evolutionary algorithms. He has experience in origin-destination matrix estimation or point of interest and trajectory detection. Working with large volumes of data has given him a good command of big data processing tools and NoSQL databases. He has also been a visiting scholar at the Knowledge Engineering and Discovery Research Institute, Auckland University of Technology.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"314575",title:"Dr.",name:"Jesus",middleName:null,surname:"L. Lobo",slug:"jesus-l.-lobo",fullName:"Jesus L. Lobo",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/314575/images/system/314575.png",biography:"Dr. Jesús López is currently based in Bilbao (Spain) working at TECNALIA as Artificial Intelligence Research Scientist. In most cases, a project idea or a new research line needs to be investigated to see if it is good enough to take into production or to focus on it. That is exactly what he does, diving into Machine Learning algorithms and technologies to help TECNALIA to decide whether something is great in theory or will actually impact on the product or processes of its projects. So, he is expert at framing experiments, developing hypotheses, and proving whether they’re true or not, in order to investigate fundamental problems with a longer time horizon. He is also able to design and develop PoCs and system prototypes in simulation. He has participated in several national and internacional R&D projects.\n\nAs another relevant part of his everyday research work, he usually publishes his findings in reputed scientific refereed journals and international conferences, occasionally acting as reviewer and Programme Commitee member. Concretely, since 2018 he has published 9 JCR (8 Q1) journal papers, 9 conference papers (e.g. ECML PKDD 2021), and he has co-edited a book. He is also active in popular science writing data science stories for reputed blogs (KDNuggets, TowardsDataScience, Naukas). Besides, he has recently embarked on mentoring programmes as mentor, and has also worked as data science trainer.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"103779",title:"Prof.",name:"Yalcin",middleName:null,surname:"Isler",slug:"yalcin-isler",fullName:"Yalcin Isler",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRyQ8QAK/Profile_Picture_1628834958734",biography:"Yalcin Isler (1971 - Burdur / Turkey) received the B.Sc. degree in the Department of Electrical and Electronics Engineering from Anadolu University, Eskisehir, Turkey, in 1993, the M.Sc. degree from the Department of Electronics and Communication Engineering, Suleyman Demirel University, Isparta, Turkey, in 1996, the Ph.D. degree from the Department of Electrical and Electronics Engineering, Dokuz Eylul University, Izmir, Turkey, in 2009, and the Competence of Associate Professorship from the Turkish Interuniversity Council in 2019.\n\nHe was Lecturer at Burdur Vocational School in Suleyman Demirel University (1993-2000, Burdur / Turkey), Software Engineer (2000-2002, Izmir / Turkey), Research Assistant in Bulent Ecevit University (2002-2003, Zonguldak / Turkey), Research Assistant in Dokuz Eylul University (2003-2010, Izmir / Turkey), Assistant Professor at the Department of Electrical and Electronics Engineering in Bulent Ecevit University (2010-2012, Zonguldak / Turkey), Assistant Professor at the Department of Biomedical Engineering in Izmir Katip Celebi University (2012-2019, Izmir / Turkey). He is an Associate Professor at the Department of Biomedical Engineering at Izmir Katip Celebi University, Izmir / Turkey, since 2019. In addition to academics, he has also founded Islerya Medical and Information Technologies Company, Izmir / Turkey, since 2017.\n\nHis main research interests cover biomedical signal processing, pattern recognition, medical device design, programming, and embedded systems. He has many scientific papers and participated in several projects in these study fields. He was an IEEE Student Member (2009-2011) and IEEE Member (2011-2014) and has been IEEE Senior Member since 2014.",institutionString:null,institution:{name:"Izmir Kâtip Çelebi University",country:{name:"Turkey"}}},{id:"339677",title:"Dr.",name:"Mrinmoy",middleName:null,surname:"Roy",slug:"mrinmoy-roy",fullName:"Mrinmoy Roy",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/339677/images/16768_n.jpg",biography:"An accomplished Sales & Marketing professional with 12 years of cross-functional experience in well-known organisations such as CIPLA, LUPIN, GLENMARK, ASTRAZENECA across different segment of Sales & Marketing, International Business, Institutional Business, Product Management, Strategic Marketing of HIV, Oncology, Derma, Respiratory, Anti-Diabetic, Nutraceutical & Stomatological Product Portfolio and Generic as well as Chronic Critical Care Portfolio. A First Class MBA in International Business & Strategic Marketing, B.Pharm, D.Pharm, Google Certified Digital Marketing Professional. Qualified PhD Candidate in Operations and Management with special focus on Artificial Intelligence and Machine Learning adoption, analysis and use in Healthcare, Hospital & Pharma Domain. Seasoned with diverse therapy area of Pharmaceutical Sales & Marketing ranging from generating revenue through generating prescriptions, launching new products, and making them big brands with continuous strategy execution at the Physician and Patients level. Moved from Sales to Marketing and Business Development for 3.5 years in South East Asian Market operating from Manila, Philippines. Came back to India and handled and developed Brands such as Gluconorm, Lupisulin, Supracal, Absolut Woman, Hemozink, Fabiflu (For COVID 19), and many more. In my previous assignment I used to develop and execute strategies on Sales & Marketing, Commercialization & Business Development for Institution and Corporate Hospital Business portfolio of Oncology Therapy Area for AstraZeneca Pharma India Ltd. Being a Research Scholar and Student of ‘Operations Research & Management: Artificial Intelligence’ I published several pioneer research papers and book chapters on the same in Internationally reputed journals and Books indexed in Scopus, Springer and Ei Compendex, Google Scholar etc. Currently, I am launching PGDM Pharmaceutical Management Program in IIHMR Bangalore and spearheading the course curriculum and structure of the same. I am interested in Collaboration for Healthcare Innovation, Pharma AI Innovation, Future trend in Marketing and Management with incubation on Healthcare, Healthcare IT startups, AI-ML Modelling and Healthcare Algorithm based training module development. I am also an affiliated member of the Institute of Management Consultant of India, looking forward to Healthcare, Healthcare IT and Innovation, Pharma and Hospital Management Consulting works.",institutionString:null,institution:{name:"Lovely Professional University",country:{name:"India"}}},{id:"310576",title:"Prof.",name:"Erick Giovani",middleName:null,surname:"Sperandio Nascimento",slug:"erick-giovani-sperandio-nascimento",fullName:"Erick Giovani Sperandio Nascimento",position:null,profilePictureURL:"https://intech-files.s3.amazonaws.com/0033Y00002pDKxDQAW/ProfilePicture%202022-06-20%2019%3A57%3A24.788",biography:"Prof. Erick Sperandio is the Lead Researcher and professor of Artificial Intelligence (AI) at SENAI CIMATEC, Bahia, Brazil, also working with Computational Modeling (CM) and HPC. He holds a PhD in Environmental Engineering in the area of Atmospheric Computational Modeling, a Master in Informatics in the field of Computational Intelligence and Graduated in Computer Science from UFES. He currently coordinates, leads and participates in R&D projects in the areas of AI, computational modeling and supercomputing applied to different areas such as Oil and Gas, Health, Advanced Manufacturing, Renewable Energies and Atmospheric Sciences, advising undergraduate, master's and doctoral students. He is the Lead Researcher at SENAI CIMATEC's Reference Center on Artificial Intelligence. In addition, he is a Certified Instructor and University Ambassador of the NVIDIA Deep Learning Institute (DLI) in the areas of Deep Learning, Computer Vision, Natural Language Processing and Recommender Systems, and Principal Investigator of the NVIDIA/CIMATEC AI Joint Lab, the first in Latin America within the NVIDIA AI Technology Center (NVAITC) worldwide program. He also works as a researcher at the Supercomputing Center for Industrial Innovation (CS2i) and at the SENAI Institute of Innovation for Automation (ISI Automação), both from SENAI CIMATEC. He is a member and vice-coordinator of the Basic Board of Scientific-Technological Advice and Evaluation, in the area of Innovation, of the Foundation for Research Support of the State of Bahia (FAPESB). He serves as Technology Transfer Coordinator and one of the Principal Investigators at the National Applied Research Center in Artificial Intelligence (CPA-IA) of SENAI CIMATEC, focusing on Industry, being one of the six CPA-IA in Brazil approved by MCTI / FAPESP / CGI.br. He also participates as one of the representatives of Brazil in the BRICS Innovation Collaboration Working Group on HPC, ICT and AI. He is the coordinator of the Work Group of the Axis 5 - Workforce and Training - of the Brazilian Strategy for Artificial Intelligence (EBIA), and member of the MCTI/EMBRAPII AI Innovation Network Training Committee. He is the coordinator, by SENAI CIMATEC, of the Artificial Intelligence Reference Network of the State of Bahia (REDE BAH.IA). He leads the working group of experts representing Brazil in the Global Partnership on Artificial Intelligence (GPAI), on the theme \"AI and the Pandemic Response\".",institutionString:"Manufacturing and Technology Integrated Campus – SENAI CIMATEC",institution:null},{id:"1063",title:"Prof.",name:"Constantin",middleName:null,surname:"Volosencu",slug:"constantin-volosencu",fullName:"Constantin Volosencu",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/1063/images/system/1063.png",biography:"Prof. Dr. Constantin Voloşencu graduated as an engineer from\nPolitehnica University of Timișoara, Romania, where he also\nobtained a doctorate degree. He is currently a full professor in\nthe Department of Automation and Applied Informatics at the\nsame university. Dr. Voloşencu is the author of ten books, seven\nbook chapters, and more than 160 papers published in journals\nand conference proceedings. He has also edited twelve books and\nhas twenty-seven patents to his name. He is a manager of research grants, editor in\nchief and member of international journal editorial boards, a former plenary speaker, a member of scientific committees, and chair at international conferences. His\nresearch is in the fields of control systems, control of electric drives, fuzzy control\nsystems, neural network applications, fault detection and diagnosis, sensor network\napplications, monitoring of distributed parameter systems, and power ultrasound\napplications. He has developed automation equipment for machine tools, spooling\nmachines, high-power ultrasound processes, and more.",institutionString:'"Politechnica" University Timişoara',institution:null},{id:"221364",title:"Dr.",name:"Eneko",middleName:null,surname:"Osaba",slug:"eneko-osaba",fullName:"Eneko Osaba",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/221364/images/system/221364.jpg",biography:"Dr. Eneko Osaba works at TECNALIA as a senior researcher. He obtained his Ph.D. in Artificial Intelligence in 2015. He has participated in more than twenty-five local and European research projects, and in the publication of more than 130 papers. He has performed several stays at universities in the United Kingdom, Italy, and Malta. Dr. Osaba has served as a program committee member in more than forty international conferences and participated in organizing activities in more than ten international conferences. He is a member of the editorial board of the International Journal of Artificial Intelligence, Data in Brief, and Journal of Advanced Transportation. He is also a guest editor for the Journal of Computational Science, Neurocomputing, Swarm, and Evolutionary Computation and IEEE ITS Magazine.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"275829",title:"Dr.",name:"Esther",middleName:null,surname:"Villar-Rodriguez",slug:"esther-villar-rodriguez",fullName:"Esther Villar-Rodriguez",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/275829/images/system/275829.jpg",biography:"Dr. Esther Villar obtained a Ph.D. in Information and Communication Technologies from the University of Alcalá, Spain, in 2015. She obtained a degree in Computer Science from the University of Deusto, Spain, in 2010, and an MSc in Computer Languages and Systems from the National University of Distance Education, Spain, in 2012. Her areas of interest and knowledge include natural language processing (NLP), detection of impersonation in social networks, semantic web, and machine learning. Dr. Esther Villar made several contributions at conferences and publishing in various journals in those fields. Currently, she is working within the OPTIMA (Optimization Modeling & Analytics) business of TECNALIA’s ICT Division as a data scientist in projects related to the prediction and optimization of management and industrial processes (resource planning, energy efficiency, etc).",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"49813",title:"Dr.",name:"Javier",middleName:null,surname:"Del Ser",slug:"javier-del-ser",fullName:"Javier Del Ser",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/49813/images/system/49813.png",biography:"Prof. Dr. Javier Del Ser received his first PhD in Telecommunication Engineering (Cum Laude) from the University of Navarra, Spain, in 2006, and a second PhD in Computational Intelligence (Summa Cum Laude) from the University of Alcala, Spain, in 2013. 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. He is a Senior Member of the IEEE, and a recipient of the Biscay Talent prize for his academic career.",institutionString:"Tecnalia Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"278948",title:"Dr.",name:"Carlos Pedro",middleName:null,surname:"Gonçalves",slug:"carlos-pedro-goncalves",fullName:"Carlos Pedro Gonçalves",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRcmyQAC/Profile_Picture_1564224512145",biography:'Carlos Pedro Gonçalves (PhD) is an Associate Professor at Lusophone University of Humanities and Technologies and a researcher on Complexity Sciences, Quantum Technologies, Artificial Intelligence, Strategic Studies, Studies in Intelligence and Security, FinTech and Financial Risk Modeling. He is also a progammer with programming experience in:\n\nA) Quantum Computing using Qiskit Python module and IBM Quantum Experience Platform, with software developed on the simulation of Quantum Artificial Neural Networks and Quantum Cybersecurity;\n\nB) Artificial Intelligence and Machine learning programming in Python;\n\nC) Artificial Intelligence, Multiagent Systems Modeling and System Dynamics Modeling in Netlogo, with models developed in the areas of Chaos Theory, Econophysics, Artificial Intelligence, Classical and Quantum Complex Systems Science, with the Econophysics models having been cited worldwide and incorporated in PhD programs by different Universities.\n\nReceived an Arctic Code Vault Contributor status by GitHub, due to having developed open source software preserved in the \\"Arctic Code Vault\\" for future generations (https://archiveprogram.github.com/arctic-vault/), with the Strategy Analyzer A.I. module for decision making support (based on his PhD thesis, used in his Classes on Decision Making and in Strategic Intelligence Consulting Activities) and QNeural Python Quantum Neural Network simulator also preserved in the \\"Arctic Code Vault\\", for access to these software modules see: https://github.com/cpgoncalves. He is also a peer reviewer with outsanding review status from Elsevier journals, including Physica A, Neurocomputing and Engineering Applications of Artificial Intelligence. Science CV available at: https://www.cienciavitae.pt//pt/8E1C-A8B3-78C5 and ORCID: https://orcid.org/0000-0002-0298-3974',institutionString:"University of Lisbon",institution:{name:"Universidade Lusófona",country:{name:"Portugal"}}},{id:"241400",title:"Prof.",name:"Mohammed",middleName:null,surname:"Bsiss",slug:"mohammed-bsiss",fullName:"Mohammed Bsiss",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/241400/images/8062_n.jpg",biography:null,institutionString:null,institution:null},{id:"276128",title:"Dr.",name:"Hira",middleName:null,surname:"Fatima",slug:"hira-fatima",fullName:"Hira Fatima",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/276128/images/14420_n.jpg",biography:"Dr. Hira Fatima\nAssistant Professor\nDepartment of Mathematics\nInstitute of Applied Science\nMangalayatan University, Aligarh\nMobile: no : 8532041179\nhirafatima2014@gmal.com\n\nDr. Hira Fatima has received his Ph.D. degree in pure Mathematics from Aligarh Muslim University, Aligarh India. Currently working as an Assistant Professor in the Department of Mathematics, Institute of Applied Science, Mangalayatan University, Aligarh. She taught so many courses of Mathematics of UG and PG level. Her research Area of Expertise is Functional Analysis & Sequence Spaces. She has been working on Ideal Convergence of double sequence. She has published 17 research papers in National and International Journals including Cogent Mathematics, Filomat, Journal of Intelligent and Fuzzy Systems, Advances in Difference Equations, Journal of Mathematical Analysis, Journal of Mathematical & Computer Science etc. She has also reviewed few research papers for the and international journals. She is a member of Indian Mathematical Society.",institutionString:null,institution:null},{id:"414880",title:"Dr.",name:"Maryam",middleName:null,surname:"Vatankhah",slug:"maryam-vatankhah",fullName:"Maryam Vatankhah",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Borough of Manhattan Community College",country:{name:"United States of America"}}},{id:"414879",title:"Prof.",name:"Mohammad-Reza",middleName:null,surname:"Akbarzadeh-Totonchi",slug:"mohammad-reza-akbarzadeh-totonchi",fullName:"Mohammad-Reza Akbarzadeh-Totonchi",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Ferdowsi University of Mashhad",country:{name:"Iran"}}},{id:"414878",title:"Prof.",name:"Reza",middleName:null,surname:"Fazel-Rezai",slug:"reza-fazel-rezai",fullName:"Reza Fazel-Rezai",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"American Public University System",country:{name:"United States of America"}}},{id:"426586",title:"Dr.",name:"Oladunni A.",middleName:null,surname:"Daramola",slug:"oladunni-a.-daramola",fullName:"Oladunni A. 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Possible contributions can address (but are not limited to) the following research topics: Bioinspired design and control of exoskeletons, orthoses, and prostheses; Experimental evaluation of the effect of assistive devices (e.g., influence on gait, balance, and neuromuscular system); Bioinspired technologies for rehabilitation, including clinical studies reporting evaluations; Application of neuromuscular and biomechanical models to the development of bioinspired technology.',annualVolume:11404,isOpenForSubmission:!0,coverUrl:"https://cdn.intechopen.com/series_topics/covers/8.jpg",editor:{id:"144937",title:"Prof.",name:"Adriano",middleName:"De Oliveira",surname:"Andrade",fullName:"Adriano Andrade",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRC8QQAW/Profile_Picture_1625219101815",institutionString:null,institution:{name:"Federal University of Uberlândia",institutionURL:null,country:{name:"Brazil"}}},editorTwo:null,editorThree:null,editorialBoard:[{id:"49517",title:"Prof.",name:"Hitoshi",middleName:null,surname:"Tsunashima",fullName:"Hitoshi Tsunashima",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002aYTP4QAO/Profile_Picture_1625819726528",institutionString:null,institution:{name:"Nihon University",institutionURL:null,country:{name:"Japan"}}},{id:"425354",title:"Dr.",name:"Marcus",middleName:"Fraga",surname:"Vieira",fullName:"Marcus Vieira",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y00003BJSgIQAX/Profile_Picture_1627904687309",institutionString:null,institution:{name:"Universidade Federal de Goiás",institutionURL:null,country:{name:"Brazil"}}},{id:"196746",title:"Dr.",name:"Ramana",middleName:null,surname:"Vinjamuri",fullName:"Ramana Vinjamuri",profilePictureURL:"https://mts.intechopen.com/storage/users/196746/images/system/196746.jpeg",institutionString:"University of Maryland, Baltimore County",institution:{name:"University of Maryland, Baltimore County",institutionURL:null,country:{name:"United States of America"}}}]},{id:"9",title:"Biotechnology - Biosensors, Biomaterials and Tissue Engineering",keywords:"Biotechnology, Biosensors, Biomaterials, Tissue Engineering",scope:"The Biotechnology - Biosensors, Biomaterials and Tissue Engineering topic within the Biomedical Engineering Series aims to rapidly publish contributions on all aspects of biotechnology, biosensors, biomaterial and tissue engineering. We encourage the submission of manuscripts that provide novel and mechanistic insights that report significant advances in the fields. Topics can include but are not limited to: Biotechnology such as biotechnological products and process engineering; Biotechnologically relevant enzymes and proteins; Bioenergy and biofuels; Applied genetics and molecular biotechnology; Genomics, transcriptomics, proteomics; Applied microbial and cell physiology; Environmental biotechnology; Methods and protocols. Moreover, topics in biosensor technology, like sensors that incorporate enzymes, antibodies, nucleic acids, whole cells, tissues and organelles, and other biological or biologically inspired components will be considered, and topics exploring transducers, including those based on electrochemical and optical piezoelectric, thermal, magnetic, and micromechanical elements. Chapters exploring biomaterial approaches such as polymer synthesis and characterization, drug and gene vector design, biocompatibility, immunology and toxicology, and self-assembly at the nanoscale, are welcome. Finally, the tissue engineering subcategory will support topics such as the fundamentals of stem cells and progenitor cells and their proliferation, differentiation, bioreactors for three-dimensional culture and studies of phenotypic changes, stem and progenitor cells, both short and long term, ex vivo and in vivo implantation both in preclinical models and also in clinical trials.",annualVolume:11405,isOpenForSubmission:!0,coverUrl:"https://cdn.intechopen.com/series_topics/covers/9.jpg",editor:{id:"126286",title:"Dr.",name:"Luis",middleName:"Jesús",surname:"Villarreal-Gómez",fullName:"Luis Villarreal-Gómez",profilePictureURL:"https://mts.intechopen.com/storage/users/126286/images/system/126286.jpg",institutionString:null,institution:{name:"Autonomous University of Baja California",institutionURL:null,country:{name:"Mexico"}}},editorTwo:null,editorThree:null,editorialBoard:[{id:"35539",title:"Dr.",name:"Cecilia",middleName:null,surname:"Cristea",fullName:"Cecilia Cristea",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002aYQ65QAG/Profile_Picture_1621007741527",institutionString:null,institution:{name:"Iuliu Hațieganu University of Medicine and Pharmacy",institutionURL:null,country:{name:"Romania"}}},{id:"40735",title:"Dr.",name:"Gil",middleName:"Alberto Batista",surname:"Gonçalves",fullName:"Gil Gonçalves",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002aYRLGQA4/Profile_Picture_1628492612759",institutionString:null,institution:{name:"University of Aveiro",institutionURL:null,country:{name:"Portugal"}}},{id:"211725",title:"Associate Prof.",name:"Johann F.",middleName:null,surname:"Osma",fullName:"Johann F. 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