Comparison of High high-fFrequency detectors.
\\n\\n
Released this past November, the list is based on data collected from the Web of Science and highlights some of the world’s most influential scientific minds by naming the researchers whose publications over the previous decade have included a high number of Highly Cited Papers placing them among the top 1% most-cited.
\\n\\nWe wish to congratulate all of the researchers named and especially our authors on this amazing accomplishment! We are happy and proud to share in their success!
Note: Edited in March 2021
\\n"}]',published:!0,mainMedia:{caption:"Highly Cited",originalUrl:"/media/original/117"}},components:[{type:"htmlEditorComponent",content:'IntechOpen is proud to announce that 191 of our authors have made the Clarivate™ Highly Cited Researchers List for 2020, ranking them among the top 1% most-cited.
\n\nThroughout the years, the list has named a total of 261 IntechOpen authors as Highly Cited. Of those researchers, 69 have been featured on the list multiple times.
\n\n\n\nReleased this past November, the list is based on data collected from the Web of Science and highlights some of the world’s most influential scientific minds by naming the researchers whose publications over the previous decade have included a high number of Highly Cited Papers placing them among the top 1% most-cited.
\n\nWe wish to congratulate all of the researchers named and especially our authors on this amazing accomplishment! We are happy and proud to share in their success!
Note: Edited in March 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:"8756",leadTitle:null,fullTitle:"Truss and Frames - Recent Advances and New Perspectives",title:"Truss and Frames",subtitle:"Recent Advances and New Perspectives",reviewType:"peer-reviewed",abstract:"This book presents the application of new techniques in analyzing truss and frame structures. The book contains two main sections: Numerical Analysis of Structures and Mass-Saving in Structures. Under each section, different approaches on the topic are given. Covered in these sections are dynamic stability analysis, design optimization considering vibration, FEM analysis, topology optimization methods, and recommendations to build lightweight structures. It is believed that this book will be helpful to its readers for new perspectives on the analysis of structures.",isbn:"978-1-78985-322-3",printIsbn:"978-1-78985-321-6",pdfIsbn:"978-1-78985-220-2",doi:"10.5772/intechopen.80173",price:119,priceEur:129,priceUsd:155,slug:"truss-and-frames-recent-advances-and-new-perspectives",numberOfPages:140,isOpenForSubmission:!1,isInWos:null,isInBkci:!1,hash:"00e7e78de5960f0ba908fa07fb641683",bookSignature:"Aykut Kentli",publishedDate:"March 4th 2020",coverURL:"https://cdn.intechopen.com/books/images_new/8756.jpg",numberOfDownloads:5358,numberOfWosCitations:0,numberOfCrossrefCitations:6,numberOfCrossrefCitationsByBook:1,numberOfDimensionsCitations:10,numberOfDimensionsCitationsByBook:2,hasAltmetrics:0,numberOfTotalCitations:16,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"January 21st 2019",dateEndSecondStepPublish:"March 11th 2019",dateEndThirdStepPublish:"May 10th 2019",dateEndFourthStepPublish:"July 29th 2019",dateEndFifthStepPublish:"September 27th 2019",currentStepOfPublishingProcess:5,indexedIn:"1,2,3,4,5,6,7",editedByType:"Edited by",kuFlag:!1,featuredMarkup:null,editors:[{id:"109235",title:"Associate Prof.",name:"Aykut",middleName:null,surname:"Kentli",slug:"aykut-kentli",fullName:"Aykut Kentli",profilePictureURL:"https://mts.intechopen.com/storage/users/109235/images/system/109235.jpeg",biography:"Aykut Kentli was born in Isparta, Turkey on September 5th,\n1975. He graduated from Istanbul Technical University - Faculty of Mechanical Engineering in 1997. He entered Marmara\nUniversity as a graduate student in Mechanical Engineering\nwith a specialization in Multi-objective Design Optimization.\nHe received his MSc degree in 2002 and PhD degree in 2008 in\nMechanical Engineering. Since 1997, he has been working as an\nacademician at the Mechanical Engineering Department of Marmara University\nFaculty of Engineering. He commenced lecturing on the courses of Manufacturing\nProcesses, Statics, Strength of Materials, Machine Design and Mechanical System\nDesign. His research interests are design optimization and fuzzy logic and their\napplications to engineering systems.",institutionString:"Marmara University",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"2",totalChapterViews:"0",totalEditedBooks:"1",institution:{name:"Marmara University",institutionURL:null,country:{name:"Turkey"}}}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,coeditorOne:null,coeditorTwo:null,coeditorThree:null,coeditorFour:null,coeditorFive:null,topics:[{id:"824",title:"Structural Engineering",slug:"mechanical-engineering-structural-engineering"}],chapters:[{id:"70975",title:"Dynamic Stability of Open Two-Link Mechanical Structures",doi:"10.5772/intechopen.91045",slug:"dynamic-stability-of-open-two-link-mechanical-structures",totalDownloads:653,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"The chapter deals with the assessment of the dynamic stability of elements selected from the truss or frame construction, which contains input and output parts (links) connected by a force line. From the aggregate of all factors, the resulting force factors and reactions are considered. Instead of the commonly used study of the moving of parts, a new method has been applied, consisting in the study of fluctuations in the speeds of movement and stresses. For this purpose, two partial differential equations are derived that relate the acceleration and the rate of voltage change to the gradients of these variables along the line of force. Using the Laplace transform obtained, the general equations of motion of the slave link. A technique for assessing the degree of distribution of force line parameters is derived, and the conditions for the loss of dynamic stability are identified. It is shown that in this mode, the destruction element of the truss or the frame is possible.",signatures:"Leonid Kondratenko and Lubov Mironova",downloadPdfUrl:"/chapter/pdf-download/70975",previewPdfUrl:"/chapter/pdf-preview/70975",authors:[null],corrections:null},{id:"68418",title:"Nonlinear Truss-Based Finite Element Methods for Catenary-Like Structures",doi:"10.5772/intechopen.87034",slug:"nonlinear-truss-based-finite-element-methods-for-catenary-like-structures",totalDownloads:766,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"This chapter is devoted to an application of a finite element method formulation to forecast the static and mechanical behavior of catenary-like structures subject to general force distributions, whose development was motivated by the need of installing assemblies of containment structures, called log boom lines, upstream a hydroelectric power plant to protect its integrity from the threats that logs carried through the river pose on it. Each log boom is modeled by a tridimensional truss element and the entire lines by assemblages of trusses. While the external forces, modeled with the aid of both simulations from computational fluid dynamics and experiments from a towing tank, originate from both the river stream and the logs that accumulate through the extension of the lines, the internal forces are calculated from classic expressions of solid mechanics; hence, the numerical method imposes equilibrium between them, which ultimately defines the geometry assembly. Verification and validation were performed at both model and prototype scales, and the results corroborated the accuracy of the tool for a series of flow conditions.",signatures:"Jose Rodolfo Chreim and Joao Lucas Dozzi Dantas",downloadPdfUrl:"/chapter/pdf-download/68418",previewPdfUrl:"/chapter/pdf-preview/68418",authors:[null],corrections:null},{id:"67861",title:"Design Optimization of 3D Steel Frameworks Under Constraints of Natural Frequencies of Vibration",doi:"10.5772/intechopen.87022",slug:"design-optimization-of-3d-steel-frameworks-under-constraints-of-natural-frequencies-of-vibration",totalDownloads:941,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"Steel multistorey 3D frames are commonly used in business and residential buildings, industrial sheds, warehouses, etc. The design optimization of tall steel buildings is usually governed by horizontal loadings, such as, wind load, as well as its dynamic behavior, for which the structure must have the stiffness and stability in accordance with the safety criteria established by codes. This chapter deals with sizing structural optimization problems, concerning weight minimization of 3D steel frames, considering natural frequencies of vibration as well as allowable displacements as the constraints of the optimization problem. The discrete design variables are to be chosen from commercial profiles tables. A differential evolution (DE) is the search algorithm adopted coupled to an adaptive penalty method (APM) to handle the constraints. Three different 3D frames are optimized, presenting very interesting results.",signatures:"Cláudio H.B. Resende, José P.G. Carvalho, Afonso C.C. Lemonge and Patricia H. Hallak",downloadPdfUrl:"/chapter/pdf-download/67861",previewPdfUrl:"/chapter/pdf-preview/67861",authors:[null],corrections:null},{id:"70489",title:"Topology Optimization Applications on Engineering Structures",doi:"10.5772/intechopen.90474",slug:"topology-optimization-applications-on-engineering-structures",totalDownloads:1597,totalCrossrefCites:6,totalDimensionsCites:10,hasAltmetrics:0,abstract:"Over the years, several optimization techniques were widely used to find the optimum shape and size of engineering structures (trusses, frames, etc.) under different constraints (stress, displacement, buckling instability, kinematic stability, and natural frequency). But, most of them require continuous data set where, on the other hand, topology optimization (TO) can handle also discrete ones. Topology optimization has also allowed radical changes in geometry which concludes better designs. So, many researchers have studied on topology optimization by developing/using different methodologies. This study aims to classify these studies considering used methods and present new emerging application areas. It is believed that researchers will easily find the related studies with their work.",signatures:"Aykut Kentli",downloadPdfUrl:"/chapter/pdf-download/70489",previewPdfUrl:"/chapter/pdf-preview/70489",authors:[{id:"109235",title:"Associate Prof.",name:"Aykut",surname:"Kentli",slug:"aykut-kentli",fullName:"Aykut Kentli"}],corrections:null},{id:"68382",title:"Light-Weight Structures: Proposals of Resource-Saving Supporting Structures",doi:"10.5772/intechopen.88237",slug:"light-weight-structures-proposals-of-resource-saving-supporting-structures",totalDownloads:714,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"The article will present resource-saving constructions and nodes of steel beams with a double profiled trapezoidal wall with intermittent weld seams, welded t-zones, t-zones from rolling, roll-formed channels, filling between the walls with polystyrene foam with diagonal and cross-lattice, a lattice in the form arched elements and single arched element; steel beams with a single transversally profiled wall of sinusoidal and trapezoidal outline with channel belts; resource-saving combined steel structures of frames and arches; assembly units of steel frames with spatial elements of square and round pipes. It is determined that the corrugation provides a reduction in material consumption, and the use of profiled sheets allows you to vary the size of corrugations, leads to a significant loss of weight of the structure under the condition of strength and stability. The advantages of the proposed resource-saving combined structures, namely: saving construction height (at the same time performs the function of the enclosing structure), transport and installation costs, there is no need to install transverse ribs (except in support areas and areas of concentration of significant loads), the emergence of opportunities for the use of modern technological equipment, a wide variety of applications, esthetics and many other advantages.",signatures:"Chichulina Kseniia and Chichulin Viktor",downloadPdfUrl:"/chapter/pdf-download/68382",previewPdfUrl:"/chapter/pdf-preview/68382",authors:[null],corrections:null},{id:"69296",title:"Research of Lightweight Structures for Sandwich Core Model",doi:"10.5772/intechopen.86852",slug:"research-of-lightweight-structures-for-sandwich-core-model",totalDownloads:688,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"The objective of this chapter is to focus on finding mechanical properties for two models defined as core-filled model (Type 1) and core-spaced model (Type 2) created by direct metal laser sintering (DMLS). Applied material is aluminum alloy AlSi10Mg powder and each model is created as a vertical additive manufacturing with DMLS. After quasi-static compression, Type 1 showed 19% higher elastic modulus, 12% higher compressive yield strength, and 51.6% higher elongation than Type 2. By uniaxial compressive test, there found two issues that can be the reasons to make weaker models by 3D printing were found: melted metals by DMLS are not connected with each other preciously and a space in additive layer when additive manufacturing makes a shape of specimen. In addition, anisotropy is the significant factor to decide stiffness or strength. In nearby future, various kinds of unit models such as core-filled or core-spaced model hope to be made a sandwich core structure and to be investigating more deeply about bending or shear properties continuously. In the near future, it is hoped that we see more upgraded 3D printing techniques for making aerospace materials.",signatures:"Jeongho Choi",downloadPdfUrl:"/chapter/pdf-download/69296",previewPdfUrl:"/chapter/pdf-preview/69296",authors:[null],corrections:null}],productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"},subseries:null,tags:null},relatedBooks:[{type:"book",id:"2716",title:"Advances in Computational Stability Analysis",subtitle:null,isOpenForSubmission:!1,hash:"f6471e14ce45888111151b9886ab7810",slug:"advances-in-computational-stability-analysis",bookSignature:"Safa Bozkurt Coskun",coverURL:"https://cdn.intechopen.com/books/images_new/2716.jpg",editedByType:"Edited by",editors:[{id:"22789",title:"Dr.",name:"Safa Bozkurt",surname:"Coşkun",slug:"safa-bozkurt-coskun",fullName:"Safa Bozkurt Coşkun"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"1591",title:"Infrared Spectroscopy",subtitle:"Materials Science, Engineering and Technology",isOpenForSubmission:!1,hash:"99b4b7b71a8caeb693ed762b40b017f4",slug:"infrared-spectroscopy-materials-science-engineering-and-technology",bookSignature:"Theophile Theophanides",coverURL:"https://cdn.intechopen.com/books/images_new/1591.jpg",editedByType:"Edited by",editors:[{id:"37194",title:"Dr.",name:"Theophile",surname:"Theophanides",slug:"theophile-theophanides",fullName:"Theophile Theophanides"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"3161",title:"Frontiers in Guided Wave Optics and Optoelectronics",subtitle:null,isOpenForSubmission:!1,hash:"deb44e9c99f82bbce1083abea743146c",slug:"frontiers-in-guided-wave-optics-and-optoelectronics",bookSignature:"Bishnu Pal",coverURL:"https://cdn.intechopen.com/books/images_new/3161.jpg",editedByType:"Edited by",editors:[{id:"4782",title:"Prof.",name:"Bishnu",surname:"Pal",slug:"bishnu-pal",fullName:"Bishnu Pal"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"371",title:"Abiotic Stress in Plants",subtitle:"Mechanisms and Adaptations",isOpenForSubmission:!1,hash:"588466f487e307619849d72389178a74",slug:"abiotic-stress-in-plants-mechanisms-and-adaptations",bookSignature:"Arun Shanker and B. 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Ziboon and Jawad K. Ali",dateSubmitted:"June 5th 2018",dateReviewed:"September 6th 2018",datePrePublished:"December 31st 2018",datePublished:"April 3rd 2019",book:{id:"7293",title:"Fractal Analysis",subtitle:null,fullTitle:"Fractal Analysis",slug:"fractal-analysis",publishedDate:"April 3rd 2019",bookSignature:"Sid-Ali Ouadfeul",coverURL:"https://cdn.intechopen.com/books/images_new/7293.jpg",licenceType:"CC BY 3.0",editedByType:"Edited by",editors:[{id:"103826",title:"Dr.",name:"Sid-Ali",middleName:null,surname:"Ouadfeul",slug:"sid-ali-ouadfeul",fullName:"Sid-Ali Ouadfeul"}],productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"}},authors:[{id:"261659",title:"Prof.",name:"Jawad",middleName:null,surname:"Ali",fullName:"Jawad Ali",slug:"jawad-ali",email:"jawadkali@theiet.org",position:null,institution:{name:"Institution of Engineering and Technology",institutionURL:null,country:{name:"United Kingdom"}}},{id:"262048",title:"Dr.",name:"Hadi",middleName:null,surname:"Ziboon",fullName:"Hadi Ziboon",slug:"hadi-ziboon",email:"haditarishziboon@yahoo.co.uk",position:null,institution:null}]},book:{id:"7293",title:"Fractal Analysis",subtitle:null,fullTitle:"Fractal Analysis",slug:"fractal-analysis",publishedDate:"April 3rd 2019",bookSignature:"Sid-Ali Ouadfeul",coverURL:"https://cdn.intechopen.com/books/images_new/7293.jpg",licenceType:"CC BY 3.0",editedByType:"Edited by",editors:[{id:"103826",title:"Dr.",name:"Sid-Ali",middleName:null,surname:"Ouadfeul",slug:"sid-ali-ouadfeul",fullName:"Sid-Ali Ouadfeul"}],productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"}}},ofsBook:{item:{type:"book",id:"11534",leadTitle:null,title:"Renewable Energy - Recent Advances",subtitle:null,reviewType:"peer-reviewed",abstract:"\r\n\tRenewable energy is playing an important role in today’s energy system. Moreover, the storage of renewable energy is becoming a very critical issue. This book aims to present a review of the latest advances in renewable energy resources, devices, and technologies. The different energy resources including solar energy, wind energy, biomass energy, water energy, and hydro energy resources will be presented as well as the different devices used for collecting renewable energy. Storage systems used for storing renewable energy will be discussed including compressed air storage systems, flywheel storage systems, electrochemical storage systems, and chemical storage systems, as well as different types of batteries used for collecting renewable energy. We hope to cover new topics and issues related to renewable energy, new regulations of renewable energy for different countries, and the simulation related to energy storage systems and devices. The goal of this book is to include also experimental work related to renewable energy.
\r\n\t
In order to fulfill the world energy demands increasing day by day, it is perquisite to have some alternate for the conventional energy resources and energy harvesting methods. Since last few decades, advancement in the field of the THz rectification reveal another way to develop highly sensitive uncooled THz detector. Undoubtedly, a terahertz measurement requires a highly sensitive detector to obtain distinct spectra. One problem faced by the detection of THz waves is low photon energy of milli‐electron volts (meV), making the development of a high‐performance terahertz detector a difficult task. By serendipity, accurate modeling and applications of the nanoscale materials and devices have conquered these difficulties.
\nThere is a fine line between the egoistical requirement and legitimate demand of energy around the world. By 2030, the demand for energy is projected to increase by 55%, while requirement of oil is increased from 11.4 to 17.7 billion tons [1]. Between 2005 and 2030, energy consumption is expected to increase by 50%, with the bulk of the demand coming from developing countries. The energy provided by the Sun at the Earth\'s surface on 1 day is more than enough to fulfill the needs of the whole Earth for more than 25 years, if utilizes efficiently. But due to low conversion efficiency, a prevalent commercial usage of solar energy is hardly seen. A portion of the increasing developments, utilizing the enhancement in nanotechnology may be able to change this situation. During the clear climate conditions, the Earth gets 1000 W/m2 solar irradiation from the Sun [2]. This enormous energy received from the Sun has opened the ways to look for novel systems to convert unused energy radiated continuously from the Sun into usable electricity. The continuous research results in environmentally friendly and clean energy sources and will replace our conventional sources of energy such as coal, gas, oil, hydro, combustible, petroleum energy, nuclear energy, etc. By‐products of these sources lead to greenhouse effects and the solar energy is considered to be the most excellent substitute for it as compared to other energy resources. There is a good scope for renewable/green energy corner as its share is less than 1% as compared to present energy resources.
\nThe requirements of efficient energy utilization could be estimated from the fact that during the 2012 Olympics held in London, organizer had managed new facilities with energy efficient, sustainable, and recyclable designs and they cut down the watts to maintain the games clean, green, and energy efficient. The London games had left a benchmark as the most energy‐efficient Olympics to till date. A similar kind of legacy is being followed by Rio Olympics 2016. This scenario has motivated the researchers toward exploring renewable energy and unused energy resources (dark energy, unused heat and radiations).
\nRectenna is one of the energy harvesting devices, which is a combination of rectifying high frequency diode and an antenna. Rectenna (Rectifier antenna) is a system that is capable for harvesting the infrared and visible wavelengths. The heart of the rectenna system is a metal
A lower electromagnetic (EM) region has been occupied for mobile communication systems, and the higher EM region has been occupied for optical communication. However, the THz region is still untapped and has not been completely in use, and this regime has become of colossal importance in extensive disciplines. This region embraces numerous aspects of space research, medical studies, atmospheric studies, natural science, plasma physics, defense and security, process control, etc. The close correlation of electrons and THz radiation is also reflected in the use of THz spectroscopy, which is a contemporary field for the researcher to attract toward it. THz spectroscopy is publicized to provide insight into the electron mobility in semiconductive and conductive nanostructures (like in MIM nanostructures and tunneling spectroscopy) that are suitable for fast electronics systems, which are used to convert solar power into electrons. MIM diodes are able to work in semiclassical and quantum region (Figure 1) further broader this window.
Schematic of the EM spectrum shows the working region for MIM devices.
It is also applicable for nonlinear optics and image spectroscopy. THz imaging has become a significant function in this region. The initial development of the premature terahertz time domain spectroscopy was the innovation that a range of materials, which are opaque in the visible and near‐IR region together with clothing and packaging materials, are reasonably transparent over a great extent of the THz range [3]. Room temperature operation of the infrared and far infrared frequencies detectors too increased the interest toward this region.
\nThe popularity of the study of this region can be estimated by the fact that about 50% of the luminosity and most of the photons energy emitted since Big Bang of the space are contained by the THz radiations [4]. Every technology has dark side as well as brighter one; research in THz range has been obstructed by the absorption of the Earth\'s atmosphere amongst various main factors is the water vapors present there.
We are more than 7 billion today and multiplying every second around the globe. Specialists believe that further 50% extra energy will be required by 2050 to prolong humanity. Nevertheless, it does not mean that population is the only stumbling block, but the ever inflating ego and diminishing humanity is also responsible for more energy needs. There is a fine line between the egoistical requirement and legitimate demand of energy around the world. Among various developed countries, Americans build up no more than 4.5% of the world\'s population and yet consume almost 20% of its energy. Its energy consumption is truly extraordinary [5]. In order to cope up with these problems, appropriate measures intended at reducing the dependence on the present fuels are needed, and the exploration for clean and renewable unconventional energy resources is one of the most urgent confront to the sustainable development of creature evolution.
\nThere are several unconventional sources of energy like thermal energy, nuclear, vibration, wind, water, solar energy, etc. Solar energy is estimated to provide a significant contribution for the solution of energy problem today. Just a small portion of the Sun\'s energy that hits the Earth is sufficient to meet all our power needs. A little amount of the solar energy reaching the Earth is utilized for producing electricity by using present solar systems. Still the energy demand met by using solar energy is very less. Solar cells based on photovoltaic technology have many applications in solar ponds, vehicles based on solar energy, water pumps, lights, satellites calculators, solar telephones, and many more. But there are several shortcomings of this technology in terms of bulky solar panels, costly installation, low conversion efficiency, and dependencies on the weather conditions. The photovoltaic technology used for energy harvesting has limitation of maximum conversion efficiency by the Shockley‐Queisser limit. However, in comparison the rectenna system is able to provide monospectral radio frequency‐DC (RF‐DC) with a conversion efficiency of 100% [6]. Moreover, photovoltaic technology is expensive and some poisonous by‐products are produced during the manufacturing process. Therefore, in this perspective to obtain high efficiency, a green source of renewable energy, rectenna, has emerged as one of the best solutions for meeting the growing energy demand. A system that converts unused EM radiations and radiations from the Sun into usable DC is a rectenna system. It consists of a high frequency antenna to capture the incoming signal and provides the signal to prerectification block. The band‐limited signal from prerectification block has been converted to DC which after sufficient filtration applied to output load, as shown in Figure 2.
Block diagram of rectenna system.
The term rectenna, i.e., rectifying antenna, was coined by William C. Brown, he used an array of diodes for conversion of incoming microwave power into DC [7]. However, the rectenna system in contrast also suffered from limited multispectral efficiency. The progress in the computer‐aided design structure has currently cut down the design processes, in which complex electronic circuits such as high‐frequency filters, antennas, and rectenna can be designed with a high level of buoyancy and reliability at very low cost and in small period of time.
\nFor the collection of the EM field which is a combination of electric and magnetic fields, optimized antenna design and analysis must be taken care. Maxwell\'s field equations describe the full apparatus of EM fields. Antenna’s geometric structure to associated wavelength and its polarization play a very important role. The receiving antenna must be located in the plane of polarization antenna for highest absorption of the electromagnetic fields. Several THz detectors and emitters establish the polarization with associated spectral response, e.g., dipole antennas are mainly based on linear polarization, whereas systems in incoming fields can either respond circularly, elliptically, or linearly polarized light [8].
\nSeveral nano‐sized antennas, available [9–11] to capture the small wavelength signals, are half‐wave dipole, spiral‐type, Bow‐Tie, Yagi‐Uda, etc. The shape and size of the antenna is very important for THz energy collection. The μm‐shaped antenna is required to collect the small wavelength signals. Latest nanotechnology for terahertz detection has now demanded for diode‐integrated antennas or antenna‐coupled diode detectors. The schematic diagram of integrated antenna with diode is shown in Figure 3.
A typical schematic of antenna coupled diode detector.
Baily gave the concept of capturing the solar power with antennas for the first time employing the wave nature of incoming power [12]. Antenna‐coupled detectors with micro‐bolometer, metal‐insulator‐metal diode, and Schottky diodes have been used for detection in the sub‐mm‐wave and mm‐wave regions with various antenna configurations [13, 14]. The surface plasmons are generated on the antenna due to incident EM radiations. Due to the appropriate impedance matching between the antenna geometry and the coupled MIM diode, these plasmons transfer to diode and it generates output DC.
Commonly available detectors for high‐frequency (HF) range are Schottky diode, geometric diode, and MIM/MIIM. High challenges are involved in designing of these detectors due to complex geometries involved, HF challenges and increased fabrication cost. Nevertheless, due to the advancement in technology, highly optimized diode detectors are available nowadays which perform well up to several hundred THz.
\nFor THz detection, a long time battle has been continued between Schottky and MIM diodes [15]. The
Let
\nThe low‐frequency term is given by
\nAnd high‐frequency term is given by
\nwhere
Also
\nThe cut‐off frequency of Schottky is given by
\nwhere
The MIM diode is a combination of two metal plates separated by a very thin insulating layer of the order of few nanometers. The contact area between upper and lower layer determines the active device area. The area may vary from few µm2 to several hundred µm2 depends upon the operating frequency. There are various parameters needed to be optimized for high conversion efficiency like metal work function, insulator electron affinity, and its thickness, which are responsible for the best detector. The dependencies of these parameters can be estimated from the fact that the small deviation (in the range of Å) of an insulating layer and diode area can cause a significant change in the tunneling characteristics, and
Parameters | Detectors | ||
---|---|---|---|
Schottky | MIM | Geometric | |
Max frequency of operation | Up to 30 THz [21] | Up to 150 THz [22] | Up to 28 THz [23] |
Minimum size of active area | NA | 1 µm2 [24] | 1 nm (neck length) [23] |
Zero bias resistance | NA | Few 100 kΩ [25] | Few 10 kΩ [26] |
Diode capacitance | Few fF [27] | 1.8 × 10‐15 F [28] | 1.8 × 10‐17 F [28] |
Applications | For few THz detection | For few 100 THz detection | For few 100 THz detection |
Fabrication complexity | Small | High | Very high |
Comparison of High high-fFrequency detectors.
It is the geometry of the device, which allows a preferential motion of charge carriers in a direction defined by its geometry. The asymmetric structure of the device forces to flow the charge carriers in one direction only, and it rectifies an alternating current as a result and hence gives the diode like actions. The diode acts as a funnel for the flow of carriers moving from left to right or right to left (depends on the design of geometry), with restricted flow in one direction and ease flow in other direction as shown in Figure 4. These diodes are able to convert from few THz to 1000 THz into usable DC [20].
Schematic diagram of geometric diode.
MIM diodes are the successor of Schottky diodes. The Schottky diodes have been routinely used for high‐frequency applications like rectification and mixing. MIM diodes are not influenced by parasitic capacitors as compared to Schottky diodes. Extremely broader bandwidth, minute size, room temperature operation, effortlessly integrability with CMOS innovation [28], and zero bias voltage requirements are different encouraging factors for MIM diodes to be investigated with increased interest from last two decades. It is an exceptionally encouraging innovation for terahertz regime. The femtosecond quick exchanging time of these diodes makes them valuable in numerous low power and ultra‐fast applications going from rectenna sunlight‐based cells as an energy harvesting device [29] to imaging, sensing, and hot electron transistors, also in numerous refined microelectronic products such as switching memories, display devices (LCD backplanes), field emission cathodes [30], etc. MIM diode is a thin‐film device in which the electrons tunnel through the insulator layer from the first metal layer to the second metal. Figure 5 shows the schematic representation of the MIM diode.
MIM diode schematic diagram.
Charge transport across the insulator occurs due to quantum‐mechanical tunneling of electrons. A similar concept applies to MIM diodes, the process in which a particle penetrates or tunnel via the energy barrier in place of jump over it in contrary to classical mechanics. When the electron reaches the barrier, the insulator in between the metal electrodes absorbs some part of the energy passes through the barrier reaching to the second electrode, but another part reflects back due to some irregularities in thee insulator. How much the energy absorbs and reflected originally depends upon the different characteristics of material used such as work‐function difference of metal electrodes, electron affinity of the insulator material, thickness of the barrier, applied potential energy, etc.
\nDue to the tunneling phenomena involved, the energy beam absorbed makes it travel at ultra‐high speeds. The speed is much higher than that on a normal conductor or a semiconductor like silicon. Tunneling is a highly nonlinear phenomenon, and hence these diodes are exploited for the rectification, mixing, and detection of alternating currents at very high frequencies even in the THz spectral region. Figure 6 shows the typical schematic diagram of the MIM band and Fowler‐Nordheim tunneling method.
A typical schematic of MIM band diagram with FN tunneling.
The frequency response of the diode is governed by the resistor‐capacitor (RC) time constant. Higher the cutoff frequency, lower the capacitance and resistance. The impedance of the diode must be close enough to the impedance of the antenna for maximum power transfer, and the capacitance must be minimized for operation at THz frequencies. Thickness cannot be decreased to facilitate tunneling, hence only area is left to be altered. Krishnan et al. report the fabrication of terahertz MIM diode, the atto‐farad capacitance (10–18) is required, which further needs the device areas less than 100 nm × 100 nm for typical material systems which require e‐beam lithography. However, this challenge of fabricating such nanoscale geometry has been overcome to a large extent by using modern lithographic techniques. Miniature‐size diodes can be fabricated with the modern ultra‐fine deposition techniques, such as e‐beam lithography, reactive sputtering, etc., with small size, higher cutoff frequency, and thin insulating layer. Table 2 lists these features of the MIM devices fabricated using different techniques.Table 2 lists these features of the MIM devices fabricated using different techniques.
MIM combination | Active area | Insulator thickness | Patterning technique | Cut‐off freq. | Ref. |
---|---|---|---|---|---|
Ni‐NiO‐Ni | 110 × 110 nm2 | 3.5 nm | E‐beam lithography | 30 THz | [31] |
Ni‐NiO‐Cr | 1.6 µm2 | 3 nm | E‐beam lithography | 94 GHZ | [32] |
Ni‐NiO‐Ag | 3.1 × 10‐4 µm2 | 6 nm | E‐beam lithography | 343 THz | [33] |
Cu‐CuO‐Cu | 2 × 2 µm2 | 2 nm | E‐beam/reactive sputtering | – | [34] |
Comparison of MIM diodes fabricated using latest deposition methods.
Trade‐off between asymmetry and diode junction resistance can be overcome using multi‐layer structure [34]. In comparison to the MIM diode, the tunneling current can be easily engineered in such multi‐insulator MIM diodes by simply altering the type and number of insulators. This changes the number of barrier heights present at each interface and consequently the
Probability of electrons penetrating the insulator layer is called as tunneling probability. It is also called as transport probability, it is the ratio of the number of electrons incident on the interface with the electrons that reflected back. In order to tunneling take place, the two metals having insulators in between must have different work functions. When a bias voltage is applied between the metal electrodes of MIM diode, the potential barrier is reduced and charge carriers start tunneling between the two electrodes through the thin‐film. Tunneling occurs in either direction, but by proper choice of metal electrodes with different work functions, the magnitude of the tunneling current will become larger in one direction than in the other direction. The tunneling current is calculated using Simmon\'s method [37]. This method assumes low‐temperature operation hence neglecting thermal currents and incorporating tunneling as the main electron transport mechanism.
\nDifferent algorithms such as TMM (transmission matrix method), WKB (Wentzel, Kramers, and Brillouin) approximation, and NEGF (nonequilibrium green function method) have been developed for calculating the tunneling probability. Simmon provides an approximation of a finite probability of electron penetration in the course of the insulator using WKB method. But this method overvalued the transport current. NEGF formulism is the method used to calculate the tunneling transmission probability. Using NEGF approximation, the total number of electrons emitted from left electrode and right electrode can be taken into consideration by defining two quantities, namely, left electrode and right electrode coupling functions, Figure 7 shows the application of NEGF formulism to MIM diode [38]. TMM is also a powerful fast method for the analysis of transport properties of nonhomogeneous systems [32]. These algorithms have been compared for the calculation of transport probability in [39].
A typical schematic diagram showing the application of NEGF to MIM diode.
An efficient modeling of MIM diode enables an investigator to predict the optimum material combination and device geometry for desired current‐voltage characteristics. The accuracy of modeling depends on correct estimation of modeling parameters such as applied bias voltage, barrier thickness, dielectric constants of the insulator layers, and effective mass (assumed to be unity).
\nVarious research groups are working to design an accurate model for rectenna system using different software such MATLAB, PSpice, Mathemaica, ADS, etc. [32, 34, 40]. We had not combined MIM diodes with antennas but modeled and fabricated MIM diodes for using two combinations (aluminum and chromium) of materials and assume the incoming energy to diode to be 100%.
\nThe diodes are simulated using model [35] and fabricated diode\'s
For the fabrication of MIM diode, the aluminum (work function of 4.28 eV) is used for the preparation of bottom electrode, and aluminum dioxide Al2o3 (having electron affinity of 1.25 eV) is used as a barrier layer after plasma oxidation of aluminum. For top electrode, chromium (work function of 4.5 eV
The substrate on which the MIM diode is fabricated is a microscopic glass slide, which is optically flat and smooth on both sides. The reason for using a glass substrate is that it is a transparent material, inexpensive, and readily available. Yet another reason is that, if silicon is used, it needs to be oxidized to form SiO2 before the metals could be deposited to prevent the shorting of metals with the substrate. Since glass as a substrate needs to be cleaned before fabrication. Complete process for cleaning has been followed as explained in Ref. [34].
The metal deposition for MIM diode is done by thermal evaporation. Two fundamental requirements for the metal to be deposited are the adhesion to the substrate and a smooth uniform surface. The fabricated MIM diode with the base metal made of aluminum and top metal made of chromium. The metal has been deposited using smart coat 3.0 by the thermal evaporation method. This method involves heating a material to the point of evaporation, usually at a pressure of around 10–6 mbar. The smart coat is cleaned properly by IPA or acetone. Using an automatic mode, the materials are loaded in the chamber and the deposition has been done. Thickness is accumulated at the program deposition rate. Basically, the potentiometer is controlling the current supply providing to the filament and accordingly controlling the rate of thickness Å/s, more the current more the rate of thickness. The rate of deposition can be monitored on the display panel. Mainly the current value is dependent on the material that are depositing, for example, for Al (aluminum) it will have 10—15 A current value and for Au (gold) it required > 70 A. Vibrations on the crystal holder produced due to external factors or due to internal vacuum pumps inside the smart coat 3.0 may vary the readings on thickness monitor. For the desired thickness (kÅ) continuous monitoring is required. Figure 8 shows the smart coat 3.0 used for metal deposition.
After loading the material in the smart coat chamber, the insulator layer is formed (using an aluminum mask) by the exposure of the oxygen (or argon) gas applied at a rate of 20–30 psi for a period of 10–12 minutes to form the plasma oxides on the base metal. Comparatively, thin layer with low impedance is formed in comparison with other deposition techniques. Similar procedure is used for the formation of top metal electrode as used for bottom electrode. After following the procedure completely, the final device is formed. Figure 9 shows the fabricated diode and the mask used.
The setup to measure the
Chromium is supplied with a negative bias and aluminum is supplied with a positive bias. The probes are lowered very slowly, so that the probe making contact with the top electrode is just in contact and the second probe on the bottom electrode is scraped a bit to ensure the proper contact with the aluminum.
The DC characteristics of the fabricated diode MIM (Al‐Al2o3‐Cr) include the
(a) Smart coat machine for thin‐film deposition (b) Inside smart coat chamber.
Fabricated MIM diode and mask used.
Setup for DC characterization.
Measured DC characteristics of (Al‐Al2o3‐ Cr) MIM diode, (a) current versus voltage relationship (b) nonlinearity versus voltage.
Accurate detection and modeling of transport characteristics for any energy harvesting system are the main key for the calculation of
The author is grateful for providing research facilities in support of this work by Director of University Institute of Engineering & Technology, Kurukshetra University, Kurukshetra. The author acknowledges the help of Prof. R.K. Aggarwal, Computer Engineering Department, National Institute of Technology, Kurukshetra for various supports.
The path to drug discovery is a long, challenging & arduous task not to mention the overburdening finances it demands. As of 2014, the average cost of developing a new drug from scratch was found to be an estimated $2.5 billion, an increase of 145% from the previous study done by the same organization in 2003. The major reasons for this drastic increase in the cost is mainly attributed to high failure rate of drugs among others [1]. Understanding of the drug discovery process is important to handle the challenges faced by the pharma companies in terms of cost and innovation.
The process of identifying a target, synthesizing an active compound with suitable characteristics like minimal toxicity, high bioavailability, cost-effective synthesis, etc., and finally developing it to introduce in the market is a time-consuming, extremely complex and risky endeavor [2]. Initially, a target is identified which plays a key role in progress of the disease. Once a link between the target and the disease has been established, the next step is to identify potential candidates which can stop or reverse the progress of the disease [3]. This process starts with the discovery of molecules that show efficacy in a simple screen, called “hits.” Screening is a process in which normally a large number of compounds from natural products and online databases are examined for biological activity in high-throughput assays. This step in the drug discovery process is very crucial and demands maintaining huge molecular libraries and carrying out thousands or millions of assays, which leaves the academicians and small pharmaceutical companies at a disadvantage and also shoots up the cost for larger industries. Next, the “hits” found are chemically modified to give improved pharmaceutical properties, such compounds are often called “leads.” But, it is quite apparent that the method stated above for discovery of a drug has a number of pitfalls. From an academic point of view, carrying out high throughput screens (HTS) is costly, time-consuming and not feasible; while, from an industrial perspective, it does nothing to improve the eminent danger of market saturation.
Truly innovative and blockbuster drugs are what drive the pharmaceutical industry forward but, over the past few years introduction of new molecular entities (NMEs) has vastly reduced. For example, in 2007 only 19 NMEs were approved by the US Food and Drug Administration (FDA), the least since 1983 [4]. Currently, and even in the future it is expected that only slight modifications of the existing blockbuster drugs would be carried out which would further aggravate this problem [5]. HTS would not help in either curbing the rising costs of discovering hits or the problem of finding truly innovative and blockbuster NMEs, the two major hurdles that the pharmaceutical industry faces now-a-days.
To overcome these challenges, molecular docking is an exemplary tool. During the first step to find hits from existing chemicals for a drug discovery and development project, virtual screening (VS) is a perfectly viable and an alternative or complementary approach to HTS for fulfilling the screening of thousands or millions of compounds within a few days. In addition, the speed of VS helps in kick-starting projects for newer targets for which no leads are available [6]. Molecular docking is one of the most applied virtual screening methods and has become increasingly useful overtime on account of immense growth in 3D X-ray and NMR structures and their improved resolution (physics and knowledge based docking algorithms depend on it) reported in the Protein Data Bank (PDB). As an example, in total 46,541 X-ray structures were reported at the end of 2008 in PDB, but by the end of 2018 it had grown to a staggering figure of 131,993 [7]. In addition, it is a resource saving technique which provides accessibility of screening to academia and small industries which were earlier limited to large pharmaceutical giants.
In this chapter, we will discuss a particular class of molecular design, i.e., “Docking” along with the various algorithms, techniques, success stories and limitations related to it. In the end, we will conclude with its scope in the near future.
Two molecules can interact in a number of ways let alone the interaction of a protein and protein or a protein and small molecule. Molecular docking helps us in predicting the intermolecular framework formed between a protein and a small molecule or a protein and protein and suggest the binding modes responsible for inhibition of the protein. To accurately carry out docking studies one requires the high-resolution X-ray, NMR or homology-modeled structure with known/predicted binding site in the biomolecule. To date, 148,827 are available in the database (PDB) [3]. Docking methods fit a ligand into a binding site by combining and optimizing variables like steric, hydrophobic and electrostatic complementarity and also estimating the free energy of binding (scoring) [8].
There are two basic components which distinguish the variety of docking softwares available to choose from—One is sampling algorithm and the other is scoring function, these are discussed in detail.
As pointed out earlier, there are a huge number of modes of binding between two molecules and even with advances in parallel computing and higher clock speeds of modern computers it would be expensive and time-consuming to generate all the possible modes. Therefore, algorithms were needed which could fish out valuable conformations from the fruitless ones.
Various algorithms were developed in this regard and can be classified by the number of degrees of freedom they ignore. The simplest of the algorithms introduced treated the molecules as two rigid bodies thereby reducing the degree of freedom to just six (three translational and three rotational). A very well cited example of a program using this algorithm is DOCK [9]. This program was designed to find molecules which had a huge extent of shape similarity to the pockets/grooves or binding sites. It derives an image of suspected binding sites present on the surface of the protein. This image consists of several overlapping spheres of varying radii which touch the molecular surface of the macromolecule at just two points. The ligand molecule is also considered as a set of spheres which approximately fill the space occupied by the ligand. Once the respective representations of the protein surface and the ligand in terms of sphere are complete, the pairing rule is applied. The pairing rule is based on the principle that ligand sphere can be paired with a protein sphere if the internal distances of all the spheres in the ligand set match all the internal distances within the protein set, allowing some user specified tolerance. Thus, it allows the program to identify geometrically similar cluster of spheres on the protein site and the ligand. Many other programs were developed later which make use of such matching algorithm (MA) which include LibDock [8], LIDAEUS [10], PhDOCK [11], Ph4DOCK [12], Q-fit [13], SANDOCK [14], etc. All these programs based on MA have the advantage of speed but have several limitations such as prior need for detailed receptor geometry and lack of molecular flexibility which does not accurately define many aspects of ligand-protein interactions.
The second algorithm is that of incremental construction (IC), wherein the ligand is fragmented from rotatable bonds into various segments. One of the segments is anchored to the receptor surface. The anchor is generally considered to be the fragment which shows maximum interactions with the receptor surface, has minimum number of alternate conformations and fairly rigid such as the ring system. Once the base/anchor has been established, the next step is to add each of the fragments step by step. Ideally, those fragments are added first which have a greater chance of showing interactions like hydrogen bonding since they are directional in nature and are responsible for specificity of the ligand. In addition, hydrogen bonds lead to more accurate prediction of geometry. Once a particular fragment is added, the poses with the least energies are considered for the next iteration, making the algorithm extremely fast and robust [15]. IC has been used in programs like DOCK 4.0 [16], FlexX [15], Hammerhead [17], SLIDE [18] and eHiTS [19], SKELGEN [20], ProPose [21], PatchDock [22], MacDock [23], FLOG [24], etc. One major limitation of this program is that it is restricted to medium sized ligands and is not feasible for large size ligands where the number of fragments generated pose a problem.
Another useful algorithm is the Monte Carlo (MC) technique. In this approach, a ligand is modified gradually using bond rotation and translation or rotation of the entire ligand. More than one parameter can also be changed at a time to get a particular conformation. That conformation is then evaluated at the binding site based on energy calculation using molecular mechanics and is then rejected or accepted for the next iteration based on Boltzmann’s probability constant. Acceptance or rejection of the conformation is a function of the change in energy with respect to a parameter T, which can be physically interpreted as temperature (simulated annealing). This criterion of acceptance or rejection makes this method strikingly different than the others. Whereas the other algorithm favor decrease in energy, in MC method increases are also possible. For higher values of T increases are likely. If one starts at a high value of T, then small energy barriers can be jumped and the configuration can move beyond local minima and is therefore particularly useful in situations where a global minimum is sought among many local minima [25]. An interesting spin-off of the MC approach is the Tabu search, which maintains a record of the search space of the binding site which has already been visited and thus ensures that the binding site is explored to the maximum [26]. MC approach has been made use of in programs like DockVision 1.0.3 [25], FDS [27], GlamDock [28], ICM [29], MCDOCK [30], PRODOCK [31], QXP [32], ROSETTALIGAND [33], RiboDock [34], Yucca [35], AutoDock [36], etc. One of the major concerns with MC approach is the uncertainty of convergence, which can be improved by performing multiple independent runs.
Genetic algorithm (GA) is quite similar to MC method and is basically used to find the global minima [37]. These are much inspired by the Darwin’s Theory of Evolution [38]. GA maintains a population of ligands with an associated fitness determined by the scoring function. Each ligand represents a potential hit. The GA alters the ligands of the population by mutation or crossover. In the first stage, a new population is created by accessing and then selecting the more fit ligands from the previous step. The members of the populations are then transformed in the alteration step. The mutation operator creates new ligands from a single ligand by randomly changing a fragment in its representation while the crossover operator exchanges information between two (occasionally more) members of the population [39, 40, 41]. GA has been incorporated in programs like Autodock 4.0 [42], DARWIN [43], DIVALI [39], FITTED [44], FLIPDock [45], GAMBLER [46], GAsDock [47], GOLD 3.1 [48], PSI-DOCK [49]. GA has a similar limitation like that of MC method wherein the uncertainty of convergence is a major drawback.
Another approach is the hierarchical method. In this approach, the low energy conformations of the ligand are pre-computed and aligned. The populations of the pre-generated ligand conformations are merged into a hierarchy such that similar conformations are positioned adjacent to each other within the hierarchy. Afterwards, on carrying out rotation or translation of the ligand, the docking program will make use of this hierarchical data structure and thus minimize the outcomes. Let us understand with a simple example—if an atom near the rigid center of the ligand is found to clash with the protein in a given rotation/translation, then this approach can reject all of the conformations lying below in the hierarchy to that of the conformation under scrutiny, because the descendants must contain the same clash as well [50]. GLIDE software makes use of the hierarchical method [51, 52].
Sampling changes among varying degrees of freedom must be performed with sufficient accuracy to identify a conformation that best matches the receptor structure, and also must be fast enough to permit the evaluation of millions of compounds in a set computational time. This is taken care by the variety of algorithms discussed above. Algorithms are further complemented by scoring functions.
The evaluation and ranking of predicted ligand conformations is a crucial aspect of VS. When we are interested in only how a single ligand binds to a biomolecule, then the scoring function needs to predict the docked orientation which most accurately represents the “true” structure of the intermolecular complex. On the other hand, if we are interested to evaluate multiple ligands, in that scenario the scoring function should not only identify the “true” docking pose but also be able to rank one ligand relative to another. Therefore, the design of reliable scoring functions and schemes which can rank different poses is of fundamental importance [53].
The scoring functions usually estimate binding energy of complex using many assumptions and simplifications to arrive as close as possible to actual binding energy in minimum time. Popular scoring functions have an adequate balance between accurate estimation of binding energy and computational cost in terms of time. There have been a number of scoring functions developed over the past many years and can be classified into three main categories—force field, empirical and knowledge based [54].
Force field functions: force field (FF) scoring functions are developed based on physical atomic interactions like van der Waals interactions, electrostatic interactions and bond lengths, bond angles and torsions [55]. Force field functions and parameters are usually derived from both experimental data and ab initio quantum mechanical calculations according to the principles of physics.
Here, rij stands for the distance between protein atom i and ligand atom j, Aij and Bij are the van der Waal parameters, qi and qj are the atomic charges and ε(rij) is the distance dependent dielectric constant.
One common example of a FF scoring function is that of the program DOCK [56] represented in Eq. (1), where, the effect of solvent is indirectly considered by the distance dependent dielectric constant e(rij) seen in the Coulombic potential. One major drawback of this function is that it does not consider an important solvent effect that charged groups favor aqueous environments whereas non-polar groups tend to stay in non-aqueous environments, commonly referred to as the desolvation effect [57]. Ignorance could lead to biased results as the function would now be totally dependent on the coulombic interactions and would thus favor highly charged ligands. In other words, it only takes into account the interaction of protein and ligand, which is inadequate. To build a more robust function one needs to also evaluate how both interact with water before the formation of the complex and how water mediates this process.
Later the Shoichet group [58] improved upon the existing function by adding the effects of the solvent on protein-ligand interactions using implicit solvent models. They employed the Poisson-Boltzmann approach to model the electrostatic potential of the protein. The van der Waals interactions were calculated using the Lennard-Jones potential; the electrostatic interaction between the ligand and the protein was estimated using a precomputed receptor potential determined with DelPhi [59]. Ligand desolvation penalties were calculated with HYDREN [60]. The solvent-corrected scores were found to be closer to experimental binding free energies than the DOCK program scores, but were still too favorable. The overestimation of complex stability could be due to the neglect of solute entropic terms [58].
There a few scoring functions which be classified in this category such as DockScore [56], GoldScore [61], HADDOCK Score [62], ICM SF [29], QXP SF [32], etc.
Empirical scoring functions: the basis of this scoring function is that the binding energies of a complex can be approximated by a sum of individual uncorrelated terms. The coefficients of the various terms involved in calculation of binding energy are obtained from regression analysis using experimentally determined binding energies or potentially from X-ray structural information. Empirical functions have simpler energy terms to evaluate when compared to force field scoring functions and thus are much faster in binding score calculations.
The first empirical scoring function developed to predict binding free energies was implemented in LUDI, credited to the pioneering work of Bohm [63]. The energy was derived using experimental binding free energies and protein-ligand crystal structures for 45 complexes.
Here, ∆Go is the binding energy independent of protein interactions, ∆Ghb describes contribution to binding energy from hydrogen bonds, ∆Gionic denotes contribution to binding energy from unperturbed ionic interactions, ∆Glipo considers contribution to binding energy through lipophilic interactions while Alipo is the lipophilic contact surface between the protein and the ligand, ∆Grot describes the loss of binding energy due to freezing of internal degrees of freedom in the ligand while NROT represents number of rotatable bonds and f(∆R, ∆α) is a penalty function that accounts for large deviations from ideal hydrogen bond and salt bridge geometry.
As shown in Eq. (2), the binding free energy is modeled using hydrogen bonds, salt bridges, the hydrophobic effect, and solute entropy terms. The hydrogen bond and salt bridge terms are modified by a penalty function which accounts for deviation from ideal geometry. Entropy loss of the ligand upon complex formation is based on the Number of ROTatable bonds (NROT) in the ligand [64, 65]. Eldridge et al. presented an empirical scoring function referred to as ChemScore by taking into account different energetic parameters like hydrogen bonds, the lipophilic effects of atoms, the effective number of rotatable bonds in the ligand among others. The scoring function was calibrated using 82 ligand-receptor complexes with known binding affinities [66].
By including different empirical energy terms, many different empirical scoring functions have been developed such as SCORE2 [67], ChemScore [66], RankScore [68], LigScore [69], GlideScore [51], HINT [70], etc. The empirical scoring functions take into account many different energy terms and thus the problem of unknowingly double-counting of certain energy terms difficult issue to tackle.
Knowledge based scoring functions: these are derived from the structural information embedded in experimentally determined atomic structures. The functions use statistical analysis on crystal structures of complexes to obtain the interatomic contact frequencies between the protein and the ligand based on the presumption that stronger an interaction is, the greater the frequency of its occurrence will be. The overall score is calculated with the help of Eq. (3) by accounting for favorable contacts and repulsive interactions between each atom in the ligand and protein lying within a sphere with a specified cutoff [71, 72, 73, 74, 75, 76, 77, 78].
Here, kB is the Boltzmann constant, T is the absolute temperature of the system, ρ(r) is the number density of the protein-ligand atom at distance r, ρ*(r) is the pair density in the reference state where interatomic interactions are zero and g(r) is pair distribution function.
Popular knowledge based functions include DrugScore [79], PMF [72, 80], MScore [81], SMoG [71], BLEEP [74], ITScore/SE [75], etc. The computational simplicity of such functions is a major advantage especially when one has large databases at hand however, the accuracy of predicting the reference state and underrepresentation of interactions with halogens and metals are the major hurdles.
Each of the above classified have their inherent drawbacks, in this regard, combination of more than one scoring functions has given improved results. This approach has been widely regarded as “Consensus Scoring” [46].
Another set of scoring functions which have recently started to attract attention are based on machine learning. One of the programs based on functions incorporating machine learning was able to achieve an astounding hit rate of 88.6% [82]. The nexus of machine learning and scoring functions is promising but the development of such a tool is slow owing to its complexity.
In order to compare the variety of scoring functions that have been developed up until now, comparative assessment of scoring functions (CASF) is an incredible platform to begin with [83].
There is another set of classification proposed for the scoring functions namely physics-based methods, empirical scoring functions, knowledge-based potentials, and descriptor-based scoring functions but there is still no clear consensus on which classification of scoring functions would be appropriate [84].
Molecular docking has been developed and improving for many years, but its ability to generate a viable drug is still generally questioned. In the section below, you will find examples where docking approach lead to recognition of active hits for a variety of different receptors/targets.
HIV 1 Integrase—a new binding site for drugs treating AIDS was discovered by Schames et al. using docking while considering the flexibility of the receptor through molecular dynamics. The group used AutoDock in conjunction with the relaxed-complex method to discover novel mode of inhibition of HIV integrase [85].
α1A Adrenergic receptor—Evers et al. generated a model of the receptor using homology modeling based on the X-ray crystallographic structure of bovine rhodopsin. Hierarchical virtual screening method was performed by them on the Aventis in-house compound repository in a stepwise manner. 22,950 filtered compounds were then docked into the α1A receptor homology model with the program GOLD and scored with PMF. The top scoring compounds were finally clustered according to their unity fingerprint similarity, and a diverse set of 80 compounds was tested in a radio ligand displacement assay. Thirty-seven compounds displayed a Ki < 10 μM with the most active having Ki = 1.4 nM [86].
Type I TGF-beta receptor kinase—A striking example and a proof of the benefit of in silico approach over classical high-throughput screening involves the discovery of novel Type I TGF-beta receptor kinase inhibitor. The same molecule (HTS-466284); Figure 1, a 27 nM inhibitor, was discovered independently using virtual screening [87] and also by traditional enzyme and cell-based high-throughput screening in the same year [88]. The compound discovered experimentally required in vitro screening of a large library of compounds in a TGF-β-dependent cell-based assay which required more time, proved to be costlier and required usage of a variety of chemicals when compared to its computational counterpart.
Structure of HTS-46628, type I TGF-beta receptor kinase inhibitor.
Aurora Kinase A—A major improvement was seen in the inhibitory activity of Aurora Kinase A inhibitors which were designed using in silico techniques by Park et al. [89]. This research group made use of a genetic algorithm to carry out the sampling while the scoring function involved the energy terms from the AutoDock program with a slight modification of the dehydration energy term. The design strategy and tools used to carry out the study proved to be immensely successful with some inhibitors revealing exceptionally high potency at low picomolar levels; Figure 2 [89].
Structures for Aurora Kinase A inhibitor with IC50 12 and 43 pM respectively.
Dopamine D3 receptor—The 3D structure of the Dopamine 3 (D3) subtype receptor was modeled by Varady et al. from the X-ray crystallographic structure of rhodopsin and validated using experimental data. A D3 pharmacophore model was devised by them from 10 selective and potent known D3 receptor ligands. Using their model, 250,251 compound were screened from the National Cancer Institute (NCI) 3D database. The hit list of 2478 potential ligands was then filtered for known chemotypes. After removal of all compounds that were structurally similar to known D3 receptor ligands, 1314 candidates remained. At the end, 20 compounds supplied by NCI to the group were tested, out of which eight had Ki values below 500 nM, among which one of the compounds had Ki = 11 nM; Figure 3 [90].
Structure of dopamine D3 receptor inhibitor with Ki = 11 nM.
Serotonin receptor (5HT1A)—Due to lack of structural information available for the receptor, Becker et al. made use of PREDICT, to develop a unique non-homology model for building a virtual 3D structure of the receptor. Using the model, 40,000 compounds from Predix’s compound library were screened for molecular docking and 78 virtual hits were discovered and then purchased by them from respective vendors. The in vitro 5-HT1A binding assays elucidated that 16 of the 78 compounds tested by the group were found to be hits with Ki < 5 μM, reflecting a 21% hit rate, 9 of which had a Ki < 1 μM. The most potent molecule had Ki = 1 nM (Figure 4) and was selected as a lead molecule for further optimization. One significant feature of the study which highlights the utility of docking was that the complete discovery process, i.e., from in silico screening through lead optimization, preclinical, and into clinical studies, was very rapid, requiring less than a couple of years from program initiation to Phase I clinical trial [91].
Structure of serotonin receptor inhibitor with Ki = 1 nM.
Crystal structure prediction challenge—The International Blind Test is a challenge organized by the Cambridge Crystallographic Data Center wherein a previously determined crystal structure is only revealed once all the participants submit their respective structures. In the Fifth International Blind Test, the challenge was toughened by including flexible molecules with 50–60 atoms. The successful prediction by two participants of the crystal structure of molecule XX in the blind test indicated that search methods and models for lattice energy are capable of providing worthwhile results, both in terms of the range of structures considered in the search and relative energies of the structures and thus can act as efficient ranking systems [92].
Muscarinic M3 receptor—A pharmacophore model was constructed by Marriot et al. from the known molecules showing significant M3 potency [93]. The research group utilized the program DISCO, which generated five models. Three models were rejected based on structural overlay. 3D screening was performed by Unity 3D of the Astra compound database. The first model developed by them gave 176 hits while the second model gave 173 hits; 172 compounds were common to the two sets and were tested for their M3-antagonistic potency. Several compounds with micromolar and even submicromolar activities resulted, for example, compound below had A50 M3 antagonism ≈ 0.2 μM; pA2 = 6.67; Figure 5 [93].
Structure of muscarinic M3 receptor antagonist.
Checkpoint Kinase 1—Lyne et al. utilized virtual screening to discover Checkpoint Kinase 1 (Chk-1) inhibitors [94]. Compounds with molecular weight > 600 or with more than 10 rotatable bonds were excluded from the database. Then 3D structures of the ligands were generated using Corina and a maximum of 8 stereoisomers were generated for each molecule. A 3D pharmacophore search was performed with their in-house program Plurality to eliminate compounds that do not have the typical binding motif for the kinase region. The remainder of the compounds were docked into the ATP binding site of Chk-1, using the program FlexX-Pharm, which considers full flexibility of the ligand but treats the protein as a rigid structure. The research group then utilized consensus scoring to identify molecules which were consistently giving good score with different scoring functions. Finally, visual inspection by the group of the 250 highest scoring hits for unfavorable interactions with the binding site or compounds with unrealistic conformations resulted in a list of 103 compounds for biological testing. Thirty-six hits were identified with IC50 ranging from 110 nM to 68 μM; Figure 6 [94].
Structures of checkpoint kinase 1 inhibitor with IC50 450 nM and 4 μM respectively.
Human Cathepsin K—Schröder et al. presented the implementation of a docking-based virtual screening workflow for the retrieval of covalent binders, human cathepsin K was utilized as a test case [95]. By using the filter of electrophilic war heads, a database with two million structurally diverse compounds with a variety of functional groups was reduced to a data set of just 343 test compounds. Molecular docking was performed by them and the top scoring poses of the GoldScore ranking list were taken into account for the manual selection of the virtual hits based on visual inspection of the appropriate fit of the molecule in the active site. A data set of 44 compounds including the five low scoring compounds were finally selected for experimental evaluation. The activity of 21 out of the selected 39 in silico hits was experimentally confirmed and four out of the five structures predicted as inactive showed no activity on cathepsin K. This study demonstrated to a huge extent the ability of docking to generate positive outcomes (Figure 7) [95].
Respective structures for active and inactive covalent binders of human cathepsin K.
Human aldose reductase (ALR2)—ALR2 catalyzes a key reaction in the polyol pathway of glucose metabolism, a process implicated in the long-term complications of diabetes. Its inhibitors were designed by Wang et al. using molecular dynamic (MD) simulations and virtual screening [96]. A major challenge encountered by them in the in silico studies was that the binding site of the enzyme underwent large conformational changes and adopted distinct configurations upon binding different classes of ligands. To address this issue, the group sampled potentially accessible binding site conformations by MD simulations based on the available crystallographic structures of ALR2. After this procedure, three average conformations were selected for the docking. FlexX was utilized to carry out docking of 7200 compounds of which 128 compounds were selected by them for further screening. Out of these 72 molecules were selected which had RMSD < 3.00 A for experimental assay, of which 15 novel ALR2 inhibitors hits were discovered. The most potent inhibitor had an IC50 = 0.24 μM; Figure 8 [96].
Structure of human aldose reductase inhibitor with IC50 = 0.24 μM.
Cyclooxygenase-2 (COX-2) and β-amyloid aggregation inhibitors—Dadashpour et al. made use of AutoDock4.2 to carry out docking studies of designed molecules based on diaryltriazine as lead. To validate the enzyme-inhibitor complex, the key molecular interactions and calculated binding energy were considered by them. Among the designed molecules, one of the compounds (Figure 9) showed an IC50 of 10.1 μM in experimental COX-2 assay. In addition, it showed potent anti-aggregation activity on β peptides [97].
Structure of cyclooxygenase-2 inhibitor with IC50 = 10.1 μM.
The major limitation of molecular docking is due to the lack of confidence on the ability of scoring functions to give accurate binding energies. This stems from the fact that some intermolecular interaction terms are hardly predicted accurately, such as solvation effect and entropy change [98]. In addition, some intermolecular interactions are rarely considered in scoring functions which have been proven to be of significance. For instance, halogen bonding is verified to make a contribution to protein-ligand binding affinity [99] and so do guanidine-arginine interactions [100], but are not considered.
Transthyretin-thyroxine complex—One critical example wherein energy functions failed is that of transthyretin-thyroxine complex. The docking simulations with energy functions resulted in generation of two binding modes, one similar to the native binding mode of thyroxine and the other belonging to an alternate binding domain with a root mean square deviation (RMSD) of 8.97 Å from native binding state. The energy simulation was carried out and the lower energy solution picked by the docking program was the one with higher RMSD. Thus, in this case molecular docking failed to make the correct prediction of binding mode. Thereby, it would be fair to conclude that we might get many false negatives during the process of VS. [101].
It is still an unsolved problem to accurately deal with the water molecules in binding pocket during docking process, which is tough task and needs a lot of attention in the near future due to two reasons. Firstly, the x-ray crystal structures lack the coordinate information of hydrogen, due to inefficient scattering by smaller atoms. Not knowing the exact position of hydrogen leads to inaccuracies in identifying water molecules which might be acting as a bridging molecule between the ligand and the receptor. Secondly, no reliable theoretical approach is available to accurately predict how water molecules are affected by ligands and how strong the effect is. On top of that, it impossible with our current knowledge to predict how many water molecules in the binding pocket would be replaced by potential ligands and how the hydrogen bonding network would be disturbed by ligand binding [102].
One of the major challenges faced in the field of docking is that of rigid receptor. A protein can adopt many different conformations depending upon the ligand to which it binds. As a result, docking performed using a rigid receptor will correspond to a single receptor conformation, which leads to false negatives in many cases where later the ligand was found to be active. This happens because a protein can exist in constant motion between different conformational states having similar energies, which is usually neglected in docking [58].
Finally, the spectrum of activity against off-target proteins is something rarely seen even in computational screens and is only dealt by animal and human trials.
Thus, it is quite evident from the case studies highlighted above and many more success stories that one can find in literature related to computer aided drug design, that in silico approaches in combination with biophysical data, experimental high throughput screening and biology/toxicology/clinical studies are an indispensable tool in the process of drug discovery. It assists in decision making, conceptualizing new ideas and exploring them in a rapid manner to test a hypothesis, bringing solutions to problems that cannot be assessed experimentally either because the experiments is too difficult to design or because it would cost too much.
Undoubtedly, many challenges still remain to be addressed such as role of water molecules, solvent effects, entropic effects, and receptor flexibility.
There is more than sufficient information now that proves the utility of computational tools in drug design and there is no scope for any debate regarding the effectiveness and advantage of computational tools in the process of drug discovery.
The Internet has irrevocably changed the dynamics of scholarly communication and publishing. Consequently, we find it necessary to indicate, unambiguously, our definition of what we consider to be a published scientific work.
",metaTitle:"Prior Publication Policy",metaDescription:"Prior Publication Policy",metaKeywords:null,canonicalURL:"/page/prior-publication-policy",contentRaw:'[{"type":"htmlEditorComponent","content":"A significant number of working papers, early drafts, and similar work in progress are openly shared online between members of the scientific community. It has become common to announce one’s own research on a personal website or a blog to gather comments and suggestions from other researchers. Such works and online postings are, indeed, published in the sense that they are made publicly available. However, this does not mean that if submitted for publication by IntechOpen they are not original works. We differentiate between reviewed and non-reviewed works when determining whether a work is original and has been published in a scholarly sense or not.
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\\n"}]'},components:[{type:"htmlEditorComponent",content:'A significant number of working papers, early drafts, and similar work in progress are openly shared online between members of the scientific community. It has become common to announce one’s own research on a personal website or a blog to gather comments and suggestions from other researchers. Such works and online postings are, indeed, published in the sense that they are made publicly available. However, this does not mean that if submitted for publication by IntechOpen they are not original works. We differentiate between reviewed and non-reviewed works when determining whether a work is original and has been published in a scholarly sense or not.
\n\nThe significance of Peer Review cannot be overstated when it comes to defining, in our terms, what constitutes a published scientific work. Peer Review is widely considered to be the cornerstone of modern publishing processes and the key value-adding contribution to a scholarly manuscript that a publisher can make.
\n\nOther than the issue of originality, research misconduct is another major issue that all publishers have to address. IntechOpen’s Retraction & Correction Policy and various publication ethics guidelines identify both redundant publication and (self)plagiarism to fall within the definition of research misconduct, thus constituting grounds for rejection or the issue of a Retraction if the work has already been published.
\n\nIn order to facilitate the tracking of a manuscript’s publishing history and its development from its earliest draft to the manuscript submitted, we encourage Authors to disclose any instances of a manuscript’s prior publication, whether it be through a conference presentation, a newspaper article, a working paper publicly available in a repository or a blog post.
\n\nA note to the Academic Editor containing detailed information about a submitted manuscript’s previous public availability is the preferred means of reporting prior publication. This helps us determine if there are any earlier versions of a manuscript that should be disclosed to our readers or if any of those earlier versions should be cited and listed in a manuscript’s references.
\n\nSome basic information about the editorial treatment of different varieties of prior publication is laid out below:
\n\n1. CONFERENCE PAPERS & PRESENTATIONS
\n\nGiven that conference papers and presentations generally pass through some sort of peer or editorial review, we consider them to be published in the accepted scholarly sense, particularly if they are published as a part of conference proceedings.
\n\nAll submitted manuscripts originating from a previously published conference paper must contain at least 50% of new original content to be accepted for review and considered for publication.
\n\nAuthors are required to report any links their manuscript might have with their earlier conference papers and presentations in a note to the Academic Editor, as well as in the manuscript itself. Additionally, Authors should obtain any necessary permissions from the publisher of their conference paper if copyright transfer occurred during the publishing process. Failure to do so may prevent Us from publishing an otherwise worthy work.
\n\n2. NEWSPAPER & MAGAZINE ARTICLES
\n\nNewspaper and magazine articles usually do not pass through any extensive peer or editorial review and we do not consider them to be published in the scholarly sense. Articles appearing in newspapers and magazines rarely possess the depth and structure characteristic of scholarly articles.
\n\nSubmitted manuscripts stemming from a previous newspaper or magazine article will be accepted for review and considered for publication. However, Authors are strongly advised to report any such publication in an accompanying note to the External Editor.
\n\nAs with the conference papers and presentations, Authors should obtain any necessary permissions from the newspaper or magazine that published the work, and indicate that they have done so in a note to the External Editor.
\n\n3. GREY LITERATURE
\n\nWhite papers, working papers, technical reports and all other forms of papers which fall within the scope of the ‘Luxembourg definition’ of grey literature do not pass through any extensive peer or editorial review and we do not consider them to be published in the scholarly sense.
\n\nAlthough such papers are regularly made publicly available via personal websites and institutional repositories, their general purpose is to gather comments and feedback from Authors’ colleagues in order to further improve a manuscript intended for future publication.
\n\nWhen submitting their work, Authors are required to disclose the existence of any publicly available earlier drafts in a note to the Academic Editor. In cases where earlier drafts of the submitted version of the manuscript are publicly available, any overlap between the versions will generally not be considered an instance of self-plagiarism.
\n\n4. SOCIAL MEDIA, BLOG & MESSAGE BOARD POSTINGS
\n\nWe feel that social media, blogs and message boards are generally used with the same intention as grey literature, to formulate ideas for a manuscript and gather early feedback from like-minded researchers in order to improve a particular piece of work before submitting it for publication. Therefore, we do not consider such internet postings to be publication in the scholarly sense.
\n\nNevertheless, Authors are encouraged to disclose the existence of any internet postings in which they outline and describe their research or posted passages of their manuscripts in a note to the Academic Editor. Please note that we will not strictly enforce this request in the same way that we would instructions we consider to be part of our conditions of acceptance for publication. We understand that it may be difficult to keep track of all one’s internet postings in which the researcher´s current work might be mentioned.
\n\nIn cases where there is any overlap between the Author´s submitted manuscript and related internet postings, we will generally not consider it to be an instance of self-plagiarism. This also holds true for any co-Author as well.
\n\nFor more information on this policy please contact permissions@intechopen.com.
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On September, 29th 2006 he has won a post PhD fellowship from the university of Bologna (from October 2006 to October 2008), at the competitive examination he was ranked first in the industrial engineering area. He extensively served as referee for several international journals. He is author/coauthor of more than 100 research papers. He has been involved in some projects supported by MURST and European Community. His research interests include pattern recognition, bioinformatics, and biometric systems (fingerprint classification and recognition, signature verification, face recognition).",institutionString:null,institution:null},{id:"496",title:"Dr.",name:"Carlos",middleName:null,surname:"Leon",slug:"carlos-leon",fullName:"Carlos Leon",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"University of Seville",country:{name:"Spain"}}},{id:"512",title:"Dr.",name:"Dayang",middleName:null,surname:"Jawawi",slug:"dayang-jawawi",fullName:"Dayang Jawawi",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"University of Technology Malaysia",country:{name:"Malaysia"}}},{id:"528",title:"Dr.",name:"Kresimir",middleName:null,surname:"Delac",slug:"kresimir-delac",fullName:"Kresimir Delac",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/528/images/system/528.jpg",biography:"K. Delac received his B.Sc.E.E. degree in 2003 and is currentlypursuing a Ph.D. degree at the University of Zagreb, Faculty of Electrical Engineering andComputing. His current research interests are digital image analysis, pattern recognition andbiometrics.",institutionString:null,institution:{name:"University of Zagreb",country:{name:"Croatia"}}},{id:"557",title:"Dr.",name:"Andon",middleName:"Venelinov",surname:"Topalov",slug:"andon-topalov",fullName:"Andon Topalov",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/557/images/1927_n.jpg",biography:"Dr. Andon V. Topalov received the MSc degree in Control Engineering from the Faculty of Information Systems, Technologies, and Automation at Moscow State University of Civil Engineering (MGGU) in 1979. He then received his PhD degree in Control Engineering from the Department of Automation and Remote Control at Moscow State Mining University (MGSU), Moscow, in 1984. 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Lignocellulosic residues are mixed and burnt with coal to generate electricity. Presently, crude oil is replaced by bioethanol and biodiesel produced from biomass substrate. Some special class of chemicals can be derived from biomass that can subsequently replace the usage of non‐renewable resources of oil and coal. Pyrolysis of woody biomass to obtain pyroliginous acid was started hundreds of years ago, which has versatile applications. The range of products that can be derived from biomass is huge, prompting extent of research using different types of thermal conversion technologies, including pyrolysis, gasification, torrefaction, anaerobic digestion and hydrothermal processing. This chapter provides insights about the stages of reaction during pyrolysis and the outcome of reaction conditions on the products. Technical development and adjustment of process condition can offer a suitable environmentally benign scheme to increase the energy density of the lignocellulosic residues.",book:{id:"5758",slug:"pyrolysis",title:"Pyrolysis",fullTitle:"Pyrolysis"},signatures:"Chowdhury Zaira Zaman, Kaushik Pal, Wageeh A. Yehye, Suresh\nSagadevan, Syed Tawab Shah, Ganiyu Abimbola Adebisi, Emy\nMarliana, Rahman Faijur Rafique and Rafie Bin Johan",authors:[{id:"198251",title:"Dr.",name:"Zaira",middleName:null,surname:"Chowdhury",slug:"zaira-chowdhury",fullName:"Zaira Chowdhury"},{id:"208451",title:"Associate Prof.",name:"Kaushik",middleName:null,surname:"Pal",slug:"kaushik-pal",fullName:"Kaushik Pal"}]}],mostDownloadedChaptersLast30Days:[{id:"56034",title:"Pyrolysis: A Sustainable Way to Generate Energy from Waste",slug:"pyrolysis-a-sustainable-way-to-generate-energy-from-waste",totalDownloads:8295,totalCrossrefCites:50,totalDimensionsCites:80,abstract:"Lignocellulosic biomass is a potentially more valuable renewable resource that can be utilized effusively as a chief source of heat for cooking and can correspondingly subsidize the production of electricity, heat, biofuels and chemicals including solid fuel like char or carbon. Lignocellulosic residues are mixed and burnt with coal to generate electricity. Presently, crude oil is replaced by bioethanol and biodiesel produced from biomass substrate. Some special class of chemicals can be derived from biomass that can subsequently replace the usage of non‐renewable resources of oil and coal. Pyrolysis of woody biomass to obtain pyroliginous acid was started hundreds of years ago, which has versatile applications. The range of products that can be derived from biomass is huge, prompting extent of research using different types of thermal conversion technologies, including pyrolysis, gasification, torrefaction, anaerobic digestion and hydrothermal processing. This chapter provides insights about the stages of reaction during pyrolysis and the outcome of reaction conditions on the products. Technical development and adjustment of process condition can offer a suitable environmentally benign scheme to increase the energy density of the lignocellulosic residues.",book:{id:"5758",slug:"pyrolysis",title:"Pyrolysis",fullTitle:"Pyrolysis"},signatures:"Chowdhury Zaira Zaman, Kaushik Pal, Wageeh A. Yehye, Suresh\nSagadevan, Syed Tawab Shah, Ganiyu Abimbola Adebisi, Emy\nMarliana, Rahman Faijur Rafique and Rafie Bin Johan",authors:[{id:"198251",title:"Dr.",name:"Zaira",middleName:null,surname:"Chowdhury",slug:"zaira-chowdhury",fullName:"Zaira Chowdhury"},{id:"208451",title:"Associate Prof.",name:"Kaushik",middleName:null,surname:"Pal",slug:"kaushik-pal",fullName:"Kaushik Pal"}]},{id:"44033",title:"Ion-Exchange Chromatography and Its Applications",slug:"ion-exchange-chromatography-and-its-applications",totalDownloads:29925,totalCrossrefCites:7,totalDimensionsCites:28,abstract:null,book:{id:"3487",slug:"column-chromatography",title:"Column Chromatography",fullTitle:"Column Chromatography"},signatures:"Özlem Bahadir Acikara",authors:[{id:"109364",title:"Dr.",name:"Özlem",middleName:null,surname:"Bahadır Acıkara",slug:"ozlem-bahadir-acikara",fullName:"Özlem Bahadır Acıkara"}]},{id:"52155",title:"EOR Processes, Opportunities and Technological Advancements",slug:"eor-processes-opportunities-and-technological-advancements",totalDownloads:5532,totalCrossrefCites:17,totalDimensionsCites:36,abstract:"Enhanced oil recovery (EOR) processes are well known for their efficiency in incrementing oil production; however, the selection of the most suitable method to adopt for specific field applications is challenging. Hence, this chapter presents an overview of different EOR techniques currently applied in oil fields, the opportunities associated with these techniques, key technological advancements to guide the decision‐making process for optimum applicability and productivity and a brief review of field applications.",book:{id:"5143",slug:"chemical-enhanced-oil-recovery-ceor-a-practical-overview",title:"Chemical Enhanced Oil Recovery (cEOR)",fullTitle:"Chemical Enhanced Oil Recovery (cEOR) - a Practical Overview"},signatures:"Lezorgia Nekabari Nwidee, Stephen Theophilus, Ahmed Barifcani,\nMohammad Sarmadivaleh and Stefan Iglauer",authors:[{id:"37799",title:"Dr.",name:"Stefan",middleName:null,surname:"Iglauer",slug:"stefan-iglauer",fullName:"Stefan Iglauer"},{id:"179076",title:"Dr.",name:"Lezorgia",middleName:"Nekabari",surname:"Nwidee",slug:"lezorgia-nwidee",fullName:"Lezorgia Nwidee"},{id:"179077",title:"Prof.",name:"Ahmed",middleName:null,surname:"Barifcani",slug:"ahmed-barifcani",fullName:"Ahmed Barifcani"},{id:"179078",title:"Prof.",name:"Stephen",middleName:null,surname:"Theophilus",slug:"stephen-theophilus",fullName:"Stephen Theophilus"},{id:"189371",title:"Dr.",name:"Mohammad",middleName:null,surname:"Sarmadivaleh",slug:"mohammad-sarmadivaleh",fullName:"Mohammad Sarmadivaleh"}]},{id:"57510",title:"Solvents for Carbon Dioxide Capture",slug:"solvents-for-carbon-dioxide-capture",totalDownloads:4122,totalCrossrefCites:16,totalDimensionsCites:40,abstract:"Anthropogenic CO2 emissions are considered the major contributor of greenhouse gas emissions worldwide. The mitigation of this kind of CO2 emissions relies on a portfolio of alternatives where CO2 absorption appears as the nearest approach to be applied at industrial scale. Researchers have been focused on developing new formulations of solvents to make more competitive CO2 absorption as a carbon capture and storage (CCS) technology. In this sense, this chapter summarizes both the conventional solvents and the most recent investigations on this field. Chemical absorption is more suitable for a lot of industrial process due to the flue gas conditions: ambient pressure, low CO2 concentration and large volume. Therefore numerous novel solvents came up in recent years and they are further discussed in this chapter. The most recent solvents, their mechanisms and kinetics and the advantages and disadvantages are also included. Finally, physical solvents are adequate in high CO2 partial pressure applications and they are reported in the last section. Although physical absorption field is constrained to high-pressure flue gas, physical solvents provided higher performance in CO2 separation process and their characteristics are also summarized.",book:{id:"6186",slug:"carbon-dioxide-chemistry-capture-and-oil-recovery",title:"Carbon Dioxide Chemistry, Capture and Oil Recovery",fullTitle:"Carbon Dioxide Chemistry, Capture and Oil Recovery"},signatures:"Fernando Vega, Mercedes Cano, Sara Camino, Luz M. Gallego\nFernández, Esmeralda Portillo and Benito Navarrete",authors:[{id:"10704",title:"Prof.",name:"Benito",middleName:null,surname:"Navarrete",slug:"benito-navarrete",fullName:"Benito Navarrete"},{id:"209759",title:"Dr.",name:"Fernando",middleName:null,surname:"Vega",slug:"fernando-vega",fullName:"Fernando Vega"},{id:"218843",title:"Dr.",name:"Mercedes",middleName:null,surname:"Cano",slug:"mercedes-cano",fullName:"Mercedes Cano"},{id:"218844",title:"Mrs.",name:"Sara",middleName:null,surname:"Camino",slug:"sara-camino",fullName:"Sara Camino"},{id:"218845",title:"Mrs.",name:"Luz. M.",middleName:null,surname:"Gallego Fernández",slug:"luz.-m.-gallego-fernandez",fullName:"Luz. M. Gallego Fernández"},{id:"218846",title:"Mrs.",name:"Esmeralda",middleName:null,surname:"Portillo",slug:"esmeralda-portillo",fullName:"Esmeralda Portillo"}]},{id:"13241",title:"Heat Flow, Work Energy, Chemical Reactions, and Thermodynamics: a Dynamical Systems Perspective",slug:"heat-flow-work-energy-chemical-reactions-and-thermodynamics-a-dynamical-systems-perspective",totalDownloads:3282,totalCrossrefCites:0,totalDimensionsCites:2,abstract:null,book:{id:"25",slug:"thermodynamics",title:"Thermodynamics",fullTitle:"Thermodynamics"},signatures:"Wassim M. Haddad, Sergey G. Nersesov and VijaySekhar Chellaboina",authors:[{id:"15784",title:"Dr.",name:"Wassim",middleName:"M.",surname:"Haddad",slug:"wassim-haddad",fullName:"Wassim Haddad"},{id:"15788",title:"Prof.",name:"Sergey",middleName:"G.",surname:"Nersesov",slug:"sergey-nersesov",fullName:"Sergey Nersesov"},{id:"15789",title:"Prof.",name:"Vijay Sekhar",middleName:null,surname:"Chellaboina",slug:"vijay-sekhar-chellaboina",fullName:"Vijay Sekhar Chellaboina"}]}],onlineFirstChaptersFilter:{topicId:"113",limit:6,offset:0},onlineFirstChaptersCollection:[{id:"78950",title:"Performance Investigation of the Solar Membrane Distillation Process Using TRNSYS Software",slug:"performance-investigation-of-the-solar-membrane-distillation-process-using-trnsys-software",totalDownloads:37,totalDimensionsCites:0,doi:"10.5772/intechopen.100335",abstract:"Membrane distillation (MD) is a separation process used for water desalination, which operates at low pressures and feeds temperatures. Air gap membrane distillation (AGMD) is the new MD configuration for desalination where both the hot feed side and the cold permeate side are in indirect contact with the two membrane surfaces. The chapter presents a new approach for the numerical study to investigate various solar thermal systems of the MD process. The various MD solar systems are studied numerically using and including both flat plate collectors (the useful thermal energy reaches 3750 kJ/hr with a total area of 4 m2) and photovoltaic panels, each one has an area of 1.6 m2 by using an energy storage battery (12 V, 200 Ah). Therefore, the power load of solar AGMD systems is calculated and compared for the production of 100 L/day of distillate water. It was found that the developed system consumes less energy (1.2 kW) than other systems by percentage reaches 52.64% and with an average distillate water flow reaches 10 kg/h at the feed inlet temperature of AGMD module 52°C. Then, the developed system has been studied using TRNSYS and PVGIS programs on different days during the year in Ain Temouchent weather, Algeria.",book:{id:"10995",title:"Distillation Processes - From Solar and Membrane Distillation to Reactive Distillation Modelling, Simulation and Optimization",coverURL:"https://cdn.intechopen.com/books/images_new/10995.jpg"},signatures:"Abdelfatah Marni Sandid, Taieb Nehari, Driss Nehari and Yasser Elhenawy"},{id:"81310",title:"Modeling of Solar-Powered Desalination",slug:"modeling-of-solar-powered-desalination",totalDownloads:26,totalDimensionsCites:0,doi:"10.5772/intechopen.103934",abstract:"The scarcity, global, and local demand of pure water for SDGs become prominent issue. The global emissions of CO2 and GHGs have put pressure to develop the solar-powered desalination plants. This article discussed the selection of site for the solar thermal desalination in Pakistan keeping the eye on sustainability and modeling and cost analysis of single solar stills technology at Lyari River in Karachi, Pakistan. Pakistan is among the water-deficit countries having 35% of population having lack of pure drinkable water. The plenty of solar irradiance and saline water in Pakistan make it very favorable for solar-powered desalination. The solar stills technology is one of the best technologies to meet the local demand of pure water. The modeling is composed of governing equations based on the law of conservation of mass and law of conservation of energy. The solar irradiance at Lyari River is taken from MERRA–2. The result depicted that the hourly production of distill water is 1 kg/m3 and 8 kg/m3 with and without the FRL lens. The cost of distill water produced from the solar stills having FRL lens is 33% less as compared with solar stills without FRL lens.",book:{id:"10995",title:"Distillation Processes - From Solar and Membrane Distillation to Reactive Distillation Modelling, Simulation and Optimization",coverURL:"https://cdn.intechopen.com/books/images_new/10995.jpg"},signatures:"Zafar Abbas, Nasir Hayat, Anwar Khan and Muhammad Irfan"},{id:"80466",title:"Reactive Distillation Applied to Biodiesel Production by Esterification: Simulation Studies",slug:"reactive-distillation-applied-to-biodiesel-production-by-esterification-simulation-studies",totalDownloads:114,totalDimensionsCites:0,doi:"10.5772/intechopen.102667",abstract:"Reactive distillation is an operation that combines chemical reaction and separation in a single equipment, presenting various technical and economic benefits. In this chapter, an introduction to the reactive distillation process applied to the biodiesel industry was developed and complemented by case studies regarding the production of biodiesel through esterification a low-cost acid feedstock (corn distillers oil) and valorization of by-products (glycerol) through ketalization. The kinetic parameters of both reactions were estimated with an algorithm that performs the minimization of the quadratic differences between experimental and calculated data through a Nelder-Mead simplex method. A 4th order Runge Kutta method was employed to integrate the conversion or concentration equations used to describe the kinetics of the reactions in a batch reactor. Both processes were simulated in the commercial software Aspen Plus with the estimated kinetic parameters. The results obtained are promising and indicate that the productivity of both processes can be improved with the application of reactive distillation technologies. The simulated esterification process with an optimized column resulted in a fatty acids conversion increase of 84% in comparison to the values lower than 50% obtained in the experimental tests. Solketal production through ketalization also achieved a high glycerol conversion superior to 98%.",book:{id:"10995",title:"Distillation Processes - From Solar and Membrane Distillation to Reactive Distillation Modelling, Simulation and Optimization",coverURL:"https://cdn.intechopen.com/books/images_new/10995.jpg"},signatures:"Guilherme Machado, Marcelo Castier, Monique dos Santos, Fábio Nishiyama, Donato Aranda, Lúcio Cardozo-Filho, Vladimir Cabral and Vilmar Steffen"},{id:"79275",title:"Thermal Desalination Systems: From Traditionality to Modernity and Development",slug:"thermal-desalination-systems-from-traditionality-to-modernity-and-development",totalDownloads:97,totalDimensionsCites:3,doi:"10.5772/intechopen.101128",abstract:"As well known, the basic birthrights of human are the clean air, clean water, healthy food, and green energy. So, clean water is the second important requested need of all living organisms on Earth. To know the importance of water to our human bodies, a deficiency of just 2% in our body’s water supply indicates dehydration. Nowadays, all countries suffer from the problem of freshwater shortage. Despite the importance of clean water for our lives, only 0.01% is available as surface water such as the rivers, lakes, and swamps. These frightening facts have made it a national and humanitarian duty for scientists to research how to overcome the water problem and how to provide alternative sources of safe drinking water using renewable energies. Desalination is the most famous and operative technique used to overcome this problem. In this chapter, the different desalination techniques are reviewed and reported. Also, the solar distillation processes are mentioned with an extended review on the solar distillers. Besides, the application of artificial intelligence in improving the performance of desalination systems is reported. The main conclusions are stated at the end of this chapter.",book:{id:"10995",title:"Distillation Processes - From Solar and Membrane Distillation to Reactive Distillation Modelling, Simulation and Optimization",coverURL:"https://cdn.intechopen.com/books/images_new/10995.jpg"},signatures:"Fadl A. Essa"},{id:"79937",title:"Desalination by Membrane Distillation",slug:"desalination-by-membrane-distillation",totalDownloads:186,totalDimensionsCites:0,doi:"10.5772/intechopen.101457",abstract:"At present, around 25% of water desalination processes are based on distillation. Similar to classical distillation, membrane distillation is a phased-change process in which a hydrophobic membrane separates two phases. Membrane distillation is considered an emerging player in the desalination, food processing and water treatment market. Due to its high salt rejection, less fouling propensity, operating at moderate temperature and pressure, membrane distillation is considered as a future sustainable desalination technology. The distillation process is quite well known in desalination. However, membrane distillation emerged a few decades ago, and a thorough understanding is needed to adapt this technique in the near future. This review chapter introduces the classical distillation and membrane distillation as an emerging technology in the desalination arena. Heat and mass transfer and thermodynamics in membrane distillation, characteristics of the performance metrics of membrane distillation are also described. Finally, the performance evaluation of MD is presented. The possibility of using low-grade heat in membrane distillation allows it to integrate directly to solar energy and industrial waste heat.",book:{id:"10995",title:"Distillation Processes - From Solar and Membrane Distillation to Reactive Distillation Modelling, Simulation and Optimization",coverURL:"https://cdn.intechopen.com/books/images_new/10995.jpg"},signatures:"Mustakeem Mustakeem, Sofiane Soukane, Muhammad Saqib Nawaz and Noreddine Ghaffour"},{id:"79199",title:"Principles and Modes of Distillation in Desalination Process",slug:"principles-and-modes-of-distillation-in-desalination-process",totalDownloads:149,totalDimensionsCites:0,doi:"10.5772/intechopen.100855",abstract:"Distillation has been a very important separation technique used over many centuries. This technique is diverse and applicable in different fields and for different substances. Distillation is important in the desalination section. Various principles are used in desalting seawater and brackish water to fulfill the demands of freshwater. This work explains the modes and principles of distillation in desalination, their types, present improvement, challenges, and limitations as well as possible future improvements. The first and primary mode of distillation is the passive type. As times went by and the demand for freshwater kept increasing, other modes were introduced and these modes fall under the active distillation type. However, each mode has its own advantages, disadvantages, and limitations over each other. The principles and modes of distillation are as significant as understanding the energy sources needed for distillation. Hence, they are the basic knowledge needed for future innovation in the desalination industries.",book:{id:"10995",title:"Distillation Processes - From Solar and Membrane Distillation to Reactive Distillation Modelling, Simulation and Optimization",coverURL:"https://cdn.intechopen.com/books/images_new/10995.jpg"},signatures:"Abubakar Sadiq Isah, Husna Takaijudin and Balbir Singh Mahinder Singh"}],onlineFirstChaptersTotal:8},preDownload:{success:null,errors:{}},subscriptionForm:{success:null,errors:{}},aboutIntechopen:{},privacyPolicy:{},peerReviewing:{},howOpenAccessPublishingWithIntechopenWorks:{},sponsorshipBooks:{sponsorshipBooks:[],offset:8,limit:8,total:0},allSeries:{pteSeriesList:[{id:"14",title:"Artificial Intelligence",numberOfPublishedBooks:9,numberOfPublishedChapters:90,numberOfOpenTopics:6,numberOfUpcomingTopics:0,issn:"2633-1403",doi:"10.5772/intechopen.79920",isOpenForSubmission:!0},{id:"7",title:"Biomedical Engineering",numberOfPublishedBooks:12,numberOfPublishedChapters:107,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2631-5343",doi:"10.5772/intechopen.71985",isOpenForSubmission:!0}],lsSeriesList:[{id:"11",title:"Biochemistry",numberOfPublishedBooks:33,numberOfPublishedChapters:330,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2632-0983",doi:"10.5772/intechopen.72877",isOpenForSubmission:!0},{id:"25",title:"Environmental Sciences",numberOfPublishedBooks:1,numberOfPublishedChapters:19,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2754-6713",doi:"10.5772/intechopen.100362",isOpenForSubmission:!0},{id:"10",title:"Physiology",numberOfPublishedBooks:14,numberOfPublishedChapters:145,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2631-8261",doi:"10.5772/intechopen.72796",isOpenForSubmission:!0}],hsSeriesList:[{id:"3",title:"Dentistry",numberOfPublishedBooks:9,numberOfPublishedChapters:139,numberOfOpenTopics:2,numberOfUpcomingTopics:0,issn:"2631-6218",doi:"10.5772/intechopen.71199",isOpenForSubmission:!0},{id:"6",title:"Infectious Diseases",numberOfPublishedBooks:13,numberOfPublishedChapters:123,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2631-6188",doi:"10.5772/intechopen.71852",isOpenForSubmission:!0},{id:"13",title:"Veterinary Medicine and Science",numberOfPublishedBooks:11,numberOfPublishedChapters:112,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2632-0517",doi:"10.5772/intechopen.73681",isOpenForSubmission:!0}],sshSeriesList:[{id:"22",title:"Business, Management and Economics",numberOfPublishedBooks:1,numberOfPublishedChapters:21,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2753-894X",doi:"10.5772/intechopen.100359",isOpenForSubmission:!0},{id:"23",title:"Education and Human Development",numberOfPublishedBooks:0,numberOfPublishedChapters:10,numberOfOpenTopics:1,numberOfUpcomingTopics:1,issn:null,doi:"10.5772/intechopen.100360",isOpenForSubmission:!0},{id:"24",title:"Sustainable Development",numberOfPublishedBooks:1,numberOfPublishedChapters:19,numberOfOpenTopics:5,numberOfUpcomingTopics:0,issn:"2753-6580",doi:"10.5772/intechopen.100361",isOpenForSubmission:!0}],testimonialsList:[{id:"6",text:"It is great to work with the IntechOpen to produce a worthwhile collection of research that also becomes a great educational resource and guide for future research endeavors.",author:{id:"259298",name:"Edward",surname:"Narayan",institutionString:null,profilePictureURL:"https://mts.intechopen.com/storage/users/259298/images/system/259298.jpeg",slug:"edward-narayan",institution:{id:"3",name:"University of Queensland",country:{id:null,name:"Australia"}}}},{id:"13",text:"The collaboration with and support of the technical staff of IntechOpen is fantastic. 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",coverUrl:"https://cdn.intechopen.com/series/covers/3.jpg",latestPublicationDate:"August 4th, 2022",hasOnlineFirst:!0,numberOfPublishedBooks:9,editor:{id:"419588",title:"Ph.D.",name:"Sergio",middleName:"Alexandre",surname:"Gehrke",slug:"sergio-gehrke",fullName:"Sergio Gehrke",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y000038WgMKQA0/Profile_Picture_2022-06-02T11:44:20.jpg",biography:"Dr. Sergio Alexandre Gehrke is a doctorate holder in two fields. The first is a Ph.D. in Cellular and Molecular Biology from the Pontificia Catholic University, Porto Alegre, Brazil, in 2010 and the other is an International Ph.D. in Bioengineering from the Universidad Miguel Hernandez, Elche/Alicante, Spain, obtained in 2020. In 2018, he completed a postdoctoral fellowship in Materials Engineering in the NUCLEMAT of the Pontificia Catholic University, Porto Alegre, Brazil. He is currently the Director of the Postgraduate Program in Implantology of the Bioface/UCAM/PgO (Montevideo, Uruguay), Director of the Cathedra of Biotechnology of the Catholic University of Murcia (Murcia, Spain), an Extraordinary Full Professor of the Catholic University of Murcia (Murcia, Spain) as well as the Director of the private center of research Biotecnos – Technology and Science (Montevideo, Uruguay). Applied biomaterials, cellular and molecular biology, and dental implants are among his research interests. He has published several original papers in renowned journals. In addition, he is also a Collaborating Professor in several Postgraduate programs at different universities all over the world.",institutionString:null,institution:{name:"Universidad Católica San Antonio de Murcia",institutionURL:null,country:{name:"Spain"}}},editorTwo:null,editorThree:null},subseries:{paginationCount:2,paginationItems:[{id:"1",title:"Oral Health",coverUrl:"https://cdn.intechopen.com/series_topics/covers/1.jpg",isOpenForSubmission:!0,editor:{id:"173955",title:"Prof.",name:"Sandra",middleName:null,surname:"Marinho",slug:"sandra-marinho",fullName:"Sandra Marinho",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRGYMQA4/Profile_Picture_2022-06-01T13:22:41.png",biography:"Dr. Sandra A. Marinho is an Associate Professor and Brazilian researcher at the State University of Paraíba (Universidade Estadual da Paraíba- UEPB), Campus VIII, located in Araruna, state of Paraíba since 2011. She holds a degree in Dentistry from the Federal University of Alfenas (UNIFAL), while her specialization and professional improvement in Stomatology took place at Hospital Heliopolis (São Paulo, SP). Her qualifications are: a specialist in Dental Imaging and Radiology, Master in Dentistry (Periodontics) from the University of São Paulo (FORP-USP, Ribeirão Preto, SP), and Doctor (Ph.D.) in Dentistry (Stomatology Clinic) from Hospital São Lucas of the Pontifical Catholic University of Rio Grande do Sul (HSL-PUCRS, Porto Alegre, RS). She held a postdoctoral internship at the Federal University from Jequitinhonha and Mucuri Valleys (UFVJM, Diamantina, MG). She is currently a member of the Brazilian Society for Dental Research (SBPqO) and the Brazilian Society of Stomatology and Pathology (SOBEP). Dr. Marinho's experience in Dentistry mainly covers the following subjects: oral diagnosis, oral radiology; oral medicine; lesions and oral infections; oral pathology, laser therapy and epidemiological studies.",institutionString:null,institution:{name:"State University of Paraíba",institutionURL:null,country:{name:"Brazil"}}},editorTwo:null,editorThree:null},{id:"2",title:"Prosthodontics and Implant Dentistry",coverUrl:"https://cdn.intechopen.com/series_topics/covers/2.jpg",isOpenForSubmission:!0,editor:{id:"179568",title:"Associate Prof.",name:"Wen Lin",middleName:null,surname:"Chai",slug:"wen-lin-chai",fullName:"Wen Lin Chai",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRHGAQA4/Profile_Picture_2022-05-23T14:31:12.png",biography:"Professor Dr. Chai Wen Lin is currently a lecturer at the Department of Restorative Dentistry, Faculty of Dentistry of the University of Malaya. She obtained a Master of Dental Science in 2006 and a Ph.D. in 2011. Her Ph.D. research work on the soft tissue-implant interface at the University of Sheffield has yielded several important publications in the key implant journals. She was awarded an Excellent Exchange Award by the University of Sheffield which gave her the opportunity to work at the famous Faculty of Dentistry of the University of Gothenburg, Sweden, under the tutelage of Prof. Peter Thomsen. In 2016, she was appointed as a visiting scholar at UCLA, USA, with attachment in Hospital Dentistry, and involvement in research work related to zirconia implant. In 2016, her contribution to dentistry was recognized by the Royal College of Surgeon of Edinburgh with her being awarded a Fellowship in Dental Surgery. She has authored numerous papers published both in local and international journals. She was the Editor of the Malaysian Dental Journal for several years. Her main research interests are implant-soft tissue interface, zirconia implant, photofunctionalization, 3D-oral mucosal model and pulpal regeneration.",institutionString:null,institution:{name:"University of Malaya",institutionURL:null,country:{name:"Malaysia"}}},editorTwo:{id:"479686",title:"Dr.",name:"Ghee Seong",middleName:null,surname:"Lim",slug:"ghee-seong-lim",fullName:"Ghee Seong Lim",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y00003ScjLZQAZ/Profile_Picture_2022-06-08T14:17:06.png",biography:"Assoc. Prof Dr. Lim Ghee Seong graduated with a Bachelor of Dental Surgery from University of Malaya, Kuala Lumpur in 2008. He then pursued his Master in Clinical Dentistry, specializing in Restorative Dentistry at Newcastle University, Newcastle, UK, where he graduated with distinction. He has also been awarded the International Training Fellowship (Restorative Dentistry) from the Royal College of Surgeons. His passion for teaching then led him to join the faculty of dentistry at University Malaya and he has since became a valuable lecturer and clinical specialist in the Department of Restorative Dentistry. He is currently the removable prosthodontic undergraduate year 3 coordinator, head of the undergraduate module on occlusion and a member of the multidisciplinary team for the TMD clinic. He has previous membership in the British Society for Restorative Dentistry, the Malaysian Association of Aesthetic Dentistry and he is currently a lifetime member of the Malaysian Association for Prosthodontics. Currently, he is also the examiner for the Restorative Specialty Membership Examinations, Royal College of Surgeons, England. He has authored and co-authored handful of both local and international journal articles. 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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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