The range of pore size with different amounts of HF and ethanol.
\\n\\n
These books synthesize perspectives of renowned scientists from the world’s most prestigious institutions - from Fukushima Renewable Energy Institute in Japan to Stanford University in the United States, including Columbia University (US), University of Sidney (AU), University of Miami (USA), Cardiff University (UK), and many others.
\\n\\nThis collaboration embodied the true essence of Open Access by simplifying the approach to OA publishing for Academic editors and authors who contributed their research and allowed the new research to be made available free and open to anyone anywhere in the world.
\\n\\nTo celebrate the 50 books published, we have gathered them at one location - just one click away, so that you can easily browse the subjects of your interest, download the content directly, share it or read online.
\\n\\n\\n\\n\\n"}]',published:!0,mainMedia:null},components:[{type:"htmlEditorComponent",content:'
IntechOpen and Knowledge Unlatched formed a partnership to support researchers working in engineering sciences by enabling an easier approach to publishing Open Access content. Using the Knowledge Unlatched crowdfunding model to raise the publishing costs through libraries around the world, Open Access Publishing Fee (OAPF) was not required from the authors.
\n\nInitially, the partnership supported engineering research, but it soon grew to include physical and life sciences, attracting more researchers to the advantages of Open Access publishing.
\n\n\n\nThese books synthesize perspectives of renowned scientists from the world’s most prestigious institutions - from Fukushima Renewable Energy Institute in Japan to Stanford University in the United States, including Columbia University (US), University of Sidney (AU), University of Miami (USA), Cardiff University (UK), and many others.
\n\nThis collaboration embodied the true essence of Open Access by simplifying the approach to OA publishing for Academic editors and authors who contributed their research and allowed the new research to be made available free and open to anyone anywhere in the world.
\n\nTo celebrate the 50 books published, we have gathered them at one location - just one click away, so that you can easily browse the subjects of your interest, download the content directly, share it or read online.
\n\n\n\n\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:"9322",leadTitle:null,fullTitle:"Hybrid Nanomaterials - Flexible Electronics Materials",title:"Hybrid Nanomaterials",subtitle:"Flexible Electronics Materials",reviewType:"peer-reviewed",abstract:"Two of the hottest research topics today are hybrid nanomaterials and flexible electronics. As such, this book covers both topics with chapters written by experts from across the globe. Chapters address hybrid nanomaterials, electronic transport in black phosphorus, three-dimensional nanocarbon hybrids, hybrid ion exchangers, pressure-sensitive adhesives for flexible electronics, simulation and modeling of transistors, smart manufacturing technologies, and inorganic semiconductors.",isbn:"978-1-83880-338-4",printIsbn:"978-1-83880-337-7",pdfIsbn:"978-1-78985-651-4",doi:"10.5772/intechopen.83326",price:119,priceEur:129,priceUsd:155,slug:"hybrid-nanomaterials-flexible-electronics-materials",numberOfPages:148,isOpenForSubmission:!1,isInWos:null,isInBkci:!1,hash:"beff6cce44f54582ee8a828759d24f19",bookSignature:"Rafael Vargas-Bernal, Peng He and Shuye Zhang",publishedDate:"June 10th 2020",coverURL:"https://cdn.intechopen.com/books/images_new/9322.jpg",numberOfDownloads:6627,numberOfWosCitations:7,numberOfCrossrefCitations:14,numberOfCrossrefCitationsByBook:1,numberOfDimensionsCitations:24,numberOfDimensionsCitationsByBook:1,hasAltmetrics:0,numberOfTotalCitations:45,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"April 12th 2019",dateEndSecondStepPublish:"September 23rd 2019",dateEndThirdStepPublish:"November 22nd 2019",dateEndFourthStepPublish:"February 10th 2020",dateEndFifthStepPublish:"April 10th 2020",currentStepOfPublishingProcess:5,indexedIn:"1,2,3,4,5,6,7",editedByType:"Edited by",kuFlag:!1,featuredMarkup:null,editors:[{id:"182114",title:"D.Sc.",name:"Rafael",middleName:null,surname:"Vargas-Bernal",slug:"rafael-vargas-bernal",fullName:"Rafael Vargas-Bernal",profilePictureURL:"https://mts.intechopen.com/storage/users/182114/images/system/182114.jpeg",biography:"Rafael Vargas-Bernal received a bachelor's degree in Communications and Electronics Engineering from the University of Guanajuato in 1995, and the degrees of Master of Science and Doctorate in Sciences with Specialty in Electronics from the National Institute of Astrophysics, Optics and Electronics (INAOE) in 1997 and 2000, respectively. Since January 2002, he has been a professor-researcher at the Higher Technological Institute of Irapuato (ITESI) and, particularly since 2006, he has worked in the Department of Materials Engineering where he has established himself as a senior researcher. He has authored 1 book, 16 articles in journals, 42 chapters in books, and about 150 conference articles. He is a member of the National System of Researchers (SNI-Mexico). He regularly serves as a reviewer of scientific articles in RSC Advances, Royal Society Open Science, Materials Science and Engineering B, New Journal of Chemistry, Sensors and Actuators B: Chemical, Applied Surface Science, Journal of Alloys and Compounds, Materials Today Communications, Sensors, Aggregate, Advances in Polymer Technology, Advances in Materials Science and Engineering, IET Circuits, Devices and Systems, Nanoscale, SoftwareX, IEEE Electron Device Letters, IEEE Transactions on Nanotechnology, as well as reviewer of standards in Semiconductor Equipment and Materials International (SEMI). His research interests include telecommunications, two-dimensional materials, nanomaterials, aerospace materials, composite materials, MEMS, advanced materials, gas sensors, and biosensors.",institutionString:null,position:null,outsideEditionCount:null,totalCites:0,totalAuthoredChapters:"9",totalChapterViews:"0",totalEditedBooks:"1",institution:{name:"Instituto Tecnológico Superior de Irapuato",institutionURL:null,country:{name:"Mexico"}}}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,coeditorOne:{id:"297762",title:"Dr.",name:"Peng",middleName:null,surname:"He",slug:"peng-he",fullName:"Peng He",profilePictureURL:"https://mts.intechopen.com/storage/users/297762/images/system/297762.jpeg",biography:"Prof. Peng He is the Duty Director of the State Key Laboratory of Advanced Welding and Joining, China. He has been an Executive Member of the ISO-Welding Standard Committee from 2014 and has been an Executive Member of the International Materials Science & Joining Technologies Committee from 2012. Up to now, he has written 292 papers and 7 books, developed 39 patents, and received 13 awards in materials science. He is currently researching materials processing, micro-joining, and reliability.",institutionString:"Harbin Institute of Technology",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"0",totalChapterViews:"0",totalEditedBooks:"0",institution:{name:"Harbin Institute of Technology",institutionURL:null,country:{name:"China"}}},coeditorTwo:{id:"255004",title:"Dr.",name:"Shuye",middleName:null,surname:"Zhang",slug:"shuye-zhang",fullName:"Shuye Zhang",profilePictureURL:"https://mts.intechopen.com/storage/users/255004/images/system/255004.jpeg",biography:"Dr. Zhang has been a lecturer at State Key Lab of Advanced Welding and Joining since 2017. He is focusing on novel and advanced materials for nanofabrication and nanodevices. He has published forty SCI&EI indexed papers, including ten IEEE conference papers, in IEEE Transactions on Components, Packaging and Manufacturing Technology, Journal of Materials Science: Materials in Electronics, Journal of Alloys and Compounds, and Advanced Materials. Dr. Zhang is the session chair of IEEE NANO 2019 and co-session chair of IEEE 3M NANO 2018 and 2019.",institutionString:"Harbin Institute of Technology",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"1",totalChapterViews:"0",totalEditedBooks:"0",institution:{name:"Harbin Institute of Technology",institutionURL:null,country:{name:"China"}}},coeditorThree:null,coeditorFour:null,coeditorFive:null,topics:[{id:"17",title:"Nanotechnology and Nanomaterials",slug:"nanotechnology-and-nanomaterials"}],chapters:[{id:"71831",title:"Introductory Chapter: Hybrid Nanomaterials",doi:"10.5772/intechopen.92012",slug:"introductory-chapter-hybrid-nanomaterials",totalDownloads:910,totalCrossrefCites:3,totalDimensionsCites:5,hasAltmetrics:0,abstract:null,signatures:"Rafael Vargas-Bernal",downloadPdfUrl:"/chapter/pdf-download/71831",previewPdfUrl:"/chapter/pdf-preview/71831",authors:[{id:"182114",title:"D.Sc.",name:"Rafael",surname:"Vargas-Bernal",slug:"rafael-vargas-bernal",fullName:"Rafael Vargas-Bernal"}],corrections:null},{id:"69106",title:"Electronic Transport in Few-Layer Black Phosphorus",doi:"10.5772/intechopen.89149",slug:"electronic-transport-in-few-layer-black-phosphorus",totalDownloads:681,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"Subjected to an adequately high magnetic field, Landau levels (LLs) form to alter the electronic transport behavior of a semiconductor. Especially in two-dimensional (2D) limit, quantum Hall effect sheds light on a variety of intrinsic properties of 2D electronic systems. With the raising quality of field effect transistors (FET) based on few-layer black phosphorus (BP), electronic transport in quantum limit (quantum transport) has been extensively studied in literatures. This chapter investigates the electronic transport in few-layer BP, especially in quantum limit. At the beginning of this chapter, a brief introduction to the background of LL, edge state, and quantum Hall effect will be delivered. We then examine the fabrication of high-quality FET based on BP and their electronic performances followed by exploring the magnetoresistances of these high-quality devices which reveal Shubnikov-de Haas (SdH) oscillations and quantum Hall effect in BP. Intrinsic parameters like effective mass, Landé g-factor, and so on are discussed based on quantum transport.",signatures:"Gen Long, Xiaolong Chen, Shuigang Xu and Ning Wang",downloadPdfUrl:"/chapter/pdf-download/69106",previewPdfUrl:"/chapter/pdf-preview/69106",authors:[{id:"302575",title:"Dr.",name:"Gen",surname:"Long",slug:"gen-long",fullName:"Gen Long"},{id:"302576",title:"Dr.",name:"Ning",surname:"Wang",slug:"ning-wang",fullName:"Ning Wang"},{id:"302807",title:"Dr.",name:"Xiaolong",surname:"Chen",slug:"xiaolong-chen",fullName:"Xiaolong Chen"},{id:"309794",title:"Dr.",name:"Shuigang",surname:"Xu",slug:"shuigang-xu",fullName:"Shuigang Xu"}],corrections:null},{id:"69619",title:"Synthesis of Three-Dimensional Nanocarbon Hybrids by Chemical Vapor Deposition",doi:"10.5772/intechopen.89671",slug:"synthesis-of-three-dimensional-nanocarbon-hybrids-by-chemical-vapor-deposition",totalDownloads:812,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"Carbon nanomaterials such as graphene, carbon nanotube (CNT), and carbon nanofiber (CNF) have received tremendous attentions in the past two decades due to their extraordinary mechanical strength and thermal and electrical properties. Recently, it indicates that three-dimensional (3D) nanocarbon hybrids overcome the weakness of individual low-dimensional nanocarbon materials and exhibit unique properties among carbon nanomaterials. Efforts have thus been made to acquire synergistic integration of one-dimensional (1D) and two-dimensional (2D) carbon nanomaterials. Meanwhile, chemical vapor deposition (CVD) is a widespread and effective method of fabricating three-dimensional nanocarbon hybrids compared with other synthetic methods. In this case, a number of 3D nanocarbon hybrids are synthesized by using different precursors at diverse temperature, and the nanocarbon hybrids are expected to be a promising choice for various application areas in the future.",signatures:"Hua-Fei Li, Shuguang Deng and Gui-Ping Dai",downloadPdfUrl:"/chapter/pdf-download/69619",previewPdfUrl:"/chapter/pdf-preview/69619",authors:[{id:"247902",title:"Prof.",name:"GuiPing",surname:"Dai",slug:"guiping-dai",fullName:"GuiPing Dai"},{id:"304258",title:"Prof.",name:"Shuguang",surname:"Deng",slug:"shuguang-deng",fullName:"Shuguang Deng"},{id:"310484",title:"Mr.",name:"Hua-Fei",surname:"Li",slug:"hua-fei-li",fullName:"Hua-Fei Li"}],corrections:null},{id:"71932",title:"Hybrid Ion Exchangers",doi:"10.5772/intechopen.92116",slug:"hybrid-ion-exchangers",totalDownloads:634,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"Hybrid ion exchangers are of recent origin in the field of ion exchange chemistry. They have shown excellent chemical, mechanical and thermal stability conversant to both organic and inorganic counterparts. Very recently, new classes of ion exchangers have been studied by combining surfactants and inorganic metal phosphates. This article highlights the salient features of metal phosphates as ion exchangers, various development stages with the modifications, with an emphasis on the recent developments in the field of analytical chemistry, particularly surfactant-based hybrid fibrous and non-fibrous metal phosphates as ion exchangers. Surfactants or surface-active agents when present in the matrix of inorganic metal phosphates not only enhance their ion-exchange capacity but, also the selective adsorption of metal ions. Therefore, these materials are of great importance in industrial and environmental applications.",signatures:"Amita Somya",downloadPdfUrl:"/chapter/pdf-download/71932",previewPdfUrl:"/chapter/pdf-preview/71932",authors:[{id:"267347",title:"Dr.",name:"Amita",surname:"Somya",slug:"amita-somya",fullName:"Amita Somya"}],corrections:null},{id:"70587",title:"Pressure-Sensitive Adhesives for Flexible Display Applications",doi:"10.5772/intechopen.90619",slug:"pressure-sensitive-adhesives-for-flexible-display-applications",totalDownloads:897,totalCrossrefCites:3,totalDimensionsCites:5,hasAltmetrics:0,abstract:"Pressure-sensitive adhesives (PSA) have been used in electronics for not only attachment of two materials but also shock absorption, thermal and electrical conductivity, electromagnetic shielding, and optical property. Optically clear adhesives (OCA) have been used as a core material for optical performance of display. In addition to basic properties of OCA such as adhesion strength, transmittance, haze, and reliability, it has required dielectric constant, gap filling, and anticorrosion according to a substrate. However, the structural and functional changes of flexible display bring challenges to OCA that protects vulnerable components such as thin-film transistor, OLED, and thin-film encapsulation by stress dispersion and adjustment of a neutral plane. At the same time, flexibility and existing properties are essential. In this chapter, the development of components and performance of OCA, and evaluation methods will be discussed.",signatures:"Tae-Hyung Lee, Ji-Soo Kim, Jung-Hun Lee and Hyun-Joong Kim",downloadPdfUrl:"/chapter/pdf-download/70587",previewPdfUrl:"/chapter/pdf-preview/70587",authors:[{id:"189738",title:"Prof.",name:"Hyun-Joong",surname:"Kim",slug:"hyun-joong-kim",fullName:"Hyun-Joong Kim"},{id:"312227",title:"Mr.",name:"Jung-Hun",surname:"Lee",slug:"jung-hun-lee",fullName:"Jung-Hun Lee"},{id:"312228",title:"Ms.",name:"Ji-Soo",surname:"Kim",slug:"ji-soo-kim",fullName:"Ji-Soo Kim"},{id:"315617",title:"Mr.",name:"Tae-Hyung",surname:"Lee",slug:"tae-hyung-lee",fullName:"Tae-Hyung Lee"}],corrections:null},{id:"70330",title:"Numerical Simulation and Compact Modeling of Thin Film Transistors for Future Flexible Electronics",doi:"10.5772/intechopen.90301",slug:"numerical-simulation-and-compact-modeling-of-thin-film-transistors-for-future-flexible-electronics",totalDownloads:745,totalCrossrefCites:5,totalDimensionsCites:6,hasAltmetrics:0,abstract:"In this chapter, we present a finite element method (FEM)-based numerical device simulation of low-voltage DNTT-based organic thin film transistor (OTFT) by considering field-dependent mobility model and double-peak Gaussian density of states model. Device simulation model is able to reproduce output characteristics in linear and saturation region and transfer characteristics below and above threshold region. We also demonstrate an approach for compact modeling and compact model parameter extraction of organic thin film transistors (OTFTs) using universal organic TFT (UOTFT) model by comparing the compact modeling results with the experimental results. Results obtained from technology computer-aided design (TCAD) simulation and compact modeling are compared and contrasted with experimental results. Further we present simulations of voltage transfer characteristic (VTC) plot of polymer P-channel thin film transistor (PTFT)-based inverter to assess the compact model against simple logic circuit simulation using SmartSpice and Gateway.",signatures:"Arun Dev Dhar Dwivedi, Sushil Kumar Jain, Rajeev Dhar Dwivedi and Shubham Dadhich",downloadPdfUrl:"/chapter/pdf-download/70330",previewPdfUrl:"/chapter/pdf-preview/70330",authors:[{id:"153167",title:"Dr.",name:"Arun Dev Dhar",surname:"Dwivedi",slug:"arun-dev-dhar-dwivedi",fullName:"Arun Dev Dhar Dwivedi"},{id:"322076",title:"Dr.",name:"Sushil Kumar",surname:"Jain",slug:"sushil-kumar-jain",fullName:"Sushil Kumar Jain"},{id:"322077",title:"Dr.",name:"Rajeev Dhar",surname:"Dwivedi",slug:"rajeev-dhar-dwivedi",fullName:"Rajeev Dhar Dwivedi"},{id:"322078",title:"Dr.",name:"Shubham",surname:"Dadhich",slug:"shubham-dadhich",fullName:"Shubham Dadhich"}],corrections:null},{id:"69281",title:"Smart Manufacturing Technologies for Printed Electronics",doi:"10.5772/intechopen.89377",slug:"smart-manufacturing-technologies-for-printed-electronics",totalDownloads:1078,totalCrossrefCites:3,totalDimensionsCites:8,hasAltmetrics:0,abstract:"Fabrication of electronic devices on different flexible substrates is an area of significant interest due to low cost, ease of fabrication, and manufacturing at ambient conditions over large areas. Over the time, a number of printing technologies have been developed to fabricate a wide range of electronic devices on nonconventional substrates according to the targeted applications. As an increasing interest of electronic industry in printed electronics, further expansion of printed technologies is expected in near future to meet the challenges of the field in terms of scalability, yield, and diversity and biocompatibility. This chapter presents a comprehensive review of various printing electronic technologies commonly used in the fabrication of electronic devices, circuits, and systems. The different printing techniques based on contact/noncontact approach of the printing tools with the target substrates have been explored. These techniques are assessed on the basis of ease of operation, printing resolutions, processability of materials, and ease of optimization of printed structures. The various technical challenges in printing techniques, their solutions with possible alternatives, and the potential research directions are highlighted. The latest developments in assembling various printing tools for enabling high speed and batch manufacturing through roll-to-roll systems are also explored.",signatures:"Saleem Khan, Shawkat Ali and Amine Bermak",downloadPdfUrl:"/chapter/pdf-download/69281",previewPdfUrl:"/chapter/pdf-preview/69281",authors:[{id:"308939",title:"Dr.",name:"Saleem",surname:"Khan",slug:"saleem-khan",fullName:"Saleem Khan"},{id:"310184",title:"Dr.",name:"Shawkat",surname:"Ali",slug:"shawkat-ali",fullName:"Shawkat Ali"},{id:"310185",title:"Prof.",name:"Amine",surname:"Bermak",slug:"amine-bermak",fullName:"Amine Bermak"}],corrections:null},{id:"71199",title:"Plastic Inorganic Semiconductors for Flexible Electronics",doi:"10.5772/intechopen.91195",slug:"plastic-inorganic-semiconductors-for-flexible-electronics",totalDownloads:870,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"Featured with bendability and deformability, smartness and lightness, flexible materials and devices have wide applications in electronics, optoelectronics, and energy utilization. The key for flexible electronics is the integration of flexibility and decent electrical performance of semiconductors. It has long been realized that high-performance inorganic semiconductors are brittle, and the thinning-down-induced flexibility does not change the intrinsic brittleness. This inconvenient fact severely restricts the fabrication and service of inorganic semiconductors in flexible and deformable electronics. By contrast, flexible and soft polymers can be readily deformed but behave poorly in terms of electrical properties. Recently, Ag2S was discovered as the room-temperature ductile inorganic semiconductor. The intrinsic flexibility and plasticity of Ag2S are attributed to multicentered chemical bonding and solid linkage among easy slip planes. Furthermore, the electrical and thermoelectric properties of Ag2S can be readily optimized by Se/Te alloying while the ductility is maintained, giving birth to a high-efficiency full inorganic flexible thermoelectric device. This chapter briefly reviews this big discovery, relevant backgrounds, and research advances and tries to demonstrate a clear structure-performance correlation between crystal structure/chemical bonding and mechanical/electrical properties.",signatures:"Tian-Ran Wei, Heyang Chen, Xun Shi and Lidong Chen",downloadPdfUrl:"/chapter/pdf-download/71199",previewPdfUrl:"/chapter/pdf-preview/71199",authors:[{id:"312244",title:"Dr.",name:"Lidong",surname:"Chen",slug:"lidong-chen",fullName:"Lidong Chen"},{id:"312245",title:"Dr.",name:"Xun",surname:"Shi",slug:"xun-shi",fullName:"Xun Shi"},{id:"322080",title:"Dr.",name:"Tian-Ran",surname:"Wei",slug:"tian-ran-wei",fullName:"Tian-Ran Wei"},{id:"322081",title:"Dr.",name:"Heyang",surname:"Chen",slug:"heyang-chen",fullName:"Heyang Chen"}],corrections:null}],productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"},subseries:null,tags:null},relatedBooks:[{type:"book",id:"5884",title:"Unraveling the Safety Profile of Nanoscale Particles and Materials",subtitle:"From Biomedical to Environmental Applications",isOpenForSubmission:!1,hash:"5e5811aa0f15ab9d8b6a235e8408875d",slug:"unraveling-the-safety-profile-of-nanoscale-particles-and-materials-from-biomedical-to-environmental-applications",bookSignature:"Andreia C. 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Nanoporous silicon is widely used for separating gas or particle [1–3] and can be applied in biosensors [4], optics [5, 6], tissue engineering [7] and radiotherapy [8]. For those applications, the integration with other components like micropump can produce one complete system. Silicon is chosen for this application because of its physical and chemical stability [9], especially in separating particles due to its biocompatibility and anti-biofouling. Polyethylene glycol (PEG) is used for surface modification for its biocompatibility. The usage of nanoporous silicon membrane is widespread especially in biological filtration. Nanoporous silicon can be combined with micropump, microchannel and microfluidic modules to make a complete device for bioMEMS and LoC applications. There are several methods of pore formation on silicon substrate like electrochemical etching process [10], focused ion beam, electron beam lithography and rapid thermal annealing [2]. Electrochemical etching process is chosen for producing pore on silicon membrane because of its simple experimental setup and easy replication of the pore formation and structure. Recently, the creation of the smallest pore size has been explored to suit various applications. There are various methods that can be explored to vary the pore formation in terms of size and structure of pore silicon [11–17]. The self-adjusting method can create the smallest pore by controlling and manipulating certain parameters during electrochemical etching process, which are current density [18–20], HF concentration [21], time, silicon orientation [22], doping level [23–25], lighting and electrolyte mixture [25]. The characterization of producing nanoporous silicon is discussed in terms of current density, HF concentration, dopant and diluents that influence the formation of pore structure and size of this nanoporous silicon membrane. Field emission scanning electron microscope (FESEM) is used to verify and examine the pore formation due to its capability to visualize the porous silicon structure in nanometer range with higher magnification. The FESEM results also verify the pore formation of porous silicon, whether uniform or non-uniform, and the pore diameters.
Porous silicon can be formed using electrochemical etching technique or anodization process in hydrofluoric solution. Commonly, porous silicon cannot be formed by dipping the silicon in HF solution. But the current flow between two electrodes, which is silicon at the anode and platinum at the cathode in the HF solution, will produce the pores on silicon membrane. Electrochemical etching process is a very simple and economical experimental setup in terms of apparatus and chemical used. Figure 1 shows different experimental setups used in this electrochemical etching process. Figure 1 is the simplest experimental setup, which used one Teflon bath to put the HF solution, and two electrodes were dipped in this HF solution, supplying the current to produce pores. Normally, the silicon is placed in the anode and platinum in the cathode. Various other metals can be used at the cathode. But the metal used can hold it in HF solution without eroding it. Teflon cell is used because it has a high level of acid resistance compared to the glass cell. The benefit of this experimental setup is simple and easy to modify. However, the pores are not uniform for both sides of the silicon due to the inhomogeneity resulting from lateral potential drop.
Cross section of a lateral electrochemical etching cell [
Meanwhile, Figure 2 shows the second type of electrochemical etching cell in the single-cell approach using a back-side contact. A metal contact is made at the back side of wafer and sealed with o-ring so that only front-side sample will be exposed to anodize electrolyte. This type of experimental setup is well suited for the front using two cells containing electrolyte, and silicon is placed in the middle of the cell. Furthermore, the cell that leads to good uniformity in porous silicon layers and the simplest interpretation of current-voltage characteristics is most commonly used and offers a good control of thickness and porosity. This cell is also well suited for the front-side illumination of the sample during anodization because of illumination that will affect the pore formation during the process [22].
Cross section of a conventional single-tank cell [
The third type of cell is the double-tank cell using an electrolytic back-side contact. Figure 3 shows the equipment used in this process, which consists of two half cells in which platinum electrodes are immersed and the silicon used to separate and isolate the two cells. Both cells used HF solution for electrochemical etching for polished and a back-side contact. The chemical pump is used to circulate the electrolyte solution to remove the gas bubbles generated using anodic reaction and maintain the concentration of HF solution in the cell tank. A good and uniform pore can be obtained using symmetrical and large platinum plates as the cathode and the anode. These two platinum electrodes are connected to power supply, and the current flows from one half to the other through silicon membrane. The back side of silicon membrane acted as a secondary cathode where the proton reduction takes place leading to hydrogen evolution, while the front side of the wafer acted as a secondary anode to form porous silicon.
Cross-sectional view of a double-tank cell [
Silicon is the material that is difficult to dissolve in HF solution except with the aid of the flow. Silicon reacts with HF solution to dissolve the H and F during power supply. In general, some solvents may be used to produce a hole in the surface of the silicon. Nanoporous silicon is formed using ethanoic HF solution that is a mixture between ethanol and HF. However, the organic solvent may also be used to obtain porous silicon like
where h+ and e− change between hole and electron and λ is a number of charge change at the first stage.
This equation is also used by some researchers [31–34]. But other equations have been proposed in the process of liquidation in accordance with the method of surface oxidation of silicon, exchange hole and electrons that become a source of divalent silicon on the oxidation level [35]. Figure 4 shows that model reaction of p-type silicon dissolution in HF solution is used. Ion dissolution measures the current flow caused by the electrochemical etching process that makes the transfer between electrons and holes. The ion is struggling to move in order to break the bonds of Si-O, Si-F and Si-H during the process. Thus, the idea for the formation of pores involves current densities studied to make the resulting hole narrower and straight [19, 36].
Chemical mechanism of electrochemical etching [
Pore formation involving the current density is discussed in Figure 5. During electrochemical etching process, the holes will be placed on silicon surface. When a high current density is given, the hole will focus and gather at the boundary layer between silicon crystal and HF solution. So, the electrochemical dissolution of silicon in HF will generate very smooth surface. This process is called electropolishing. On the other hand, if the low current density is applied, a lot of fluoride ions will be placed on the silicon surface rather than the holes. In this situation, etching process is limited because of the lack of hole in silicon surface during ion dissolution. The dissolution rate of fluoride ion to migrate to the electric field is limited because of the lack of hole. So, if the surface is rough, the hole will force out to make a large hole by the uneven pit surface [32].
The boundary layer between the silicon crystal and HF solution during ion transfer processes [
Briefly, the electrochemical etching process is a process that involves the dissolution of the ion to form pore and electropolishing. Ion dissolution process is dependent on the current density during the electrochemical etching process. The current density also affects the pore structure like spongy or columnar structure [33]. The current density is also among the parameters that can be manipulated to produce the perfect pore structure. Pore formation is influenced by the current density based on graph IV to study either the formation of pores or electropolishing process. Graph IV involving current and voltage used in the formation of pore is shown in Figure 6. For each pore formation process and polishing silicon electrochemical reaction has a different equation is divided anode depends on the ability of electrode and HF solution [11]. At low current density, pore silicon can be formed. But the pore was only on the surface of the membrane and structured like a sponge. The current process called simple force of transition forms either pores or electropolishing.
Graph of current density versus different potentials for pore formation and electropolishing [
Theoretically, the current density affects the pore formation in silicon. The current will create a line at the end of the pore using space-charge region (SCR) as shown in Figure 7 [35]. When the electric field is strong enough to build pore with the given current flow, oxide forms on the surface of the pores. The oxide layer will be dissolved by the electrolyte solution and forms pores below the existing holes. When the coating is completely dissolved by the electrolyte, the existing electric field produces a flow line to another, and this process will be repeated. Thus, the current flow is capable of dissolving silicon and produces nano- or micro-sized pores depending on the dopant density either p or n. Dissolution will occur two times at the same area as there are currents to break down and encourage the maximum pore formation in the orientation <010> or <001> [35, 36].
Existence of SCR and current lines bent toward pore tip at the higher electric field strength [
However, the straight pores are influenced by other factors such as time and current density etching. The hole formation can be varied by manipulating etching time technique, which is called the current burst model. The current burst is conditioned when the current model is still reacting to the dissolution of the silicon surface. When no current burst model, the formation of a new model of current burst occurred and attacked the area around the edge of the pore caused by inhomogeneity in time and space [38]. When the etching time is increased, current flows in any area of pore tips occur. Figure 8 shows how the region acts current burst in any possible area during pore formation.
Forming a hole caused by the formation of a new model of current eruption which dissolves holes in different orientations [
Electrochemical etching is a self-adjusting technique that manipulates several parameters to get various pore structures and sizes. The dopant-type silicon orientation and photoluminescence factor will affect the pore structure as shown in Figure 9. Pore-shaped structure inclined (b) due to the orientation of silicon. Oriented silicons 110 and 111 produce an inclined hole. In order to produce a vertical, straight or columnar pore structure, orientation of silicon 100 can be formed using n-type dopant with back-side illumination. Figure 9 represents some symbols such as n+, n−, p+ and p− representing the dopant used. The symbols + and − represent the dopant level, which is the amount of charge carriers that exist on the silicon. Symbol + has high density of n/p dopant compared to charge carriers, while the symbol −, a sign of the type of dopant n/p, is less than the charge carriers. Different silicon pore structures can be produced by changing these parameters.
Illustration of pore formation based on dopant factor [
The mechanism of dopant used that affects the formation of the pore structure is discussed. N-type silicon (phosphorus) has the ability to build vertical pore structure, while the p-type silicon (boron) produces uneven pore structure. This is due to the p-type silicon, which does not have a mechanism to control the accumulation of charge carriers to disperse the maximum pore anisotropic silicon and passivate the walls of the hole during the electrochemical etching process. So, pore is difficult to form using this type of dopant [40]. In contrast, the n-type silicon is efficient in collecting minority charge carriers with the help of illumination. Illumination acts as a booster for the formation of a straight channel pore. In addition, the pore wall dissolution spontaneously passivated on dissolution of consequences of the reduction of the hole [41]. Based on the properties of dopants, some chemical reaction model to explain the formation of pores is influenced by the band gap caused by confinement charge during the formation of a small hole. Interstitial concentration decreases, further moving charges in the silicon structure [42]. The charge moves on the surface of the silicon dopant.
Dopant acts as impurities for semiconductor to improve the conductivity of semiconductor materials. The use of doping will facilitate the pore formation during etching process [43]. The difference of the two dopants is having a surplus or one less valence electron. Silicon without dopants also has the same number of electrons and holes. When it comes to the surface conductivity of silicon, the silicon resistance is lower because the conductivity is inversely proportional to the resistance of silicon. The conductivity depends on two parameters, namely, the concentration of charge carriers either electrons or holes and agility carrier. During electrochemical etching process, the reaction of Pt at cathode electrode makes a very small electron movement to balance the charge between silicon and Pt. The dopant will affect pore formation based on valence band on dopant to the electrolyte solution. Valence band is very important to make the charge carriers to the electrode erosion. P-type silicon is a majority carrier. Even without bias, the transport rates of the hole are small to move above the silicon surface. When there is positive bias applied to the silicon electrode, the barrier between the charge transports diminishes, and the valence band of the hole becomes focused onto the surface of the interface. In this situation, this kind of bias terms is used in semiconductors. The majority carriers are electrons, which are n-type silicon.
N-type silicon is exposed to lighting to produce more vent holes formed in the silicon. This is because the light will generate electron-hole pairs near the silicon surface and sweep vent holes on the surface of silicon. Thus, the n-type silicon can produce a straight hole if lighting is given continuously to the silicon surface. Dopant silicon obstacles will affect the formation of the hole because the structure depends on the homogeneity and the size of the hole depends on the current density and time [43]. To produce a sharp, straight or columnar pore structure by using the space-charge region, high lighting and dopant silicon whether n-type or p-type are required [44]. The use of low resistance dopant material will produce a star-shaped hole and a structure, which is not straight even when using the same experimental procedure [37]. Resistance dopants also affect the pore size based on the density of dopant. Silicon with a pore size of 2–4 nm can be formed using silicon-type n and p dopants that have low and medium density, silicon with pore size of 5–50 nm can be generated using a dopant with high density and silicon with pore size of 50 nm to several 10 m can be formed using a dopant with medium density [45]. This is because the mechanism of formation of the vent holes needs to justify the dissolution of the ion [19].
Pore formation depends on the dopant density. Figure 10 shows the schematic of pore formation mechanism, which starts with the orientation of crystallization of silicon. Figure 10(a) shows that the (100) crystallographic face contains strained Si–H bonds, and it tends to be more disposed due to dissolution compared to other faces. In contrast, the (111) face contains Si–H bonds that are more stable and perpendicular to the surface. The differential reactivity of the crystal faces leads to crystallographic pores in order to propagate primarily in the <100> direction. Figure 10(b) shows that high radius of curving at the tip, especially at the bottom, of a pore generates a region for enhanced electric field, which can attract valence band holes. Figure 10(c) shows that the space-charge region is a region in which carriers are depleted due to band bending while interfacing between silicon and electrolyte. Band bending increases by decreasing the dopant density, so this mechanism is a primary determinant for macropore size formation especially for low-doped n-type Si. In Figure 10(d), as the diameter of a silicon filament decreases, the resistance for transporting the valence band holes increases. At a critical filament diameter (typically a few nm for p-type silicon), injection of the hole into the solution becomes more favorable, and holes do not propagate further down the length of the nanowire. This mechanism is responsible for the lack of electrochemical dissolution of a microporous layer when it has been formed. Figure 10(e) shows that the result of increasing the band gap from the quantum confinement excludes the valence band holes from the smallest regions of the porous silicon matrix. (f) If there are no fluoride ions available at the silicon/solution interface, silicon oxide forms at the interface. Valence band holes are then excluded from this region, and they continue to oxidize the silicon/porous silicon interface. This causes pore widening and produces electropolishing porous layer [46].
Schematic of pore formation mechanism in porous silicon [
In short, the pore formation is influenced by many factors for producing holes of various sizes and shapes. The details on pore formation will be discussed further by characterization of these parameters.
Double-sided polished 400 μm thick silicon nitride specimens with <100> orientation were prepared by cutting the substrate to a dimension of 2.54 × 3 cm. The silicon substrates are then cleaned with the standard cleaning procedure. The substrates are dipped in acetone and methanol for 5 minutes in an ultrasonic bath. Then, the samples were dipped into 10% hydrofluoric acid (HF) for 1 minute to remove the stain on the silicon surface. The samples were then rinsed using deionized (DI) water and blasted with nitrogen gas to dry the samples. Finally, the samples were put on a hot plate with the temperature set to 120°C for 15–20 minutes for the hard-bake process to ensure no water remains on the silicon surface.
The silicon samples then undergo the lithography process to pattern the square frame on the substrate. The positive photoresist AZ 4620 was first coated on the silicon substrate using a spin coater with a setting of 500 rpm for 10 seconds and then 2000 rpm for 20 seconds. Next, the substrates were put on a hot plate at 120°C for 1 minute. Only then will the samples be ready for the lithography process. The mask aligner Karl Suss MJB 3 was used to transfer the square pattern on a mask to the silicon substrates. Then, the samples were exposed to UV light for 90 seconds. Afterwards, the substrates were dipped for 4 minutes in an AZ 400K developer to develop the square patterns. After that, the samples went through a hard-bake process for 15 minutes. Next, they were dipped into a buffer oxide etch (BOE) solution to remove unwanted nitrides at the opening frame. The schematic of BOE process is shown in Figure 11. The Teflon clamper is used to hold the silicon nitride for this process. The BOE solution is put on the silicon surface for 4 hours in room temperature to produce a mask for KOH etching process.
Buffered oxide etchant process to remove unwanted photoresist.
Then, the substrates were dipped in acetone again to remove the photoresist. For thinning the silicon substrates, 45 g of potassium hydroxide (KOH) pallet was mixed well with 55 ml DI water to make a 45% concentration solution. Next, the KOH solution was put into a beaker containing just DI water. The double-boiling method was used for this etching process as shown in Figure 12. This is a repeating process to get the silicon membrane thickness of 5 μm. The KOH process is a very crucial part to get the smoothed surface roughness. The admixture of 45% with isopropyl alcohol (IPA) will improve the surface roughness of the membrane [47]. Furthermore, IPA acts as a catalyst to increase the etching rate during bulking away of the silicon substrate. The cross section of silicon membrane is shown in Figure 13. The thickness of the membrane is 35 μm after immersing the silicon in KOH solution for 6 hours. So, to obtain a thickness of 5 μm, the silicon will be immersed in KOH solution.
Schematic of double-boiling technique for KOH etching process.
The cross section of silicon membrane after 6 hours of KOH etching process.
The silicon membrane needs to be handled carefully because the thin membrane is easy to break during the electrochemical etching experiment stage. Electrochemical etching process starts after the membrane is immersed in electrochemical bath in order to remove nitride that remains on the silicon surface using BOE solution. The silicon membrane must be in hydrophobic condition before the process starts. If not, silicon membrane will be dipped again in 10% HF to remove all stains on silicon membrane. Any impurity will affect the pore formation throughout the process. An illustration of the process flow is shown in Figure 14.
Fabrication process for producing nanoporous silicon membrane.
Electrochemical etching was performed to form pores on the silicon membrane surface using hydrofluoric acid (HF) solution [21, 39, 46, 48]. The experimental setup was shown in Figure 15 by supplying a constant current between two electrodes immersed in a Teflon cell containing an aqueous solution of HF or diluted HF. An ethanol and HF solution is commonly used among researchers as an electrolyte aqueous solution for electrochemical etch. Ethanol will act as the surfactant in reducing the hydrogen bubble throughout the process [46, 48]. Fluorescence light is put facing the silicon membrane during electrochemical etching process as a catalyst in producing a well-forming pore during pore formation mechanism [15, 17]. Furthermore, photoluminescence is used to assist an electron to attack silicon surface in order to produce the best pore distribution. So, the pore formation will become more uniform toward the end of the process. Finally, FESEM is used to observe and verify the pore structure of the silicon membrane.
Electrochemical etching process.
A few experiments have been conducted to study the effect of HF concentration, current density, doping and diluents to the pore formation. The pore formed will be inspected and examined under FESEM Supra VVP5. The pore structure and pore size are examined, and each effect will be characterized in this part.
The first study is on hydrofluoric acid concentration. The experimental setup used various HF concentrations by differentiating the volume ratio between HF solution and ethanol. This section will discuss the pore formation and size after electrochemical etching process. Forty-nine percent of HF and ethanol are mixed in Teflon beaker with different volume ratios, which are 3:7, 5:5, 7:3 and 9:1. The platinum is placed at the cathode, and undoped silicon is placed at the anode. The current density has been set at 25 mA/cm2 for 20 minutes. 3 mL of ethanoic HF will be put in the single-tank cell. During the process, the top membrane was faced with photoluminescence of 5 W. After 20 minutes, the silicon has been inspected under FESEM Supra VVP5 to examine the pore size and structure on silicon membrane. Figure 16 shows that the pore has been formed after electrochemical etching process. FESEM shows that low concentration of HF produces a large pore size compared with high concentration of HF. This is because high-volume HF contains more fluoride ion.
The pore structure of a different volume ratio of HF/ethanol.
The second experimental setup will study the pore formation by varying time. Other samples were put in this single-tank cell and electrochemical etching process was performed for varying time (30, 40 and 50 minutes). The result will be examined under FESEM to study the pore size. The average pore sizes are counted by inspecting this sample under Atomic Force Microscope (AFM). The AFM is able to count the pore size by grain/pore analysis. Then, the data will be analysed to study the effect of HF concentration and time to the pore formation. Figure 17 shows the relation of HF concentration to the pore size at variant time of immersed silicon in electrolyte solution. The graph shows that the pore size becomes wider at low HF concentration. Furthermore, time taken for electrochemical etching process is one of the factors that make the pore become wider. Low HF concentration produces non-uniform pore structure. This pore formation mechanism starts with migration between electron and holes in order to attract charge carrier when applied in electric field. The migration of electron and holes happens in competition between Si–O, Si–F and Si–H bond formation. The small amount or volume ratio of HF in electrolyte solution will generate the oxide. The oxide layer is generated on the silicon surface. F− ions are trying to attack rapidly to avoid oxide layer to grow and to avoid the water molecules to take over the role of nucleophile. The lack of F ions makes the oxide unremovable from the silicon surface. It is because the insulated oxide terminates the pore propagation [46].
The effect of HF concentration in terms of pore size at different times.
Table 1 shows that the pore size range was measured under FESEM. The effect of volume ratio of HF and ethanol during electrochemical etching process is studied by measuring the pore size. It has been found that the HF volume is a key in order to form nanosized pores. The highest HF amount will reduce the thickness of space-charge layer and increase the pore-tip current density [39]. The high volume of HF can prevent the native oxide growth throughout the process because dissolution silicon oxide rate is increased by increasing the HF volume, which automatically increases the critical current density at the covered oxide layer on silicon. In this case, the small pore structure is formed by increasing the HF concentration.
Time (minutes) | Pore diameter | |||
---|---|---|---|---|
3:7 | 5:5 | 7:3 | 9:1 | |
20 | 60–200 nm | 30–50 nm | 9–19 nm | 5–10 nm |
30 | 220–360 nm | 40–100 nm | 16–34 nm | 13–25 nm |
40 | 200–500 nm | 50–150 nm | 57–101 nm | 17–30 nm |
50 | 600 nm–1 μm | 50–300 nm | 58–120 nm | 30–50 nm |
The range of pore size with different amounts of HF and ethanol.
The immersed time also affects the pore formation. Table 1 shows the longest immersed time that makes the pore diameter wider. 20 and 50 minutes as immersed time are compared. The result shows that 20 minutes of the uniform pore formation produced is compared to 50 minutes. It is because the longer immersed time makes the pore become wide due to the breakage of the pore wall.
The pore size formed in different HF concentrations using dopant boron has been studied [21]. For the dopant silicon, pore size depends on dopant concentration to produce variant size of pore. For example, mesoporous (5–50 nm) is produced using highly doped level. Meanwhile, a macroporous (50 nm–10 μm) can be produced using medium-doped level and microporous (2–4 nm) using low dopant. Figure 18 shows that the finding of pore formation using highly doped boron has been inspected under FESEM and the visual color observation on silicon surface. A volume ratio of 3:7 produces a pore size of 10 nm; 4:6, 8 nm; and 6:4, 3 nm. From the result, the HF concentration can affect pore formation for various silicon substrates, regardless of their being doped or undoped.
Effect of pore formation for variant HF concentration using p-type silicon [
Current density is one of the factors that affect the pore formation. The previous experimental setup demonstrates that the HF concentration affects the pore formation in terms of pore size. This experimental setup examines the current density affecting the pore structure, etching rate and also pore size. This study used the aforementioned experimental setup using p-type silicon membrane with resistivity of 1–100 Ωcm. The first set of experiments is to gauge the etching rate of porous layer by manipulating the current density. The current density is varied from 5 to 30 mA/cm2 using ethanoic HF as electrolyte solution. The porous layer is measured using FESEM by cutting the silicon membrane to get the cross section of porous layer. The silicon membrane is immersed in ethanoic HF solution for 1 hour. A 5 mA/cm2 current density gives an etch rate of 12.6 nm/h, while a 30 mA/cm2 current density gives an etch rate of 1.3 μm/h. It was observed that etch rate increases linearly with the applied current, as illustrated in Figure 19. In this experimental setup, there are certain parameters that have been fixed in order to gauge the sole effect of current density on the etch rate, which include photoillumination, HF concentration, distance between anode and cathode and stirring time.
Correlation between the porous layer etching rate and current density in ethanoic HF solution.
Ethanoic HF electrolyte solution etching rate is very slow. In contrast, the HF solution has a quick etching rate. The etch rate of μm/h is observed for current density changing from 5 to 20 mA/cm2 for 5% HF electrolyte solution [19]. The ethanoic HF shows the same trend graph between etching rate and current density. However, the ethanoic HF etch rate became slower due to the effect of ethanol which acts as surfactant in decreasing the hydrogen bubble [20, 21].
Next, the effect of current density to the pore size is studied by grouping current density by three, which is the low current density (5–30 mA/cm2), medium current density (60–100 mA/cm2) and high current density which is set at 200 mA/cm2 upwards. Electrochemical formation of silicon membrane is observed within this current level.
The pore size for various current densities has been plotted in Figure 20 for different current density levels used for electrochemical etching process. The pore size is less than 30 nm for different current densities applied. The current density that has less effect on the pore size has been observed due to the doping level effect. The p-doped silicon substrate has been used to perform this electrochemical etching process. From previous studies, pore size was affected by concentration of HF solution [14] and doping level [22, 23].
The size of pore by variation of current density.
Furthermore, the effect of current density to the pore structure is studied by varying the current density. This experimental setup is used to study the cross section of porous layer. The low and medium current densities that produce spongy porous silicon layers have been observed as shown in Figures 21 and 22. For filtering particle use, the columnar silicon structure is the most appropriate structure to confirm that all particles can be penetrated through the silicon membrane without any clogging in the middle of separating process.
Scanning electron micrographs (SEM) of porous silicon for p-type doped <100> silicon [
Scanning electron micrographs of porous silicon for n-type doped <100> silicon [
The dissolution process is affected by current density during electrochemical etch. Usually, pore formation mechanism begins with the migration of electron and holes in order to attract charge carriers by applying electric field. The chemistry reaction that occurs on the silicon surface involves the competition between Si–O, Si–F and Si–H bond formations [24].
Pore formation is formed by the number of holes on the silicon substrate. It enables to align themselves toward the chemical reaction to follow the trend of current line according to the high current density [25, 26]. The strong electric field can be gained by high current density that tries to utilize a polarizing effect on the substrate. Holes intend to gather at defective surface site. Based on an electron excitation, silicon or dopant atom is able to move into the lattice or non-lattice sites of the silicon crystallites.
The F− ions in the electrolyte aqueous solution are encouraged to transfer to the silicon substrate, with the succeeding reaction resulting in dissolution. These holes prefer to gather ions at the pore-tip border in silicon bulk because of the low potential energy as compared to the wall area [8, 27]. Figure 21 shows the porous layer under different current densities and time immersed to HF solution by varying the dopant density. Highly doped p-type silicon is able to produce the columnar porous layer. Meanwhile, n-type silicon is capable to produce columnar structure using high current density at low to medium dopant density.
Doping can be affected by pore structure of silicon, changing from being undoped to being doped to either phosphorus or boron, as shown in Figure 23. The pore structure is observed by varying the silicon substrate which is undoped, phosphorus doped and boron doped. Undoped silicon membrane is used as an indicator to verify the doping effect. It shows that the square pore structure can be formed on silicon membrane surface. Undoped silicon formed a scattered pore with different sizes. But phosphorus-doped silicon observed the irregular pore formation. The circular pore shape can be formed when irregular shape breaks the existing pore structure and finally forms a larger pore. For this matter, it was observed that the immersed time affects the pore formation. However, the immersed time will not affect to the doped silicon bulk because the doped level can determine the range of pore size [14, 18, 19].
Shape of porous on different doping.
The effect of time on pore structure is studied during immersion of silicon substrate in HF electrolyte. The pore size increases consistently when increasing immersed time for undoped silicon substrate as shown in Figure 24. In order to gauge the sole effect on doping type, the amount of HF, distance between anode and cathode and stirring rpm were fixed. For this setup, pore formation for boron- and phosphorus-doped silicon substrate is not affected by time. The pore size with range of 12–20 nm has been formed for doped silicon substrate. The pore size diameter has been affected by doping density. As aforementioned, the doping density can be used to categorize the pore size diameter which is mesoporous, microporous and macroporous that has been classified by International Union of Pure and Applied Chemistry (IUPAC).
Pore formation by varying immersed time during electrochemical etching process.
The surface morphology of silicon membrane is discussed in this part to examine the effect of alcohol to the pore formation. Methanol, ethanol and propanol are used in this experimental setup. The pore formation after electrochemical etching process is observed when a current density of 25 mA/cm2 is supplied for 30 minutes. The quantity of holes in electrode surface and the diffusion of fluoride ion will control the mechanism of pore formation. The passivation of pore wall can be boosted by electric field supplied during the pore formation [12, 14, 49]. In this experimental setup, three types of silicon substrate are used, namely, undoped (>80 Ωcm), n-type (resistivity 0–100 Ωcm) and p-type (resistivity 0–100 Ωcm).
Figures 25–27 show the effect of alcohol diluents for variant silicon substrate. It indicates that pore formation not solely depends on the alcohol diluent, but the dopant also gives the effect too. It has been examined that p-type silicon substrate is hard for pore creation compared to others which are undoped and n-type silicon substrate. This is because of the disability of p-type substrate to control the charge carrier collection at the pore tips for anisotropic dissolution of silicon. So, ion can hardly attack the silicon during the pore formation [40]. Besides that, n-type silicon substrate is more efficient to collect the charge carrier with the assistance of photoluminescence to promote columnar pore structure due to the depletion of holes during pore passivity against dissolution [41]. P-type silicon substrate is suggested to use high current density to get the columnar and well-ordered pore structure [33].
The pore structure for the mixture of HF + methanol as electrolyte solution: (a) undoped, (b) n-type (c) p-type.
The pore structure for the mixture of HF + ethanol as electrolyte solution: (a) undoped, (b) n-type and (c) p-type.
The pore structure for the mixture of HF + propanol as electrolyte solution: (a) undoped, (b) n-type and (c) p-type.
In the first part, methanol and 49% hydrofluoric acid that are mixed become electrolyte solution. Under FESEM inspection shown in Figure 25, it is found that star-shaped pore is observed using undoped silicon substrate with less than 40 nm pore size. Meanwhile, non-uniform pore is examined on n-type substrate with less than 40 nm pore size. The pore is formed on the undoped and n-type silicon surface. However, pore is not observed on p-type silicon substrate due to its mechanism, which is hard to control and collect the charge carrier as mentioned before [50].
In the second part, electrolyte solution is changed to the mixture of hydrofluoric acid and ethanol with the aforesaid parameters. As shown in Figure 26, pores are formed on all silicon surfaces with variant pore structure and uniformity. An irregular-shaped pore with 150 nm size is observed on undoped silicon substrate. Then, the irregular-shaped pore with circular pore structure is examined on n-type silicon substrate. According to FESEM, the circular pore has larger size compared to irregular-shaped pore due to its breakage during the process. Besides that, an irregular shape is observed with well-ordered pore on the p-type silicon membrane surface.
In the third set of experiment, the mixture of propanol and hydrofluoric acid as electrolyte solution is used. The current density is set at 25 mA/cm2 for 30 minutes for each silicon substrate. The pore formation becomes unstable for the three silicon substrates. The undoped silicon substrate gives non-uniform pore structure. It is the same with n-type substrates which observed the irregular shape plus the bad pore structure. Then, for p-type substrate it is observed that pore cannot be formed well in electrolyte aqueous solution. Figure 27 shows a micrograph of the structure of pore when using this solution.
Based on a few experiments shown, alcohol diluents affect the pore formation. By altering this electrolyte aqueous solution, the variation of pore-like circular and star-shaped pore structures has been explored in this setup. Besides, in a mixture of HF and propanol, it is difficult to identify clearly the pore structure using this electrolyte solution. Normally, alcohol diluents are called as amphiphilic surfactants. The amphiphilic surfactants are hydrocarbon-based surfactants that are absorbed on silicon surface with their non-polar tails attached on hydrophobic silicon surface [40]. The shortest hydrocarbon chain is methanol, which results nearly in well-ordered pore structure. Furthermore, variant diluents, whether organic or nonorganic, can alter the pore structure. An organic surfactant like DMF and Tetramethylammonium hydroxide (TMAH) also gives a different shape [51].
The combination of HF and ethanol is the most stable due to the sharp pore structure and formation [52]. On the other hand, the worst pore formation is observed using the mixture of propanol and hydrofluoric acid. The highest etching rate can be observed using propanol due to the fastest etched rate which is 20 nm/minute by inspecting the porous cross section. Even though faster time produces pore structure, the pore is difficult to observe using these diluents on the silicon substrate surface. The surface roughness also can be inspected to observe the pore structure on the silicon surface [25].
A star-shaped pore structure is studied to find out whether this pore structure can be replicated again. This process is conducted to optimize this parameter whether star pore can be formed. The aforementioned parameter is used for this experimental setup. The immersed time is varied for each 10-minute start, from 20 to 50 minutes. In Figure 25, star-shaped pore structure was formed in this electrolyte aqueous solution with aforementioned parameter. The well-ordered pore is formed in immersed time between 30 and 50 minutes. However, wide star shape is formed by increasing immersed time due to pore breakage. The pore structure becomes wider as shown in Figure 28 by increasing immersed time.
The pore formation by varied immersed time for ethanol HF + methanol solution.
Pore formation that can be varied by manipulating parameters like dopant, current density, HF concentration and diluent is discussed in this topic. This technique is called a self-adjusting technique because the ion will move by itself to produce various pore structures. The pore can be used in various applications like filtration system, biosensor and microfluidic modules. For filtration system, the columnar pore structure gives the most advantages to ensure the particle can be separated efficiently. The pore size can be varied depending on the size of particles to be sorted out. According to this study, the electrochemical etching process is a very easy technique in producing pore due to its simple experimental setup and the chemicals used.
Recently, in computer networks the numbers of intrusions have grown extensively, and many new pirating tools and intrusive methods have appeared. To save the security of computer systems, several solutions have been identified like intrusion detection systems (IDS) which it is the mean solution to deal with suspicious activities in a network [1].
Using IDS tools, the presence of imperfect information greatly influences the response data under non-suitable as a medium for decision-making. Uncertainty is presented as imperfect data, the variability of the data that resides in the random nature of the information due to the heterogeneity of data sources, vagueness and incompleteness of data due to the lack of useful data [2]. Thus, fuzzy clustering as a robust artificial intelligent method has been successfully employed to reduce the amount of false alarm generated by the detection process and separate the overlap between normal and abnormal behavior in computer networks [3].
Hence, we use two intrusion detection datasets CTU-13 and UNSW-NB15 which contain varieties of intrusions, that we combine into one homogenous dataset and then we apply our ML model based on the Fuzzy C-Mean (FCM) clustering algorithm. We choose Microsoft Azure Blob Storage to load our datasets on.
This paper addresses the problem of generating application clusters from the network intrusion detection datasets. The Fuzzy C-Mean (FCM) clustering algorithms were chosen to be used in building an efficient network intrusion detection model. The paper is structured as follows: Section 2 provides related work of IDS using Big Data techniques, Section 3 introduces brief introduction about intrusion detection, Section 4 presents the used datasets, the proposed system and its components, Section 5 illustrates the evaluation metrics and results of the tested system, finally, Section 6 provides conclusions and further development of future work.
Several works of IDS using Big Data techniques exist. Jeong et al. [4] indicate that Hadoop can solve intrusion detection and big data issues by focusing specifically on anomalous IDSs. The experience of Lee et al. [5] with Hadoop technologies shows good feasibility as an intrusion detection instrument because they were able to reach up to 14 Gbps for a DDOS detector. M. Essid and F. Jemili [6] have combined and eliminated the redundancy of the alerts bases KDD99 and DARPA, they used Hadoop for data fusion. Besides, R. Fekih and F. Jemili [7] used Spark to merge and remove the redundancy of the three alerts bases KDD99, DARPA and MAWILAB. The main objective was to improve detection rates and decrease false negatives. Terzi et al. [8] created a new approach to unsupervised anomaly detection and used it with Apache Spark on Microsoft Azure (HDInsight21) to harness scalable processing power. The new approach was tested on CTU-13, a botnet traffic dataset, and achieved an accuracy rate of 96%. M.Hafsa and F.Jemili [9] created a new approach to intrusion detection. They used Apache Spark on Microsoft Azure (HDInsight21) to analyze and process data from the MAWILAB database. Their new approach achieved an accuracy rate of 99%. Ren et al. [10] created a new approach to unsupervised anomaly detection using the KDD’99 base to analyze and process the data, they achieved a low detection rate. Rustam and Zahras [11] compared two models, one supervised (the Support Vector Machine SVM model) and the other unsupervised (Fuzzy C-Means FCM) to analyze, process, and detect KDD’99 database intrusions. They found that SVM achieved an average accuracy rate of 94.43%, while FCM achieved an average accuracy rate of 95.09%. In this work, we propose an Apache Spark-based approach to detect intrusions. The goal of our system is to provide an efficient intrusion detection system using Big Data tools and fuzzy inference to treat uncertainties and provide better results.
CTU-13 consists in a group of thirteen scenarios that each run a specific botnet performed in a real network environment. Each scenario includes a botnet pcap file, a tagged NetFlow file, a README file with the capture timeline, and the malware run file. The NetFlow (network flow) file is based on bidirectional flows that provide information about the communication between a source (a client) and a destination (a server). This dataset includes three types of traffic with a different distribution: Normal, botnet (or Malware), and background:
The following Figure 1 presents the distribution of experimental data for CTU-13 data set:
Attack categories in CTU-13.
UNSW-NB 15 is a dataset that was created in an Australian Cyber Range Lab using an IXIA PerfectStorm tool to extract a hybrid of realistic modern natural activities and contemporary synthetic attack behaviors generated by network traffic. This dataset contains 49 features are categorized into five groups and which are explained in [17, 18].
The following Table 1 represents the attack types which are classified into nine groups.
Types | Description |
---|---|
The attacker attempts to cause a program or network suspended by feeding it the randomly generated data. | |
It penetrates the web applications via ports (port scan), web scripts (HTML files), and emails (spam). | |
A technique in that a system security mechanism is bypassed to access a computer or its data. | |
An intrusion which attempts to make a network resource or a server unavailable to users, generally by temporarily suspending the services of a host connected to the Internet. | |
It takes advantage of a glitch, bug, or vulnerability to be caused by an unintentional behavior on a network or a host. | |
A technique establishes against every block-cipher using a hash function to collision without configuration of the block-cipher. | |
It gathers information about a computer network to evade its security controls. | |
The attacker penetrates a slight piece of code starting from a shell to check the compromised machine. | |
The attacker replicates itself in order to advance on other computers. Frequently, it uses a computer network to spread itself, relying on the security failures on the target computer to access it. |
UNSW-NB15 attack types.
Apache Spark, is powerful hybrid, scalable and fast distributed data processing engine most active open source project in big data. It was developed at UC Berkeley in 2009. It became one of the top projects in Apache in 2010 [19]. Spark provides APIs in Scala, Java, Python and R languages. To get a good hold on huge data, it must be fast enough by processing massive data at once. Therefore, it is necessary that Spark is available on several clusters rather than on a single machine. The result of the treatment provided by Spark is not written to the disk but kept in memory. This all-in-memory ability is a high-performance computing technique for advanced analytics, making Spark 100 times faster than Hadoop (Figure 2) [20].
Speed comparison chart between spark Hadoop.
Spark also has an ecosystem of libraries that can be used for Machine Learning, interactive queries. Which can have important implications for productivity. The project has been progressively enriched to provide a complete ecosystem today which is shown in Figure 3.
Apache spark ecosystem.
Microsoft Azure, formally known as Windows Azure, is a cloud computing platform for building, deploying and managing services and applications anywhere with the help of a global network of managed data centers located in 54 regions around the world [21]. Microsoft’s HDInsight is a managed Hadoop service in Azure Cloud that uses the Hortonworks Data Platform (HDP). HDInsight clusters can be customized easily by adding additional packages and can scale up in case of high demand by allocating more processing power [22]. By the Azure Active Directory, The data is protected and persists even after the cluster is deleted.
The FCM algorithm is one of the most widely used fuzzy clustering algorithms [23] which attempts to partition a finite collection of elements into a collection of c fuzzy clusters with respect to some given criterion. This algorithm is based on minimization of the following objective function:
where:
m: Any real number greater than 1.
||*||: Any norm expressing the similarity between any measured data and the center. The algorithm FCM is composed of the following steps:
Where:
k: The iteration steps.
A pseudo code of the algorithm FCM is presented as follows (Figure 4).
Pseudo code of FCM algorithm-.
The idea of our distributed architecture comes down to a process adaptation of in data fusion approach. This architecture allows us to facilitate data analysis with a powerful Spark big data tool (see Figure 5).
Diagram of proposed approach.
We will be using Jupyter Notebook with Apache Spark and the Python API (PySpark). In this stage, we will read CSV files and converting them to Apache Parquet format into Microsoft Azure Blob Storage. Apache Spark supports multiple operations on data, it bids the ability to convert data to another format in just one line of code. Developed by Twitter and Cloudera, Apache Parquet is an open-source columnar file format optimized for query performance and minimizing I/O, offering very efficient compression and encoding schemes [26]. Figure 6 shows the efficiency of using the Parket format. This format minimizes storage costs and data processing time.
Apache parquet advantages.
The following Table 2 indicates the old and new size of each datasets after converting to Apache Parquet, We notice that by converting CSV to Parquet the storage costs are minimized.
DataSets | Average Size (CSV) | Average Size (Parquet) | speedup |
---|---|---|---|
2600.96MO | 555MO | x4.69 | |
559MO | 202MO | x2.77 |
Average file size before and after converting.
The feature selection phase selects relevant attributes required for decision making. A pre-processing phase converts the flow records in a specific format which is acceptable to an anomaly detection algorithm [27].
with the CTU-13 dataset, We did not utilize the feature selection algorithm for this dataset, we instead selected columns that were pertinent and delete unnecessary features(empty columns). After the removing, we get with a total of 13 columns.
Using UNSW-NB15 dataset, we processed the data selection problem. We apply a combination fusion of Random Forest Algorithm with Decision Tree Classifier. V. Kanimozhi [28] decides that the combined fusion of these two algorithms provides 98.3% has listed the best four features are as sbytes, sttl, sload, ct_dst_src_ltm and the Figure 7 labels the graphical representation of Feature Importances and the top four features.
Feature importance of UNSW-NB15 dataset.
The goal of eliminating no-useful attributes is bring about a better performance by the system with a better accuracy.
This eliminate redundancies task involves removing duplicates (removing all the repeated records) which helps with attack detection as it makes the system less biased by the existence of more frequent records.This tactic makes computation faster as it must deal with less data [29].
Before the merge of the bases, some common columns have different names from one database to another (for example “Label” in CTU-13 named “attack_cat” in UNSW-NB15), in this state, we will rename these attributes then we will merge our bases. Since, Apache Spark offers the ability to join our databases in just one line of code. The following Listing shows the query used:
Using the Apache Spark Machine Learning library, we create a Machine Learning pipeline. A pipeline is a sequence of stages where each stage is either an Estimator or a Transformer.
In our final base, some attributes are of types string (Like: Label, sport, proto, ...), in this step we will convert all attributes of type string to attribute of type integer by using the transformer “StringIndexer” which encodes a string column of labels to a column of label indices. These indices are ordered by label frequencies, the most frequent label gets index 0.
StringIndexer classifies attacks automatically in class, it assigns the same index for attacks of the same category.
In our experimental work and as we said above we will use Microsoft Azure as a cloud environment to upload and analyze the dataset with FCM algorithm. We use the training dataset to form and evaluate our model. The test dataset is then used to make predictions. We choose to train our Model with FCM algorithm. The first stage of the FCM algorithm is to initialize the input variable, the input vector includes the dataset features, the number of cluster is 2 (
The data records clustering.
Apache Spark Machine Learning provides a suite of metrics to evaluate the performance of Machine Learn- ing models [31]. To measure the performance in our work the metrics used are as present in below Table 3 (Where TP = True Positives, TN = True Negatives, FP = False Positives and FN = False Negatives).
Measure | Description | Formula |
---|---|---|
Accuracy measures performance across all labels | Accuracy = TP + TN/TP + FP + FN + TN | |
The ratio of correctly predicted positive observations to the total predicted positive observations. | Precision = TP/TP + FP | |
The ratio of correctly predicted positive observations to the all observations in actual class | Recall = TP/TP + FN | |
The weighted average of Precision and Recall | F1 = 2*(Recall * Precision) / (Recall + Precision) |
Evaluation metrics.
After apply the FCM to our final dataset(After merging our intrusion detection datasets) the result is shown in the following Table 4.
Input data | Output data | Classification rate | |
---|---|---|---|
243 899 | 231 704 | 94.9% | |
601 822 | 589 785 | 97.9% |
Evaluation metrics.
As shown in Table 4 the total input data is 845 721 records, 243 899 records as normal and 601 822 records as intrusion. After applying FCM algorithm, the result is 231 704 record for normal and 589 785 records for intrusion. Then we calculated the normal and intrusion classification rate by the following equation:
The simulation results show that the classification rate is 96.4% by the FCM algorithm which means that the false positive rate(returns the rate of instances which are falsely classified) is 0.02%.
It is possible to obtain a very precise system (accuracy of 99%) but not very efficient with a recall of 10%. In our work, with an accuracy of 97.2% and a recall of 96.4%, we can say that our system is efficient. The use of the fuzzy algorithm in this experiment gave a good result. The advantage of our system is the fuzzy representation that is increasingly used to deal with missing and inaccurate data problems which is the disadvantage of most classification algorithms.
In this paper, we achieved a successful distributed IDS. Using the FCM algorithm allows to effectively train and analyze our model after merging datasets. Proposing a distributed system and showing the power of Spark to combine and handle large and heterogeneous structures of training datasets present the main merits in our work.
In future work, we will perform our dataset analysis with another Big Data framework expected to reach faster results. In addition, we will develop our approach with other classifiers to get better results.
Intro
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His studies in robotics lead him not only to a PhD degree but also inspired him to co-found and build the International Journal of Advanced Robotic Systems - world's first Open Access journal in the field of robotics.",institutionString:null,institution:{name:"TU Wien",country:{name:"Austria"}}},{id:"441",title:"Ph.D.",name:"Jaekyu",middleName:null,surname:"Park",slug:"jaekyu-park",fullName:"Jaekyu Park",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/441/images/1881_n.jpg",biography:null,institutionString:null,institution:{name:"LG Corporation (South Korea)",country:{name:"Korea, South"}}},{id:"465",title:"Dr.",name:"Christian",middleName:null,surname:"Martens",slug:"christian-martens",fullName:"Christian Martens",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Rheinmetall (Germany)",country:{name:"Germany"}}},{id:"479",title:"Dr.",name:"Valentina",middleName:null,surname:"Colla",slug:"valentina-colla",fullName:"Valentina Colla",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/479/images/358_n.jpg",biography:null,institutionString:null,institution:{name:"Sant'Anna School of Advanced Studies",country:{name:"Italy"}}},{id:"494",title:"PhD",name:"Loris",middleName:null,surname:"Nanni",slug:"loris-nanni",fullName:"Loris Nanni",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/494/images/system/494.jpg",biography:"Loris Nanni received his Master Degree cum laude on June-2002 from the University of Bologna, and the April 26th 2006 he received his Ph.D. in Computer Engineering at DEIS, University of Bologna. 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. From 1985 to 1986, he was a Research Fellow in the Research Institute for Electronic Equipment, ZZU AD, Plovdiv, Bulgaria. In 1986, he joined the Department of Control Systems, Technical University of Sofia at the Plovdiv campus, where he is presently a Full Professor. He has held long-term visiting Professor/Scholar positions at various institutions in South Korea, Turkey, Mexico, Greece, Belgium, UK, and Germany. And he has coauthored one book and authored or coauthored more than 80 research papers in conference proceedings and journals. His current research interests are in the fields of intelligent control and robotics.",institutionString:null,institution:{name:"Technical University of Sofia",country:{name:"Bulgaria"}}},{id:"585",title:"Prof.",name:"Munir",middleName:null,surname:"Merdan",slug:"munir-merdan",fullName:"Munir Merdan",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/585/images/system/585.jpg",biography:"Munir Merdan received the M.Sc. degree in mechanical engineering from the Technical University of Sarajevo, Bosnia and Herzegovina, in 2001, and the Ph.D. degree in electrical engineering from the Vienna University of Technology, Vienna, Austria, in 2009.Since 2005, he has been at the Automation and Control Institute, Vienna University of Technology, where he is currently a Senior Researcher. His research interests include the application of agent technology for achieving agile control in the manufacturing environment.",institutionString:null,institution:null},{id:"605",title:"Prof",name:"Dil",middleName:null,surname:"Hussain",slug:"dil-hussain",fullName:"Dil Hussain",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/605/images/system/605.jpg",biography:"Dr. Dil Muhammad Akbar Hussain is a professor of Electronics Engineering & Computer Science at the Department of Energy Technology, Aalborg University Denmark. Professor Akbar has a Master degree in Digital Electronics from Govt. College University, Lahore Pakistan and a P-hD degree in Control Engineering from the School of Engineering and Applied Sciences, University of Sussex United Kingdom. Aalborg University has Two Satellite Campuses, one in Copenhagen (Aalborg University Copenhagen) and the other in Esbjerg (Aalborg University Esbjerg).\n· He is a member of prestigious IEEE (Institute of Electrical and Electronics Engineers), and IAENG (International Association of Engineers) organizations. \n· He is the chief Editor of the Journal of Software Engineering.\n· He is the member of the Editorial Board of International Journal of Computer Science and Software Technology (IJCSST) and International Journal of Computer Engineering and Information Technology. \n· He is also the Editor of Communication in Computer and Information Science CCIS-20 by Springer.\n· Reviewer For Many Conferences\nHe is the lead person in making collaboration agreements between Aalborg University and many universities of Pakistan, for which the MOU’s (Memorandum of Understanding) have been signed.\nProfessor Akbar is working in Academia since 1990, he started his career as a Lab demonstrator/TA at the University of Sussex. After finishing his P. hD degree in 1992, he served in the Industry as a Scientific Officer and continued his academic career as a visiting scholar for a number of educational institutions. In 1996 he joined National University of Science & Technology Pakistan (NUST) as an Associate Professor; NUST is one of the top few universities in Pakistan. In 1999 he joined an International Company Lineo Inc, Canada as Manager Compiler Group, where he headed the group for developing Compiler Tool Chain and Porting of Operating Systems for the BLACKfin processor. The processor development was a joint venture by Intel and Analog Devices. In 2002 Lineo Inc., was taken over by another company, so he joined Aalborg University Denmark as an Assistant Professor.\nProfessor Akbar has truly a multi-disciplined career and he continued his legacy and making progress in many areas of his interests both in teaching and research. He has contributed in stochastic estimation of control area especially, in the Multiple Target Tracking and Interactive Multiple Model (IMM) research, Ball & Beam Control Problem, Robotics, Levitation Control. He has contributed in developing Algorithms for Fingerprint Matching, Computer Vision and Face Recognition. He has been supervising Pattern Recognition, Formal Languages and Distributed Processing projects for several years. He has reviewed many books on Management, Computer Science. Currently, he is an active and permanent reviewer for many international conferences and symposia and the program committee member for many international conferences.\nIn teaching he has taught the core computer science subjects like, Digital Design, Real Time Embedded System Programming, Operating Systems, Software Engineering, Data Structures, Databases, Compiler Construction. 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He is the founder of The IEEE IWOBI conference series and the president of its Steering Committee, as well as the founder of both the InnoEducaTIC and APPIS conference series. He is an evaluator of project proposals for the European Union (H2020), Medical Research Council (MRC, UK), Spanish Government (ANECA, Spain), Research National Agency (ANR, France), DAAD (Germany), Argentinian Government, and the Colombian Institutions. He has been a reviewer in different indexed international journals (<70) and conferences (<250) since 2001. He has been a member of the IASTED Technical Committee on Image Processing from 2007 and a member of the IASTED Technical Committee on Artificial Intelligence and Expert Systems from 2011. \n\nHe has held the general chair position for the following: ACM-APPIS (2020, 2021), IEEE-IWOBI (2019, 2020 and 2020), A PPIS (2018, 2019), IEEE-IWOBI (2014, 2015, 2017, 2018), InnoEducaTIC (2014, 2017), IEEE-INES (2013), NoLISP (2011), JRBP (2012), and IEEE-ICCST (2005)\n\nHe is an associate editor of the Computational Intelligence and Neuroscience Journal (Hindawi – Q2 JCR-ISI). He was vice dean from 2004 to 2010 in the Higher Technical School of Telecommunication Engineers at ULPGC and the vice dean of Graduate and Postgraduate Studies from March 2013 to November 2017. 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He has (co)authored more than 150 publications in indexed journals, international conferences and book chapters, 1 book (in Greek), 3 edited books, and 5 journal special issues. His publications have more than 2100 citations with h-index 27 (GoogleScholar). His research interests include computer/machine vision, machine learning, pattern recognition, computational intelligence. \nDr. Papakostas served as a reviewer in numerous journals, as a program\ncommittee member in international conferences and he is a member of the IAENG, MIR Labs, EUCogIII, INSTICC and the Technical Chamber of Greece (TEE).",institutionString:null,institution:{name:"International Hellenic University",institutionURL:null,country:{name:"Greece"}}},editorTwo:null,editorThree:null},{id:"25",title:"Evolutionary Computation",coverUrl:"https://cdn.intechopen.com/series_topics/covers/25.jpg",isOpenForSubmission:!0,editor:{id:"136112",title:"Dr.",name:"Sebastian",middleName:null,surname:"Ventura Soto",slug:"sebastian-ventura-soto",fullName:"Sebastian Ventura Soto",profilePictureURL:"https://mts.intechopen.com/storage/users/136112/images/system/136112.png",biography:"Sebastian Ventura is a Spanish researcher, a full professor with the Department of Computer Science and Numerical Analysis, University of Córdoba. 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She is now a lecturer at the University of Witwatersrand, South Africa, and a principal researcher at the Health Economics and Epidemiology Research Office (HE2RO), South Africa. Dr. Moolla holds a Ph.D. in Psychology with her research being focused on mental health and resilience. In her professional work capacity, her research has further expanded into the fields of early childhood development, mental health, the HIV and TB care cascades, as well as COVID. She is also a UNESCO-trained International Bioethics Facilitator.",institutionString:"University of the Witwatersrand",institution:{name:"University of the Witwatersrand",country:{name:"South Africa"}}},{id:"419588",title:"Ph.D.",name:"Sergio",middleName:"Alexandre",surname:"Gehrke",slug:"sergio-gehrke",fullName:"Sergio Gehrke",position:null,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",country:{name:"Spain"}}},{id:"342152",title:"Dr.",name:"Santo",middleName:null,surname:"Grace Umesh",slug:"santo-grace-umesh",fullName:"Santo Grace Umesh",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/342152/images/16311_n.jpg",biography:null,institutionString:null,institution:{name:"SRM Dental College",country:{name:"India"}}},{id:"333647",title:"Dr.",name:"Shreya",middleName:null,surname:"Kishore",slug:"shreya-kishore",fullName:"Shreya Kishore",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/333647/images/14701_n.jpg",biography:"Dr. Shreya Kishore completed her Bachelor in Dental Surgery in Chettinad Dental College and Research Institute, Chennai, and her Master of Dental Surgery (Orthodontics) in Saveetha Dental College, Chennai. She is also Invisalign certified. She’s working as a Senior Lecturer in the Department of Orthodontics, SRM Dental College since November 2019. She is actively involved in teaching orthodontics to the undergraduates and the postgraduates. Her clinical research topics include new orthodontic brackets, fixed appliances and TADs. She’s published 4 articles in well renowned indexed journals and has a published patency of her own. Her private practice is currently limited to orthodontics and works as a consultant in various clinics.",institutionString:null,institution:{name:"SRM Dental College",country:{name:"India"}}},{id:"323731",title:"Prof.",name:"Deepak M.",middleName:"Macchindra",surname:"Vikhe",slug:"deepak-m.-vikhe",fullName:"Deepak M. Vikhe",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/323731/images/13613_n.jpg",biography:"Dr Deepak M.Vikhe .\n\n\t\n\tDr Deepak M.Vikhe , completed his Masters & PhD in Prosthodontics from Rural Dental College, Loni securing third rank in the Pravara Institute of Medical Sciences Deemed University. He was awarded Dr.G.C.DAS Memorial Award for Research on Implants at 39th IPS conference Dubai (U A E).He has two patents under his name. He has received Dr.Saraswati medal award for best research for implant study in 2017.He has received Fully funded scholarship to Spain ,university of Santiago de Compostela. He has completed fellowship in Implantlogy from Noble Biocare. \nHe has attended various conferences and CDE programmes and has national publications to his credit. His field of interest is in Implant supported prosthesis. Presently he is working as a associate professor in the Dept of Prosthodontics, Rural Dental College, Loni and maintains a successful private practice specialising in Implantology at Rahata.\n\nEmail: drdeepak_mvikhe@yahoo.com..................",institutionString:null,institution:{name:"Pravara Institute of Medical Sciences",country:{name:"India"}}},{id:"204110",title:"Dr.",name:"Ahmed A.",middleName:null,surname:"Madfa",slug:"ahmed-a.-madfa",fullName:"Ahmed A. Madfa",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/204110/images/system/204110.jpg",biography:"Dr. Madfa is currently Associate Professor of Endodontics at Thamar University and a visiting lecturer at Sana'a University and University of Sciences and Technology. He has more than 6 years of experience in teaching. His research interests include root canal morphology, functionally graded concept, dental biomaterials, epidemiology and dental education, biomimetic restoration, finite element analysis and endodontic regeneration. Dr. Madfa has numerous international publications, full articles, two patents, a book and a book chapter. Furthermore, he won 14 international scientific awards. Furthermore, he is involved in many academic activities ranging from editorial board member, reviewer for many international journals and postgraduate students' supervisor. Besides, I deliver many courses and training workshops at various scientific events. Dr. Madfa also regularly attends international conferences and holds administrative positions (Deputy Dean of the Faculty for Students’ & Academic Affairs and Deputy Head of Research Unit).",institutionString:"Thamar University",institution:null},{id:"210472",title:"Dr.",name:"Nermin",middleName:"Mohammed Ahmed",surname:"Yussif",slug:"nermin-yussif",fullName:"Nermin Yussif",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/210472/images/system/210472.jpg",biography:"Dr. Nermin Mohammed Ahmed Yussif is working at the Faculty of dentistry, University for October university for modern sciences and arts (MSA). Her areas of expertise include: periodontology, dental laserology, oral implantology, periodontal plastic surgeries, oral mesotherapy, nutrition, dental pharmacology. She is an editor and reviewer in numerous international journals.",institutionString:"MSA University",institution:null},{id:"204606",title:"Dr.",name:"Serdar",middleName:null,surname:"Gözler",slug:"serdar-gozler",fullName:"Serdar Gözler",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/204606/images/system/204606.jpeg",biography:"Dr. Serdar Gözler has completed his undergraduate studies at the Marmara University Faculty of Dentistry in 1978, followed by an assistantship in the Prosthesis Department of Dicle University Faculty of Dentistry. Starting his PhD work on non-resilient overdentures with Assoc. Prof. Hüsnü Yavuzyılmaz, he continued his studies with Prof. Dr. Gürbüz Öztürk of Istanbul University Faculty of Dentistry Department of Prosthodontics, this time on Gnatology. He attended training programs on occlusion, neurology, neurophysiology, EMG, radiology and biostatistics. In 1982, he presented his PhD thesis \\Gerber and Lauritzen Occlusion Analysis Techniques: Diagnosis Values,\\ at Istanbul University School of Dentistry, Department of Prosthodontics. As he was also working with Prof. Senih Çalıkkocaoğlu on The Physiology of Chewing at the same time, Gözler has written a chapter in Çalıkkocaoğlu\\'s book \\Complete Prostheses\\ entitled \\The Place of Neuromuscular Mechanism in Prosthetic Dentistry.\\ The book was published five times since by the Istanbul University Publications. Having presented in various conferences about occlusion analysis until 1998, Dr. Gözler has also decided to use the T-Scan II occlusion analysis method. Having been personally trained by Dr. Robert Kerstein on this method, Dr. Gözler has been lecturing on the T-Scan Occlusion Analysis Method in conferences both in Turkey and abroad. Dr. Gözler has various articles and presentations on Digital Occlusion Analysis methods. He is now Head of the TMD Clinic at Prosthodontic Department of Faculty of Dentistry , Istanbul Aydın University , Turkey.",institutionString:"Istanbul Aydin University",institution:{name:"Istanbul Aydın University",country:{name:"Turkey"}}},{id:"256417",title:"Associate Prof.",name:"Sanaz",middleName:null,surname:"Sadry",slug:"sanaz-sadry",fullName:"Sanaz Sadry",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/256417/images/8106_n.jpg",biography:null,institutionString:null,institution:{name:"Istanbul Aydın University",country:{name:"Turkey"}}},{id:"240870",title:"Ph.D.",name:"Alaa Eddin Omar",middleName:null,surname:"Al Ostwani",slug:"alaa-eddin-omar-al-ostwani",fullName:"Alaa Eddin Omar Al Ostwani",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/240870/images/system/240870.jpeg",biography:"Dr. Al Ostwani Alaa Eddin Omar received his Master in dentistry from Damascus University in 2010, and his Ph.D. in Pediatric Dentistry from Damascus University in 2014. Dr. Al Ostwani is an assistant professor and faculty member at IUST University since 2014. \nDuring his academic experience, he has received several awards including the scientific research award from the Union of Arab Universities, the Syrian gold medal and the international gold medal for invention and creativity. Dr. Al Ostwani is a Member of the International Association of Dental Traumatology and the Syrian Society for Research and Preventive Dentistry since 2017. He is also a Member of the Reviewer Board of International Journal of Dental Medicine (IJDM), and the Indian Journal of Conservative and Endodontics since 2016.",institutionString:"International University for Science and Technology.",institution:{name:"Islamic University of Science and Technology",country:{name:"India"}}},{id:"42847",title:"Dr.",name:"Belma",middleName:null,surname:"Işik Aslan",slug:"belma-isik-aslan",fullName:"Belma Işik Aslan",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/42847/images/system/42847.jpg",biography:"Dr. Belma IşIk Aslan was born in 1976 in Ankara-TURKEY. After graduating from TED Ankara College in 1994, she attended to Gazi University, Faculty of Dentistry in Ankara. She completed her PhD in orthodontic education at Gazi University between 1999-2005. Dr. Işık Aslan stayed at the Providence Hospital Craniofacial Institude and Reconstructive Surgery in Michigan, USA for three months as an observer. She worked as a specialist doctor at Gazi University, Dentistry Faculty, Department of Orthodontics between 2005-2014. She was appointed as associate professor in January, 2014 and as professor in 2021. Dr. Işık Aslan still works as an instructor at the same faculty. She has published a total of 35 articles, 10 book chapters, 39 conference proceedings both internationally and nationally. Also she was the academic editor of the international book 'Current Advances in Orthodontics'. She is a member of the Turkish Orthodontic Society and Turkish Cleft Lip and Palate Society. She is married and has 2 children. Her knowledge of English is at an advanced level.",institutionString:"Gazi University Dentistry Faculty Department of Orthodontics",institution:null},{id:"202198",title:"Dr.",name:"Buket",middleName:null,surname:"Aybar",slug:"buket-aybar",fullName:"Buket Aybar",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/202198/images/6955_n.jpg",biography:"Buket Aybar, DDS, PhD, was born in 1971. She graduated from Istanbul University, Faculty of Dentistry, in 1992 and completed her PhD degree on Oral and Maxillofacial Surgery in Istanbul University in 1997.\r\nDr. Aybar is currently a full-time professor in Istanbul University, Faculty of Dentistry Department of Oral and Maxillofacial Surgery. She has teaching responsibilities in graduate and postgraduate programs. Her clinical practice includes mainly dentoalveolar surgery.\r\nHer topics of interest are biomaterials science and cell culture studies. She has many articles in international and national scientific journals and chapters in books; she also has participated in several scientific projects supported by Istanbul University Research fund.",institutionString:null,institution:{name:"Marmara University",country:{name:"Turkey"}}},{id:"178412",title:"Associate Prof.",name:"Guhan",middleName:null,surname:"Dergin",slug:"guhan-dergin",fullName:"Guhan Dergin",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/178412/images/6954_n.jpg",biography:"Assoc. Prof. Dr. Gühan Dergin was born in 1973 in Izmit. He graduated from Marmara University Faculty of Dentistry in 1999. He completed his specialty of OMFS surgery in Marmara University Faculty of Dentistry and obtained his PhD degree in 2006. In 2005, he was invited as a visiting doctor in the Oral and Maxillofacial Surgery Department of the University of North Carolina, USA, where he went on a scholarship. Dr. Dergin still continues his academic career as an associate professor in Marmara University Faculty of Dentistry. He has many articles in international and national scientific journals and chapters in books.",institutionString:null,institution:{name:"Marmara University",country:{name:"Turkey"}}},{id:"178414",title:"Prof.",name:"Yusuf",middleName:null,surname:"Emes",slug:"yusuf-emes",fullName:"Yusuf Emes",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/178414/images/6953_n.jpg",biography:"Born in Istanbul in 1974, Dr. Emes graduated from Istanbul University Faculty of Dentistry in 1997 and completed his PhD degree in Istanbul University faculty of Dentistry Department of Oral and Maxillofacial Surgery in 2005. He has papers published in international and national scientific journals, including research articles on implantology, oroantral fistulas, odontogenic cysts, and temporomandibular disorders. Dr. Emes is currently working as a full-time academic staff in Istanbul University faculty of Dentistry Department of Oral and Maxillofacial Surgery.",institutionString:null,institution:{name:"Istanbul University",country:{name:"Turkey"}}},{id:"192229",title:"Ph.D.",name:"Ana Luiza",middleName:null,surname:"De Carvalho Felippini",slug:"ana-luiza-de-carvalho-felippini",fullName:"Ana Luiza De Carvalho Felippini",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/192229/images/system/192229.jpg",biography:null,institutionString:"University of São Paulo",institution:{name:"University of Sao Paulo",country:{name:"Brazil"}}},{id:"256851",title:"Prof.",name:"Ayşe",middleName:null,surname:"Gülşen",slug:"ayse-gulsen",fullName:"Ayşe Gülşen",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/256851/images/9696_n.jpg",biography:"Dr. Ayşe Gülşen graduated in 1990 from Faculty of Dentistry, University of Ankara and did a postgraduate program at University of Gazi. \nShe worked as an observer and research assistant in Craniofacial Surgery Departments in New York, Providence Hospital in Michigan and Chang Gung Memorial Hospital in Taiwan. \nShe works as Craniofacial Orthodontist in Department of Aesthetic, Plastic and Reconstructive Surgery, Faculty of Medicine, University of Gazi, Ankara Turkey since 2004.",institutionString:"Orthodontist, Assoc Prof in the Department of Aesthetic, Plastic and Reconstructive Surgery, Faculty of Medicine, University of Gazi",institution:null},{id:"255366",title:"Prof.",name:"Tosun",middleName:null,surname:"Tosun",slug:"tosun-tosun",fullName:"Tosun Tosun",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/255366/images/7347_n.jpg",biography:"Graduated at the Faculty of Dentistry, University of Istanbul, Turkey in 1989;\nVisitor Assistant at the University of Padua, Italy and Branemark Osseointegration Center of Treviso, Italy between 1993-94;\nPhD thesis on oral implantology in University of Istanbul and was awarded the academic title “Dr.med.dent.”, 1997;\nHe was awarded the academic title “Doç.Dr.” (Associated Professor) in 2003;\nProficiency in Botulinum Toxin Applications, Reading-UK in 2009;\nMastership, RWTH Certificate in Laser Therapy in Dentistry, AALZ-Aachen University, Germany 2009-11;\nMaster of Science (MSc) in Laser Dentistry, University of Genoa, Italy 2013-14.\n\nDr.Tosun worked as Research Assistant in the Department of Oral Implantology, Faculty of Dentistry, University of Istanbul between 1990-2002. \nHe worked part-time as Consultant surgeon in Harvard Medical International Hospitals and John Hopkins Medicine, Istanbul between years 2007-09.\u2028He was contract Professor in the Department of Surgical and Diagnostic Sciences (DI.S.C.), Medical School, University of Genova, Italy between years 2011-16. \nSince 2015 he is visiting Professor at Medical School, University of Plovdiv, Bulgaria. \nCurrently he is Associated Prof.Dr. at the Dental School, Oral Surgery Dept., Istanbul Aydin University and since 2003 he works in his own private clinic in Istanbul, Turkey.\u2028\nDr.Tosun is reviewer in journal ‘Laser in Medical Sciences’, reviewer in journal ‘Folia Medica\\', a Fellow of the International Team for Implantology, Clinical Lecturer of DGZI German Association of Oral Implantology, Expert Lecturer of Laser&Health Academy, Country Representative of World Federation for Laser Dentistry, member of European Federation of Periodontology, member of Academy of Laser Dentistry. Dr.Tosun presents papers in international and national congresses and has scientific publications in international and national journals. He speaks english, spanish, italian and french.",institutionString:null,institution:{name:"Istanbul Aydın University",country:{name:"Turkey"}}},{id:"260116",title:"Dr.",name:"Mehmet",middleName:null,surname:"Yaltirik",slug:"mehmet-yaltirik",fullName:"Mehmet Yaltirik",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/260116/images/7413_n.jpg",biography:"Birth Date 25.09.1965\r\nBirth Place Adana- Turkey\r\nSex Male\r\nMarrial Status Bachelor\r\nDriving License Acquired\r\nMother Tongue Turkish\r\n\r\nAddress:\r\nWork:University of Istanbul,Faculty of Dentistry, Department of Oral Surgery and Oral Medicine 34093 Capa,Istanbul- TURKIYE",institutionString:null,institution:{name:"Istanbul University",country:{name:"Turkey"}}},{id:"171887",title:"Prof.",name:"Zühre",middleName:null,surname:"Akarslan",slug:"zuhre-akarslan",fullName:"Zühre Akarslan",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/171887/images/system/171887.jpg",biography:"Zühre Akarslan was born in 1977 in Cyprus. She graduated from Gazi University Faculty of Dentistry, Ankara, Turkey in 2000. \r\nLater she received her Ph.D. degree from the Oral Diagnosis and Radiology Department; which was recently renamed as Oral and Dentomaxillofacial Radiology, from the same university. \r\nShe is working as a full-time Associate Professor and is a lecturer and an academic researcher. \r\nHer expertise areas are dental caries, cancer, dental fear and anxiety, gag reflex in dentistry, oral medicine, and dentomaxillofacial radiology.",institutionString:"Gazi University",institution:{name:"Gazi University",country:{name:"Turkey"}}},{id:"272237",title:"Dr.",name:"Pinar",middleName:"Kiymet",surname:"Karataban",slug:"pinar-karataban",fullName:"Pinar Karataban",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/272237/images/8911_n.png",biography:"Assist.Prof.Dr.Pınar Kıymet Karataban, DDS PhD \n\nDr.Pınar Kıymet Karataban was born in Istanbul in 1975. After her graduation from Marmara University Faculty of Dentistry in 1998 she started her PhD in Paediatric Dentistry focused on children with special needs; mainly children with Cerebral Palsy. She finished her pHD thesis entitled \\'Investigation of occlusion via cast analysis and evaluation of dental caries prevalance, periodontal status and muscle dysfunctions in children with cerebral palsy” in 2008. She got her Assist. Proffessor degree in Istanbul Aydın University Paediatric Dentistry Department in 2015-2018. ın 2019 she started her new career in Bahcesehir University, Istanbul as Head of Department of Pediatric Dentistry. In 2020 she was accepted to BAU International University, Batumi as Professor of Pediatric Dentistry. She’s a lecturer in the same university meanwhile working part-time in private practice in Ege Dental Studio (https://www.egedisklinigi.com/) a multidisciplinary dental clinic in Istanbul. Her main interests are paleodontology, ancient and contemporary dentistry, oral microbiology, cerebral palsy and special care dentistry. She has national and international publications, scientific reports and is a member of IAPO (International Association for Paleodontology), IADH (International Association of Disability and Oral Health) and EAPD (European Association of Pediatric Dentistry).",institutionString:null,institution:null},{id:"172009",title:"Dr.",name:"Fatma Deniz",middleName:null,surname:"Uzuner",slug:"fatma-deniz-uzuner",fullName:"Fatma Deniz Uzuner",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/172009/images/7122_n.jpg",biography:"Dr. Deniz Uzuner was born in 1969 in Kocaeli-TURKEY. After graduating from TED Ankara College in 1986, she attended the Hacettepe University, Faculty of Dentistry in Ankara. \nIn 1993 she attended the Gazi University, Faculty of Dentistry, Department of Orthodontics for her PhD education. After finishing the PhD education, she worked as orthodontist in Ankara Dental Hospital under the Turkish Government, Ministry of Health and in a special Orthodontic Clinic till 2011. Between 2011 and 2016, Dr. Deniz Uzuner worked as a specialist in the Department of Orthodontics, Faculty of Dentistry, Gazi University in Ankara/Turkey. In 2016, she was appointed associate professor. Dr. Deniz Uzuner has authored 23 Journal Papers, 3 Book Chapters and has had 39 oral/poster presentations. She is a member of the Turkish Orthodontic Society. Her knowledge of English is at an advanced level.",institutionString:null,institution:null},{id:"332914",title:"Dr.",name:"Muhammad Saad",middleName:null,surname:"Shaikh",slug:"muhammad-saad-shaikh",fullName:"Muhammad Saad Shaikh",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Jinnah Sindh Medical University",country:{name:"Pakistan"}}},{id:"315775",title:"Dr.",name:"Feng",middleName:null,surname:"Luo",slug:"feng-luo",fullName:"Feng Luo",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Sichuan University",country:{name:"China"}}},{id:"344229",title:"Dr.",name:"Sankeshan",middleName:null,surname:"Padayachee",slug:"sankeshan-padayachee",fullName:"Sankeshan Padayachee",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"University of the Witwatersrand",country:{name:"South Africa"}}},{id:"315727",title:"Ms.",name:"Kelebogile A.",middleName:null,surname:"Mothupi",slug:"kelebogile-a.-mothupi",fullName:"Kelebogile A. Mothupi",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"University of the Witwatersrand",country:{name:"South Africa"}}},{id:"423519",title:"Dr.",name:"Sizakele",middleName:null,surname:"Ngwenya",slug:"sizakele-ngwenya",fullName:"Sizakele Ngwenya",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"University of the Witwatersrand",country:{name:"South Africa"}}},{id:"337613",title:"Mrs.",name:"Tshakane",middleName:null,surname:"R.M.D. Ralephenya",slug:"tshakane-r.m.d.-ralephenya",fullName:"Tshakane R.M.D. Ralephenya",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"University of the Witwatersrand",country:{name:"South Africa"}}},{id:"419270",title:"Dr.",name:"Ann",middleName:null,surname:"Chianchitlert",slug:"ann-chianchitlert",fullName:"Ann Chianchitlert",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Walailak University",country:{name:"Thailand"}}},{id:"419271",title:"Dr.",name:"Diane",middleName:null,surname:"Selvido",slug:"diane-selvido",fullName:"Diane Selvido",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Walailak University",country:{name:"Thailand"}}},{id:"419272",title:"Dr.",name:"Irin",middleName:null,surname:"Sirisoontorn",slug:"irin-sirisoontorn",fullName:"Irin Sirisoontorn",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Walailak University",country:{name:"Thailand"}}}]}},subseries:{item:{id:"40",type:"subseries",title:"Ecosystems and Biodiversity",keywords:"Ecosystems, Biodiversity, Fauna, Taxonomy, Invasive Species, Destruction of Habitats, Overexploitation of Natural Resources, Pollution, Global Warming, Conservation of Natural Spaces, Bioremediation",scope:"