PL properties of undoped and Mn-doped ZnSe QDs.
\\n\\n
More than half of the publishers listed alongside IntechOpen (18 out of 30) are Social Science and Humanities publishers. IntechOpen is an exception to this as a leader in not only Open Access content but Open Access content across all scientific disciplines, including Physical Sciences, Engineering and Technology, Health Sciences, Life Science, and Social Sciences and Humanities.
\\n\\nOur breakdown of titles published demonstrates this with 47% PET, 31% HS, 18% LS, and 4% SSH books published.
\\n\\n“Even though ItechOpen has shown the potential of sci-tech books using an OA approach,” other publishers “have shown little interest in OA books.”
\\n\\nAdditionally, each book published by IntechOpen contains original content and research findings.
\\n\\nWe are honored to be among such prestigious publishers and we hope to continue to spearhead that growth in our quest to promote Open Access as a true pioneer in OA book publishing.
\\n\\n\\n\\n
\\n"}]',published:!0,mainMedia:{caption:"IntechOpen Maintains",originalUrl:"/media/original/113"}},components:[{type:"htmlEditorComponent",content:'
Simba Information has released its Open Access Book Publishing 2020 - 2024 report and has again identified IntechOpen as the world’s largest Open Access book publisher by title count.
\n\nSimba Information is a leading provider for market intelligence and forecasts in the media and publishing industry. The report, published every year, provides an overview and financial outlook for the global professional e-book publishing market.
\n\nIntechOpen, De Gruyter, and Frontiers are the largest OA book publishers by title count, with IntechOpen coming in at first place with 5,101 OA books published, a good 1,782 titles ahead of the nearest competitor.
\n\nSince the first Open Access Book Publishing report published in 2016, IntechOpen has held the top stop each year.
\n\n\n\nMore than half of the publishers listed alongside IntechOpen (18 out of 30) are Social Science and Humanities publishers. IntechOpen is an exception to this as a leader in not only Open Access content but Open Access content across all scientific disciplines, including Physical Sciences, Engineering and Technology, Health Sciences, Life Science, and Social Sciences and Humanities.
\n\nOur breakdown of titles published demonstrates this with 47% PET, 31% HS, 18% LS, and 4% SSH books published.
\n\n“Even though ItechOpen has shown the potential of sci-tech books using an OA approach,” other publishers “have shown little interest in OA books.”
\n\nAdditionally, each book published by IntechOpen contains original content and research findings.
\n\nWe are honored to be among such prestigious publishers and we hope to continue to spearhead that growth in our quest to promote Open Access as a true pioneer in OA book publishing.
\n\n\n\n
\n'}],latestNews:[{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"},{slug:"introducing-intechopen-book-series-a-new-publishing-format-for-oa-books-20210915",title:"Introducing IntechOpen Book Series - A New Publishing Format for OA Books"}]},book:{item:{type:"book",id:"7779",leadTitle:null,fullTitle:"Path Planning for Autonomous Vehicles - Ensuring Reliable Driverless Navigation and Control Maneuver",title:"Path Planning for Autonomous Vehicle",subtitle:"Ensuring Reliable Driverless Navigation and Control Maneuver",reviewType:"peer-reviewed",abstract:"Path Planning (PP) is one of the prerequisites in ensuring safe navigation and manoeuvrability control for driverless vehicles. Due to the dynamic nature of the real world, PP needs to address changing environments and how autonomous vehicles respond to them. This book explores PP in the context of road vehicles, robots, off-road scenarios, multi-robot motion, and unmanned aerial vehicles (UAVs ).",isbn:"978-1-78923-992-8",printIsbn:"978-1-78923-991-1",pdfIsbn:"978-1-83962-285-4",doi:"10.5772/intechopen.77593",price:119,priceEur:129,priceUsd:155,slug:"path-planning-for-autonomous-vehicles-ensuring-reliable-driverless-navigation-and-control-maneuver",numberOfPages:148,isOpenForSubmission:!1,isInWos:1,isInBkci:!1,hash:"91196f0aadb70bd5cecac290401d614f",bookSignature:"Umar Zakir Abdul Hamid, Volkan Sezer, Bin Li, Yanjun Huang and Muhammad Aizzat Zakaria",publishedDate:"October 2nd 2019",coverURL:"https://cdn.intechopen.com/books/images_new/7779.jpg",numberOfDownloads:6482,numberOfWosCitations:2,numberOfCrossrefCitations:12,numberOfCrossrefCitationsByBook:0,numberOfDimensionsCitations:18,numberOfDimensionsCitationsByBook:0,hasAltmetrics:0,numberOfTotalCitations:32,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"September 6th 2018",dateEndSecondStepPublish:"November 29th 2018",dateEndThirdStepPublish:"January 28th 2019",dateEndFourthStepPublish:"April 18th 2019",dateEndFifthStepPublish:"June 17th 2019",currentStepOfPublishingProcess:5,indexedIn:"1,2,3,4,5,6,7",editedByType:"Edited by",kuFlag:!1,featuredMarkup:null,editors:[{id:"268173",title:"Dr.",name:"Umar Zakir Abdul",middleName:null,surname:"Hamid",slug:"umar-zakir-abdul-hamid",fullName:"Umar Zakir Abdul Hamid",profilePictureURL:"https://mts.intechopen.com/storage/users/268173/images/system/268173.jpg",biography:"A PhD holder, Umar Zakir Abdul Hamid has been working in the future mobility (connected and autonomous vehicle) field since 2014 with various teams in different countries and continents. Previously, he led a team of 12 engineers (of 10 different nationalities) working in the Autonomous Vehicle Software Product Development with Sensible 4, Finland. Umar is one of the recipients of the Finnish Engineering Award 2020 for his contributions to the development of all weather autonomous driving solutions with the said firm. With more than 30 scientific publications as author and editor under his belt, Umar actively participates in global automotive standardization efforts where he is a Secretary for a Society Automotive Engineers (SAE) Committee. Since the end of Summer 2021, Umar has been working as the Lead of Strategic Planning for CEVT AB in Sweden.",institutionString:"Sensible 4 Oy",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"0",totalChapterViews:"0",totalEditedBooks:"1",institution:null}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,coeditorOne:{id:"268170",title:"Dr.",name:"Volkan",middleName:null,surname:"Sezer",slug:"volkan-sezer",fullName:"Volkan Sezer",profilePictureURL:"https://mts.intechopen.com/storage/users/268170/images/system/268170.jpg",biography:"Volkan Sezer is currently an Associate Professor in the Control and Automation Engineering Department of Istanbul Technical University. He received his B.Sc. in Electronics and Telecommunication Engineering from Yildiz Technical University, Istanbul, Turkey in 2005, his M.Sc. in Mechatronics Engineering and his Ph.D. in Control and Automation Engineering from Istanbul Technical University, Istanbul, Turkey in 2008 and 2012 respectively. After his PhD. he did research in Singapore as an MIT (Massachusetts Institute of Technology) researcher in the Future Urban Mobility (FM) group. His research interests are based on the artificial intelligence for robotics and automotive technology. More specifically autonomous/semi-autonomous ground vehicles, active safety, robot autonomy and energy efficiency of hybrid electric vehicles are the main subjects of his research.",institutionString:"Istanbul Technical University",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"1",totalChapterViews:"0",totalEditedBooks:"1",institution:{name:"Istanbul Technical University",institutionURL:null,country:{name:"Turkey"}}},coeditorTwo:{id:"268176",title:"Dr.",name:"Bin",middleName:null,surname:"Li",slug:"bin-li",fullName:"Bin Li",profilePictureURL:"https://mts.intechopen.com/storage/users/268176/images/7661_n.png",biography:"Bin Li, PhD is currently working with Aptiv PLC, USA as Lead Algorithm Engineer, focusing on system architecture and algorithm development & verification of motion planning & control of autonomous vehicles. He received his PhD degree in Mechanical Engineering from Shanghai Jiao Tong University, Shanghai, China in 2010. Dr. Li has more than 15 years research experience in vehicle dynamics & control, electric vehicles, active safety and autonomous driving with over 50 papers and chapters published. He was a Researcher on active safety control for commercial vehicles at Concordia University, a Research Engineer on mobile robotic control at McGill University, and a Research Fellow on next generation electric vehicle at University of Waterloo. Dr. Li has been an active organizer for SAE World Congress and ASME conferences since 2015.",institutionString:"Autonomous Driving, Aptiv PLC",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"0",totalChapterViews:"0",totalEditedBooks:"0",institution:null},coeditorThree:{id:"268185",title:"Dr.",name:"Yanjun",middleName:null,surname:"Huang",slug:"yanjun-huang",fullName:"Yanjun Huang",profilePictureURL:"https://mts.intechopen.com/storage/users/268185/images/7662_n.png",biography:"Yanjun Huang is a Postdoctoral Fellow at the Department of Mechanical\nand Mechatronics Engineering at University of Waterloo, where he received\nhis PhD in 2016. His research interest is mainly on the vehicle holistic\ncontrol in terms of safety, energy-saving, and intelligence, including vehicle\ndynamics and control, HEV/EV optimization and control, motion planning\nand control of connected and autonomous vehicles, and human-machine\ncooperative driving. He is serving as an associate editor for several international journals.",institutionString:"University of Waterloo",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"0",totalChapterViews:"0",totalEditedBooks:"0",institution:null},coeditorFour:{id:"242513",title:"Dr.",name:"Muhammad Aizzat",middleName:null,surname:"Zakaria",slug:"muhammad-aizzat-zakaria",fullName:"Muhammad Aizzat Zakaria",profilePictureURL:"https://mts.intechopen.com/storage/users/242513/images/7663_n.png",biography:"One of the pioneering members of the Autonomous Vehicle field in Malaysia,\nDr. Muhammad Aizzat Zakaria is a senior lecturer at Universiti Malaysia\nPahang. His current research focuses on the area of intelligent vehicle\nnavigation. He has worked on the intelligent mobile robot systems of the\nautonomous vehicles. He is also interested in working with robotic system\nmodeling and mechatronic systems for robotic intelligent control applications.",institutionString:"Universiti Malaysia Pahang",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"0",totalChapterViews:"0",totalEditedBooks:"0",institution:null},coeditorFive:null,topics:[{id:"1284",title:"Autonomous Vehicle",slug:"evolutionary-robotics-autonomous-vehicle"}],chapters:[{id:"68713",title:"Introductory Chapter: Roles of Path Planning in Providing Reliable Navigation and Control for Autonomous Vehicles and Robots",doi:"10.5772/intechopen.88634",slug:"introductory-chapter-roles-of-path-planning-in-providing-reliable-navigation-and-control-for-autonom",totalDownloads:548,totalCrossrefCites:0,totalDimensionsCites:2,hasAltmetrics:0,abstract:null,signatures:"Umar Zakir Abdul Hamid, Volkan Sezer, Bin Li, Yanjun Huang and Muhammad Aizzat Zakaria",downloadPdfUrl:"/chapter/pdf-download/68713",previewPdfUrl:"/chapter/pdf-preview/68713",authors:[{id:"309668",title:"Dr.",name:"Umar Zakir",surname:"Abdul Hamid",slug:"umar-zakir-abdul-hamid",fullName:"Umar Zakir Abdul Hamid"}],corrections:null},{id:"67261",title:"Military Factors Influencing Path Planning",doi:"10.5772/intechopen.86421",slug:"military-factors-influencing-path-planning",totalDownloads:655,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"The chapter discussed and considered the factors that influence the path planning for military purposed autonomous vehicles. The planning of movement (path planning) for autonomous vehicles is complex process influenced by many categories of factors. The complexity of autonomous vehicles path planning is dramatically increasing in military operational environment when the confrontation with enemy is expected. From operational point of view, it is necessary to considered in which military domain the autonomous vehicles will operate, for example, in Land domain, Air domain or Sea domain. From tactical point of view, there will be group of common factors for each domains and group of different factors for specific domain. As much as possible factors which will be included in consideration of path planning as the part of mathematical algorithms will increase the prerequisite for successful fulfilling of assigned tasks and missions.",signatures:"Jaroslav Kozůbek, Zdeněk Flasar and Ivo Dumišinec",downloadPdfUrl:"/chapter/pdf-download/67261",previewPdfUrl:"/chapter/pdf-preview/67261",authors:[{id:"286375",title:"Ph.D.",name:"Jaroslav",surname:"Kozůbek",slug:"jaroslav-kozubek",fullName:"Jaroslav Kozůbek"},{id:"287297",title:"Prof.",name:"Zdenek",surname:"Flasar",slug:"zdenek-flasar",fullName:"Zdenek Flasar"},{id:"287299",title:"Mr.",name:"Ivo",surname:"Dumisinec",slug:"ivo-dumisinec",fullName:"Ivo Dumisinec"}],corrections:null},{id:"66530",title:"Path Planning for Autonomous Vehicle in Off-Road Scenario",doi:"10.5772/intechopen.85384",slug:"path-planning-for-autonomous-vehicle-in-off-road-scenario",totalDownloads:1208,totalCrossrefCites:0,totalDimensionsCites:1,hasAltmetrics:1,abstract:"The road topography information, such as bank angle and road slope, can significantly affect the trajectory tracking performance of the autonomous vehicle, so this information needs to be considered in the trajectory planning and tracking control for off-road autonomous vehicle. In this chapter, a two-level real-time dynamically integrated spatiotemporal-based trajectory planning and control method for off-road autonomous vehicle is proposed. In the upper-level trajectory planner, the most suitable time-parameterised trajectory with the minimum values of road slope and bank angle can be selected from a set of candidate trajectories. In the lower-level trajectory tracking controller, the sliding-mode control (SMC) technique is applied to control the vehicle and achieve the desired trajectory. Finally, simulation results are presented to verify the proposed integrated trajectory planning and control method and prove that the proposed integrated method has better overall tracking control and dynamics control performance than the conventional method both in the highway scenario and off-road scenario. Furthermore, the four-wheel-independent-steering (4WIS) and four-wheel-independent-driving (4WID) vehicle shows better tracking control performance than vehicle based on two-wheel model.",signatures:"Boyuan Li, Haiping Du and Bangji Zhang",downloadPdfUrl:"/chapter/pdf-download/66530",previewPdfUrl:"/chapter/pdf-preview/66530",authors:[{id:"18457",title:"Dr.",name:"Haiping",surname:"Du",slug:"haiping-du",fullName:"Haiping Du"},{id:"274380",title:"Ph.D.",name:"Boyuan",surname:"Li",slug:"boyuan-li",fullName:"Boyuan Li"},{id:"286924",title:"Prof.",name:"Bangji",surname:"Zhang",slug:"bangji-zhang",fullName:"Bangji Zhang"}],corrections:null},{id:"67475",title:"Vision-Based Path Finding Strategy of Unmanned Aerial Vehicles for Electrical Infrastructure Purpose",doi:"10.5772/intechopen.86689",slug:"vision-based-path-finding-strategy-of-unmanned-aerial-vehicles-for-electrical-infrastructure-purpose",totalDownloads:1037,totalCrossrefCites:1,totalDimensionsCites:2,hasAltmetrics:0,abstract:"In this chapter we present the development of automated visual inspection systems for electrical infrastructure. The inspection is performed using images acquired with an unmanned aerial vehicle (UAV). Through automated inspection routes, the state of the infrastructure can be evaluated and then the appropriate correcting measures be taken. The monitoring of power lines can be done using passive sensors such as cameras or active sensors such as light detection and ranging (LIDAR) cameras, image processing techniques, computer vision and control systems can then be used. Additionally, a three-dimensional (3D) reconstruction process is possible using images either offline or during the monitoring. An UAV with an onboard embedded computer is used to execute the computer vision and path planning algorithms. The work done shows that the proposed strategy aids in the automation of power line inspection.",signatures:"Alexander Cerón, Flavio Prieto and Luis Mejias",downloadPdfUrl:"/chapter/pdf-download/67475",previewPdfUrl:"/chapter/pdf-preview/67475",authors:[{id:"48008",title:"Prof.",name:"Alexander",surname:"Cerón",slug:"alexander-ceron",fullName:"Alexander Cerón"},{id:"82312",title:"Prof.",name:"Flavio",surname:"Prieto",slug:"flavio-prieto",fullName:"Flavio Prieto"},{id:"130744",title:"Prof.",name:"Luis",surname:"Mejias",slug:"luis-mejias",fullName:"Luis Mejias"}],corrections:null},{id:"65956",title:"Extending the Limits of the Random Exploration Graph for Efficient Autonomous Exploration in Unknown Environments",doi:"10.5772/intechopen.84821",slug:"extending-the-limits-of-the-random-exploration-graph-for-efficient-autonomous-exploration-in-unknown",totalDownloads:686,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"The autonomous construction of environment maps using mobile robots is a fundamental problem of robotics; this is because virtually all tasks performed by robots need a representation of the working environment to operate. Although many works have addressed this problem known as SLAM, it still remains open; since most of the solutions do not consider a planner that allows the robot to explore autonomously the working environment or the works that consider it, they have developed slow algorithms that do not guarantee a total coverage of the environment or an optimal development of the exploration, which may result in maps of poor quality or definitely not usable given this lack of information. Thus, this work presents a new exploration method based on the random exploration graph (REG), which, unlike its predecessor, defines a systematic analysis of the next positions to be explored eliminating randomness in decision-making and thus minimizing the amount of movements that the robot must make to reach them and the time required to achieve total coverage of the environment. Additionally, a series of tests carried out on the proposed method are presented, and the results obtained in classical variables such as time and distance allow to validate the efficiency of our approach.",signatures:"Alfredo Toriz Palacios and Abraham Sánchez López",downloadPdfUrl:"/chapter/pdf-download/65956",previewPdfUrl:"/chapter/pdf-preview/65956",authors:[{id:"223703",title:"Ph.D.",name:"Alfredo",surname:"Toriz Palacios",slug:"alfredo-toriz-palacios",fullName:"Alfredo Toriz Palacios"},{id:"286711",title:"Dr.",name:"Abraham",surname:"Sánchez López",slug:"abraham-sanchez-lopez",fullName:"Abraham Sánchez López"}],corrections:null},{id:"66432",title:"Model of the Optimal Maneuver Route",doi:"10.5772/intechopen.85566",slug:"model-of-the-optimal-maneuver-route",totalDownloads:887,totalCrossrefCites:7,totalDimensionsCites:9,hasAltmetrics:0,abstract:"The chapter deals with the mathematical model for planning the optimal movement route, which has been implemented in the Tactical Decision Support System (TDSS). The model processes and evaluates the data contained in the five raster layers, which are tactically relevant for planning the movement route of troops or autonomous vehicles on the battlefield. The basis for calculating the optimal movement route is a ground surface layer, which is then modified by algorithmic and criterion relationships with the layers of hypsometry, weather attack, and the activities of enemy and friendly units. The result of mathematical model calculations is a time-optimized and safe movement route displayed on the topographic basis. The experiments realized have verified the function of the optimal movement route model when neither the reconnaissance group nor the autonomous vehicle was observed by the enemy. The total time of the UGV with the use of the TDSS to cover the route of maneuver was 67 minutes shorter than the real time of the BRAVO group movement with the use of the TDSS and 105 minutes shorter than the real time of the ALFA group without the use of the TDSS. The comparison of responses to the attack shows that the BRAVO group using the Maneuver Control System (MCS CZ) as part of the TDSS has destroyed the attackers faster by 71 seconds than the ALFA group without the use of the TDSS.",signatures:"Jan Nohel, Petr Stodola and Zdeněk Flasar",downloadPdfUrl:"/chapter/pdf-download/66432",previewPdfUrl:"/chapter/pdf-preview/66432",authors:[{id:"287297",title:"Prof.",name:"Zdenek",surname:"Flasar",slug:"zdenek-flasar",fullName:"Zdenek Flasar"},{id:"162332",title:"Prof.",name:"Petr",surname:"Stodola",slug:"petr-stodola",fullName:"Petr Stodola"},{id:"286639",title:"Dr.",name:"Jan",surname:"Nohel",slug:"jan-nohel",fullName:"Jan Nohel"}],corrections:null},{id:"68806",title:"Path Planning Optimization with Flexible Remote Sensing Application",doi:"10.5772/intechopen.86500",slug:"path-planning-optimization-with-flexible-remote-sensing-application",totalDownloads:808,totalCrossrefCites:2,totalDimensionsCites:2,hasAltmetrics:0,abstract:"The purpose of the path planning optimization is to find the most favorable route between starting and arrival points based on defined criteria and target functions. The change in the characteristics of each route becomes complicated when there is an increase in the number of intermediate points. This study predominately analyses the monitoring of a limited area. The author demonstrates how the path of the autonomous systems will change in different conditions and further introduces the possibility of using mobile remote sensing systems. The test is performed firstly in 2D flat area, then 3D spaces, and then—taking a forest fire as an example—the ideal conditions changed to reality. The study reveals findings on efficiency, based both on professional and economic considerations. The utilization of remote sensing technologies was found to optimize the observation of the given area generating new problems, such as what is the size of the monitored area at a given moment and how can we increase it for the higher effectiveness. An increase in the size of the monitored area results into an efficient and functional autonomous system albeit generating a shorter and modified path. Mobile autonomous systems therefore can be replaced by stable systems; simultaneously under real conditions, they can be more efficient than stable ones.",signatures:"Agoston Restas",downloadPdfUrl:"/chapter/pdf-download/68806",previewPdfUrl:"/chapter/pdf-preview/68806",authors:[{id:"286465",title:"Ph.D.",name:"Agoston",surname:"Restas",slug:"agoston-restas",fullName:"Agoston Restas"}],corrections:null},{id:"66691",title:"Distributed Optimization of Multi-Robot Motion with Time-Energy Criterion",doi:"10.5772/intechopen.85668",slug:"distributed-optimization-of-multi-robot-motion-with-time-energy-criterion",totalDownloads:656,totalCrossrefCites:2,totalDimensionsCites:2,hasAltmetrics:0,abstract:"This paper is an application of a special case of distributed optimization problem. It is applied on optimizing the motion of multiple robot systems. The problem is decomposed into L subproblems with L being the number of robot systems. This decomposition reduces the problem to solving a single robot problem. The optimization problem is solved via a distributed algorithm, utilizing subgradient method. A global objective function is set as the sum of individual robot objectives in time and energy. Constraints are divided into two sets, namely, robot-individual constraints and robots’ interactions (collision) constraints. The approach is applied for the case of wheeled mobile robots: we are able to generate in parallel for each robot an optimized control input trajectory and then illustrate it in simulation examples.",signatures:"Mohamad T. 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Continuous and high-concentration exposure of heavy metals can cause various physiological and biochemical problems to the environment and human being. Thus, the detection of these harmful metal ions has become very important from industrial, environmental and biological point of view. This is a challenging subject for analytical chemists due to the sensitivity, detection limits and acceptable toxicity levels set by global regulation bodies [1, 2]. In addition, similar chemistry of heavy metals is fastidious with respect to selectivity of the determination method. A variety of standardized analytical methods for the detection of metal ions are available. However, only some of them have found application in routine analysis. Recommended procedures for the detection of heavy metals in water samples include photometric methods, flame or graphite furnace atomic absorption spectroscopy (AAS), inductively coupled plasma emission or mass spectrometry (ICP-ES, ICP-MS), total reflection X-ray fluorimetry (TXRF) and anodic-stripping voltammetry (ASV) [3, 4, 5]. These methods offer good limits of detection and wide linear ranges, but they are time consuming, require high cost analytical instruments trained operating personals and high maintenance which is a financial burden to analytical laboratories. Furthermore, the required sample pre-treatment and preparation time introduce systematic errors in the analysis. However, the development of fast, economical and portable devices for metal ion detection has grown tremendously over the past 10 years. Particularly, chemo-sensors, which offer the ability for both on-line and field monitoring, has attracted many industries in the detection of metal ions in water [6]. This has allowed for quick and continuous supervision monitoring of drinking or ground water and lentic or lotic watercourses. An ideal sensor should provide good sensitivity, high selectivity towards the target analyte, mathematical relationship of signal output to the amount of analyte, fast response time, good signal-to-noise ratio and long-term stability [7]. A variety of sensors have been developed, and these include DNAzymes sensors, optical sensors, electrochemical, colorimetric and fluorescent sensors [1, 2, 3, 4, 5, 6, 7, 8, 9, 10] just to mention a few. This chapter aims to introduce the reader to the use of quantum dots (QDs) as metal ion sensors.
A chemical sensor can be defined as ‘a portable miniaturized analytical device, which can deliver real-time and on-line information in the presence of specific compounds or ions in complex samples’ [11]. Chemical sensors can be categorized into electrochemical, optical, mass-sensitive and heat-sensitive, according to the types of transducer. Of these classifications, optical sensors have been the most widely used as contact-less detectors, counting or positioning of parts. An optical sensor device consists of the following components: (a) the recognition element, where specific interaction and identification of the analyte takes place; (b) the transducer element that converts the recognition process into a measurable optical signal; (c) an optical device (process unit) which consists of at least a light source and finally (d) a detector which detects and converts the change of optical properties and amplifies the signal into a unit readout. The optical properties measured can be absorbance, reflectance, luminescence, light polarization, Raman and others. Optical sensors have found many applications in various fields, including biomedical, clinical, environmental monitoring and process controlling [12, 13, 14, 15, 16, 17, 18]. They are an attractive analytical tool, whenever continuous monitoring and real-time information is desired. They can track sources of contamination in an industrial process, follow the formation and movement of environmental pollutants and can raise the alarm when a toxic species exceeds an expected level of exposure. For environmental analysis, single-use test strips for various ions, including heavy metals, are commercially available [19], which have their limitations in accuracy and reversibility. In recent years, activities applying optical sensors for the determination of heavy metals increased [20]. The most significant methods are the application of quenchable fluorophores or indicator dyes.
Semiconductor quantum dots (QD) are nanocrystalline materials that confines the motion of the charge carriers in three spatial directions. These crystals are intermediate state of matter that display properties present in neither bulk nor molecular systems. The physical and electronic properties of QDs are strongly dependent on size (number of atoms). Their importance was recognized by the 2000 Nobel Prize in Physics awarded to Alferov and Kroemerin for their basic work on information and communication technology using the semiconductor heterostructures. QDs are generally made as binary semiconductor nanocrystals from groups II–VI (e.g. CdSe, ZnS, etc.), groups IV–VI (e.g. PbTe, PbS) or groups III–V (e.g. InAs, InP) in the periodic table [21]. Moreover, QDs of Si, Ge, Ag, also of carbon and graphene [22, 23, 24] and ternary QDs (from I–VI) have been reported [25, 26]. QDs have received much attraction because of their stable, tunable, bright and narrow photoemission, high chemical and photo bleaching stability, processability and surface functionality and they offer many advantages in comparison with conventional fluorophore. Thus, a new generation of QDs based sensor containing the unique optical properties of QDs has been constructed for sensing molecules and ions in ultratrace level.
Colloidal synthesis of QDs widely employs a ‘bottom-up’ approach where the crystals are nucleated and grown from the precursor materials dissolved in a suitable solvent in the presence of a stabilizing agent. This approach was pioneered by L. Brus, an American scientist when he was at Bell laboratories, New Jersey, in the late 1970s and carried over by some of his post docs notably Moungi Bawendi and Paul Alivisatos. Because of its mild preparative conditions, this method is also called as a wet chemical route and has become popular among the scientists and industrialists for their usefulness in the biomedical and analytical fields. Different types of QDs such as alloyed QDs, core/shell QDs, impurity-doped QDs, polymer-QD composites with desired size and desired functional group on the surface can be prepared by colloidal synthesis, which are difficult to obtain by the other methods.
High-quality colloidal quantum dot crystals can be prepared in organic medium. Organic QDs obtained by this method have good degree of monodispersity and high photoluminescence quantum efficiency. This method became familiar after the synthesis of CdSe QD by Murray et al. in 1993 [27, 28]. The precursors for CdSe QDs chosen by Murray were dimethylcadmium (Me2Cd) and TOPSe (Se dissolved in trioctylphosphine (TOP). The rapid injection of both the precursors together into the hot solution of trioctylphosphine oxide (TOPO) at ~300°C produced yellow/orange CdSe nanocrystallites. However, the use of expensive and/or hazardous organic reagents, harsh reaction conditions, and hydrophobicity of the as-prepared QDs are some of the shortcomings of the organic synthetic routes. To make the QDs water soluble, hydrophobic nature of the QDs surface should be converted into hydrophilic nature by surface encapsulation or ligand exchange. Surface modification processes are tedious, involving multiple steps and usually produce materials with reduced optical properties compared to the parent organic materials [29, 30].
On the other hand, QDs can also be synthesized in aqueous medium directly. For example, in aqueous synthesis of thiol-stabilized CdTe QDs, Cd2+ dissolved in water medium would be reacted with a HTe− solution in the presence of water-soluble thiol ligands. Refluxing of the above mixture produces CdTe QDs dispersion. Rajh et al. used a thiol (3-mercapto-l,2-propane-diol) as a stabilizing agent to prepare CdTe QD with 20% photoluminescence quantum yield (PLQY) [31]. Afterwards, numerous thiols were investigated as stabilizing agents [32, 33, 34]. Compared with organic phase synthesis, aqueous synthesis involves less toxic precursors, inexpensive and produces excellent water-soluble and biocompatible products.
Most of the QDs, which are prepared in aqueous conditions, have low stability and low PLQY. As the surface of QDs is highly reactive, they have a high possibility to aggregate in the presence of heat, light, air or some ions. This may cause surface, which further reduced the PLQY. A number of techniques have been used to improve the particle stability, PL efficiency and biocompatibility of the QDs. These include photo-irradiation [35, 36], ultrasonic irradiation [37], doping with transition metals [38, 39, 40] and inorganic passivation [41]. Among them, inorganic passivation and doping techniques are the most widely investigated.
Doped semiconductor nanocrystals have been studied extensively in the past two decades since Bhargava et al. [42] reported on Mn-doped ZnS (Mn:ZnS). They stated that it could be possible to obtain efficient emission from the dopant centres even if the host nanocrystals were not of high quality. The PL of doped QDs is purely dopant-specific. Based on this, different colour-emitting (blue to red) QDs doped with metals (Al3+), transition metals (Cu+, Mn2+) and halides (F−) have been reported in the literature [43, 44, 45]. Doped nanocrystalline II–VI semiconductors incorporating rare earth (RE) ions such as Tb3+, Eu3+ and Er3+ have also been reported [46, 47]. However, due to the dissimilar chemical properties (e.g. ionic radius, valence state) between the RE ion and host cation (Cd2+, Zn2+), efficient doping of RE ions into II–VI semiconductor host is not favourable.
In contrast to RE ions, the chemical properties of Mn2+ are very similar to those of Cd2+ (or Zn2+); thus, incorporating Mn2+ into II–VI semiconductor host is much easier. Mn-doped semiconductors are potential luminescent and spintronic materials. The Mn2+ ion, used in many luminescent materials, has a d5 configuration. The Mn2+ ion exhibits a broad emission peak, whose position depends strongly on the host lattice due to changes in crystal field strength with host. The emission colour can vary from green to deep red, corresponding to a 4T1–6A1 transition. Since this transition is spin-forbidden, the typical luminescent relaxation time of this emission is of the order of milliseconds.
Doping of the impurity in the host material can be carried out via nucleation-doping or growth-doping processes [48] as shown in Figure 1. In a former process, both host and dopant materials are subjected to nucleation at the same time followed by growth of the host material, whereas in the growth-doping process, the host material alone is nucleated and grow for certain time, followed by doping and re-growth of host material again.
Schematic representations of nucleation- and growth-doping techniques.
QDs possess high surface-to-volume ratio and any change occurring at the surface can influence its surface-dependent properties; hence, luminescence of QDs is sensitive to surface states. Any species that interact directly with the QDs surface by physical or chemical means interferes with radiative recombination of the exciton leading to ‘quenching’ or enhancement of QDs fluorescence. Following this approach, QDs fluorescent probes can be designed by modifying their surface with suitable ligands so that they can selectively recognize the target analyte.
QD-based sensors are most frequently used to detect metal cations. Generally, metal ion quenches the QDs fluorescence via three different types of interaction: (i) by exchanging the metal cation of QDs, (ii) by displacing the capping ligand from the QDs surface and (iii) by binding with surface ligands [48]. The first two types are based on the competitive interaction between the analyte metal ion and the surface metal ion of QDs to bind with counterpart anion or surface-capping ligand, respectively, thus forming a stable lower solubility product. For instance, CuSe has a lower solubility than CdSe. As a result, surface Cd2+ ions in CdSe QDs can be easily exchanged by analyte Cu2+ ions to form CuSe particles on the surface of QDs. Similarly, in the case of glutathione (GSH)-capped CdSe QDs, Pb2+ ion binds with the thiol group of the capping GSH followed by displacement from QDs surface due to its higher binding affinity than Cd2+. However, the quenching mechanism in both cases is different. The electron and/or hole transfer from the CdSe to the CuSe energy levels (case i) is much faster than the process of fluorescence generation in the CdSe moiety, thus leading to quenching of QD fluorescence. The CuSe particles chemisorbed on CdSe QDs alters the bandgap energy level and crystal lattice. Hence, the shift in absorption, emission and X-ray diffractometry (XRD) patterns of the QDs after the interaction with the analyte metal ions is the indicative of this metal ion exchange process. By contrast, removing the capping ligand from the QDs surface by analyte metal ion (case ii) depassivates the QDs surface and creates drastic imperfections on the QDs surface, resulting in fluorescence quenching. In the ion-binding type (case iii), divalent analyte metal ions adsorb to the QD surface by electrostatic interaction with the capping carboxylic ligands, thus coordinating several QDs together, leading to the formation of closely packed QD aggregates. This causes a decrease in the luminescence intensity due to self-quenching mechanism. The quenching by this interaction is sensitive to pH and ionic strength of the medium. Under acidic conditions, quenching by metal ions is very low due to non-availability of carboxylate for the interaction with metal ions.
Apart from the metal ions, molecules such as phenolic compounds, H2O2 [49], 2,4,6-trinitrotoluene (TNT) [50, 51] and glucose [52] can also be detected by fluorometric titration with QDs. The electron-accepting nature of phenolic compounds and TNT shuttled the electron from the conduction band to the valence band of the excited QDs, whereas H2O2 oxidizes the surface of QD and destroys its lattice structure resulting in the PL quenching. Glucose can be indirectly detected knowing that glucose can produce H2O2 on catalytic oxidation by glucose oxidase.
Most of the QDs that were investigated for fluorometric sensing are based on cadmium QDs; however, a major drawback for their application is the toxicity of cadmium ion. Less toxic particles like doped ZnS or ZnSe QDs may be interesting alternatives for biological imaging and other applications. Mn2+-doped ZnS quantum dots have been extensively investigated in various fields [53]. Fang et al. synthesized high-quality water-dispersible Mn2+-doped ZnSe core/ZnS shell (Mn:ZnSe/ZnS) nanocrystals directly in aqueous media with MPA as the capping ligand [54]. They observed that there was almost no dopant Mn emission in the Mn:ZnSe d-dots and bright Mn luminescence was observed after overcoating the ZnS shell around the Mn:ZnSe dots. In the present work, Mn-doped ZnSe (Mn:ZnSe) QDs have been synthesized by a wet chemical method using 3-mercaptopropionic acid (3-MPA) as capping agent and characterized by various analytical tools. The nucleation-doping method was adopted because it would form a structure similar to core-shell (MnSe/ZnSe) with a diffuse interface. The PL of the resulting QDs was examined in the presence of different metal ions to check its selective response.
All chemicals were of analytical grade and were used without further purification. All solutions were prepared using doubly distilled water. Zn (CH3COO) 2•2H2O (ZnAc2) and Mn (CH3COO) 2 • 4H2O (MnAc2) were obtained from Sisco Research Laboratories (SRL) Pvt. Ltd., Mumbai. Selenium powder (99.99%) 3-mercaptopropionic acid and sodium borohydride (NaBH4) were the AR reagents from Sigma Aldrich, Bangalore. Phosphate buffer at a pH of 7.0 was prepared according to literature. The chloride solutions of different metal ions were prepared at the concentration of 1 × 10−4 M using doubly distilled (DD) water.
Aqueous colloidal solution of Mn:ZnSe QDs was synthesized using MPA as capping agent as depicted in Figure 2. Typically, 0.25 mmol of selenium powder and 0.6 mmol of NaBH4 were loaded in a round-bottomed flask containing 10 mL of N2-purged DD water. The reaction mixture was heated at 100°C for 15 min under N2 flow until the black selenium powder disappeared completely to give a clear colourless solution. On the other hand, 0.5 mmol of ZnAc2 and 0.0015 or 0.003 mmol of MnAc2 were dissolved in 25 mL of DD water followed by the addition of MPA. The pH of the reaction mixture was adjusted to 10.3 by adding 1 M NaOH solution and purged with N2 for 20 min. Then, freshly prepared NaHSe solution was added followed by stirring at 50°C for 2 h. The molar ratio of Zn to Se to MPA was set at 1:0.5:2, whereas Zn to Mn was 1:0.03 or 1:0.06. The as-synthesized nanoparticles were purified by precipitation with ethanol, followed by centrifugation and vacuum drying.
Synthesis of Mn-doped ZnSe QDs.
To investigate the optical, crystal structure and morphological properties of QDs, they were characterized by various analytical techniques. ultraviolet-visible (UV-vis) absorption spectra were recorded with a Shimadzu, (Model UV-1800) UV-visible spectrophotometer, Japan. The samples were dispersed in doubly distilled water and loaded in a 4.5-mL precleaned quartz cuvette with 1-cm optical path. The entire spectrum was scanned against the background spectrum of water. PL measurements of the samples were performed in a 4.5-mL quartz cuvette at ambient conditions on a Perkin Elmer LS5B spectrofluorimeter. For a given sample, the excitation wavelength was identified from the absorption spectrum and it was fixed to scan the emission wavelength. X-ray powder diffraction patterns of the samples were recorded at ambient conditions by using PANanalytical X’Pert PRO diffractometer with monochromatic Cu-Kα1 radiation (λ = 1.5418 Å), 2θ ranging from 10 to 80° in steps of 0.017°/s. The accelerating voltage was set at 40 kV and the current flux was 30 mA. Transmission electron microscopy (TEM) images of QDs were obtained from the FEI Tecnai G2 (T-30) instrument with the operating voltage of 250–300 kV. A small amount of sample for TEM analysis was ultra-sonicated in ethanol or water for a few minutes and then dropped on carbon-coated copper grids. The sample grid was then kept in vacuum desiccators prior to the analysis.
Fluorescence sensitivity of the QDs towards different metal ions was carried out on a fluorescence microplate reader (Turners Biosystems-Modulus Microplate Multimode Reader-9300-010). Stock solutions of different metal ions (Li+, Na+, K+, Mg2+, Ca2+, Ba2+, Al3+, Mn2+, Fe2+, Co2+, Ni2+, Cu2+, Zn2+, Ag+, Cd2+, Hg2+ and Pb2+) were prepared by dissolving their respective nitrate or chloride salts. Aqueous solution of QDs with the OD = 0.1 was prepared by diluting the stock solution of QDs. The solution of 50 μL was dropped into each well of a 96-well plate followed by filling with different metal solutions to obtain the final volume of 200 μL. The excitation wavelength was selected according to the absorption spectrum of QDs and the relative fluorescence intensity was measured with the plate reader. The standard deviations were calculated from at least six measurements.
Figure 3a shows the absorption spectra of 3 and 6% Mn:ZnSe QDs along with undoped QDs. The Mn content is represented here as the mole % against the host metal (Zn) which is considered as 100% according to the experiment. Compared with bulk ZnSe having the bandgap of ~2.8 eV, the absorption band edge of both doped and undoped QDs is blue-shifted (400–500 meV) indicating quantum confinement of the particles. Furthermore, the bandgap of Mn:ZnSe is blue-shifted with respect to undoped ZnSe QDs under the same experimental conditions, which reveal the formation of smaller-sized particles. This is consistent with the results by Mahamuni et al [55]. The synthesis process itself is affected by Mn additive. In addition, the spectrum of 3% Mn:ZnSe QDs is slightly blue-shifted from that of 6% Mn:ZnSe QDs. Because of lower Mn/Se content, the former has relatively smaller-sized nuclei formed in the nucleation step which leads to a slight blue shift.
(a) Absorption and (b) PL spectra of undoped and Mn-doped ZnSe QDs.
The PL spectra of the 3 and 6% Mn:ZnSe QDs along with undoped QDs (λexc = 365 nm) are shown in Figure 3b. The spectrum of undoped ZnSe QDs shows broad emission band centred at 480 nm and a small shoulder at 398 nm assigned to trap-state emission and band-edge emission, respectively. These two emissions appearing together are often observed in CdSe, ZnSe nanocrystals and their sulphur analogues. As discussed by Denzler et al [56], the bulk defects such as vacancies (Schottky defects) and interstitials (Frenkel defects) are the main source of trap states in the aqueous ZnSe QDs. With cubic zinc blende structure (by XRD), ZnSe usually has Schottky defects predominant over Frenkel defects. Therefore, the observed photoluminescence of QDs could be ascribed to a recombination of electrons at the selenium vacancy energy levels because of low Se/Zn ratio synthetic conditions. There are many possible recombination paths through many trap-state emissions, each with different emission energy, causing the relatively wide emission peak. The PL spectrum of as-prepared ZnSe QDs has the full width at half maximum of about 110 nm.
The PL spectrum of 3% Mn:ZnSe QDs exhibits a new band at 579 nm in addition to trap- and band-edge emissions. The appearance of this new emission in the Mn-doped QDs is attributed to Mn2+-related 4T1→6A1 emission. This transition is spin-forbidden but is allowed because of crystal field effects [55]. Fang et al [54] notified that if the dopant ions are adsorbed on the surface of the host nanocrystal instead of being incorporated into its lattice, no dopant emission is observed and further the host emission is drastically quenched because a loosely adsorbed dopant ion can easily act as a surface trap that quenches the host PL [57]. However, in the present system, after doping with 3% Mn, the luminescence of host emission is enhanced by 7.7 times along with the appearance of Mn emission. This indicates the successful incorporation of Mn2+ in the host ZnSe lattice. The enhancement of host PL is mainly attributed to the reduction of non-radiative energy centres by Mn2+ doping. Table 1 shows the PL-integrated intensity ratios calculated from the spectra.
PL-integrated intensity ratios of Mn:ZnSe QDs | |||||||||
---|---|---|---|---|---|---|---|---|---|
Mn doping | Band-edge | Trap | Mn | Cumulative | Trap/Band edge | Trap/ Mn | |||
Peak (nm) | I/I0% | Peak (nm) | I/I0% | Peak (nm) | I/I3% | I/I0% | It/Ib | It/IMn | |
0% | 397 | 1.0 | 480 | 1.0 | – | – | 1.0 | 82.2 | – |
3% | 386 | 6.7 | 461 | 7.7 | 579 | 1.0 | 10.1 | 95.7 | 3.2 |
6% | – | – | 473 | 3.1 | 584 | 1.4 | 6.5 | – | 0.9 |
PL properties of undoped and Mn-doped ZnSe QDs.
*t = trap, b = band edge. (PL peak position and the corresponding integrated intensity are obtained by Gaussian fitting.)
With further increase in the Mn concentration from 3 to 6%, the resultant doped QDs show increased Mn emission followed by subtle red-shift indicating the increase in Mn content in host. However, the host-trap emission is decreased and no band-edge emission is significantly observed. Furthermore, instead of the expected two-fold increase in the Mn emission (from 3% doped), only 1.4-fold increase is observed. The reason might be the combination of the following three processes: (i) non-radiative energy transfer between neighbouring Mn2+-dopant ions which quenches Mn emission [58], (ii) adsorption of some Mn ions on the surface instead of incorporation into the host lattice which quenches both host and Mn emission and (iii) initially formed larger MnSe. As the environment of the doping ions in larger nuclei is not as uniform as that in smaller ones, the PL emission performance of doped QDs with larger nuclei will not be satisfactory as those with smaller nuclei [57]. Overall, the PL peak position of the host is in tune with the corresponding band-edge absorption. The 3% doped sample has the highest emission peak intensity, followed by the 6% and then the 0% sample. The above results are interesting that the ratio of the dual-colour emissions (blue and orange) of the Mn-doped ZnSe QDs could be controlled by tuning the Mn-doping levels in the QDs.
X-ray diffraction pattern of the 3% Mn:ZnSe QDs is presented in Figure 4. Broad diffraction peaks are observed and are attributed to the nanocrystalline nature of the material. The XRD peaks are close to the characteristic peaks corresponding to the (111), (220) and (311) planes of cubic zinc blende ZnSe. Cubic structures are often obtained in the low-temperature aqueous synthesis of ZnSe QDs. This indicates that the incorporation of Mn2+ into the host ZnSe does not bring any obvious change in the crystal lattice and the structure [37, 54]. TEM image of the 3% Mn:ZnSe QDs (Figure 5a) shows that QDs are spherical in nature with the average diameter of ~4 nm. Some of the aggregates of the particles are also seen. The energy-dispersive X-ray spectroscopy (EDS) spectrum (Figure 5b) confirms the presence of Mn, Zn and Se and the purity of the sample.
XRD patterns of 3% Mn-doped ZnSe QDs.
(a) TEM image and (b) EDS of 3% Mn-doped ZnSe QDs.
The fluorescence titrations of the 3% Mn:ZnSe QDs (PL, λmax = 461 nm) with various metal ions are shown in Figure 6a. The fluorescence intensity (F) is measured with excitation at 365 nm. The PL of blank QDs is used as a control (F0). From the figure, it is observed that QDs show maximum response to mercury ions (Hg2+), little response to Ni2+, Cu2+ and Pb2+ ions and almost no response to other metal ions. About 74% of the PL intensity is quenched after the addition of 30 μM L−1 of Hg2+ ions.
(a) Effect of metal ions (30 μM L−1) on the PL intensity of 3% Mn-doped ZnSe QDs at pH 10.8. (b) The plot of PL intensity of 3% Mn-doped ZnSe QDs versus [Hg2+] ions and (c) the corresponding Stern-Volmer relationship.
The influence of [Hg2+] ion on the QDs fluorescence was studied. Figure 6b shows the quenching behaviour of Hg2+ ions on the PL intensity of QDs. The PL intensity is quenched drastically and then slightly with the increase in [Hg2+] ions. The fluorescence quenching with respect to the concentration of quencher was analysed using the Stern-Volmer equation. The plot of F0/F versus [Hg2+] as shown in Figure 6c exhibits a good linear relationship up to 30 μM L−1 with a correlation coefficient R2 = 0.9918. The limit of detection (LOD) was calculated according to the following equation:
where 3 is the signal-to-noise ratio, S0 is the standard deviation of blank measurements (n = 6) and Ksv is the slope of calibration graph. LOD of the present probe towards [Hg2+] under the experimental conditions is found to be 6.63 × 10−7 M L−1.
The fluorescence quenching can be explained in terms of strong binding of quencher metal ions (Hg2+) on the surface of QDs. It is known that the solubility HgSe (Ksp = 2 × 10−53) is extremely lower than that of ZnSe (Ksp= 3.6 × 10−26). The low solubility product is always preferred in a solution and hence the quencher metal ions (Hg2+) displace the Zn on the surface of QDs and form a lower solubility product (HgSe) which deposit on the surface of the QDs
The formed particles of HgSe, both isolated and aggregated, can quench the luminescence of QDs by facilitating non-radiative annihilation of charge carriers, which act as electron-hole recombination centres [59]. However, mere Ksp values are not the sole factors in fluorescence quenching. In addition, surface ligands have profound effects on the fluorescence response of QDs to metal ions [60]. They play a critical role in metallic ion selectivity [61]. Also, the quenching of luminescence of the QDs can occur partly through ion binding followed by photoinduced electron transfer process from the thiol ligand to Hg2+ ions on the surface of QDs. The schematic representation of fluorescence quenching is shown in Figure 7. Theoretical calculation and further study are in progress to gain an insight into the mechanism of fluorescence quenching.
Schematic representation of fluorescence quenching of QDs by metal ions.
In summary, water-soluble MPA-capped Mn-doped ZnSe QDs were synthesized using nucleation-doping method. The absorption spectra of the as-synthesized QDs were blue-shifted in relation to the bulk counterparts due to quantum confinement. The QDs exhibited dual-colour emission (blue and orange). The intensity ratio of the dual-colour emission can be varied by tuning the Mn-doping percentage. It was found that 3% Mn doping in the ZnSe crystal lattice increases the fluorescence (blue) of ZnSe QDs by 10-fold due to the reduction of non-radiative energy centres. Furthermore, Mn2+-related 4T1→6A1 (orange) emission characteristic of Mn doped in the ZnSe host was observed. The as-prepared QDs exhibited a cubic crystal structure according to XRD patterns. TEM images showed aggregates of tiny spherical particles with the average diameter of ~4 nm. The as-prepared Mn3%:ZnSe QDs were treated with different metal ions and were found to be highly selective to Hg2+ ions and exhibit pleasing LOD. The possible mechanism of sensing by quenching was also proposed. These studies on metal ion sensing by fluorescent QDs have demonstrated their potential as chemical sensor which can be developed for industrial applications.
Olive oil occupied a key role in ancient Roman cooking and its culinary use expanded along with the Roman Empire, laying the foundation for what we now refer to as the Mediterranean diet. The culinary use of olive oil takes four basics forms: as a preservative, as a cooking medium, as an ingredient and as a condiment [1]. This chapter has a central focus on EVOO as a cooking medium.
As a cooking medium EVOO has a many functions, such as transferring heat from the heat source to the food, acting as a lubricant to prevent food from sticking to the cooking surface, adding flavour, crust and creating a more visually appealing look to the food [1]. It is an extremely healthy oil to use for all types of cooking and there is a lot of existing and emerging research related to the health benefits due to high levels of antioxidants (some of which are unique to EVOO) and the ability of the oil to enhance the health attributes of some ingredients once cooked [2, 3, 4].
However, myths related to cooking with EVOO have been prevalent from time to time, creating a lot of confusion for consumers.
Some of the prevalent myths related to cooking with EVOO are listed in Table 1.
Chemical reactions such as hydrolysis, oxidation, and polymerisation are prone to occur when edible oils are heated. Heating oils at high temperatures or for long periods of time can generate decomposition products such as free fatty acids (FFAs), alcohols, cyclic compounds, and polymers. Several factors can affect or influence these reactions, such as the type and quality of the oil, the kind of food used in cooking, the time and temperature of cooking and the food/oil ratio. These chemical reactions can affect both the nutritional value and the organoleptic properties of the oil. In addition, some of the products formed through oil decomposition may have adverse effects on human health. Physical changes in oil occur during heating and include increased viscosity, darkening in colour, and increased foaming. At the same time, the smoke point of the oil decreases [14, 15, 16, 17, 18].
There are two major properties of cooking oils commonly believed to dictate the behaviour of that oil, and subsequent safety when exposed to high cooking temperatures: smoke point and oxidative stability. While oxidative stability is a reasonable predictor of an oils’ ability to withstand heat, initial smoke point has proven to have very little correlation with the oils’ stability under heat while cooking, and the formation of polar compounds [5].
The smoke point is defined as the temperature at which a visible and continuous bluish smoke appears. At this point sufficient volatile compounds, such as FFAs and short chain oxidation products are emerging and evaporating from the oil.
The smoke point of an oil generally increases as the FFA content decreases, and the degree of refinement increases [19, 20].
The smoke point should not be considered a reliable measure of an oil’s stability and suitability for cooking for the following reasons:
The smoke point changes when an oil is heated, therefore it is not the same during the whole cooking process. The smoke point decreases faster when heating oils with a higher polyunsaturated fat content, such as in seed oils, than when heating oils with less poly-unsaturation and greater monounsaturated fat levels such as in EVOO [21].
The chemical fraction that mostly determines the smoke point of an oil is the FFA fraction which is under 1% of the total oil composition. This means that when the oil reaches the smoke point, only a minor part of it is evaporating and does not indicate the deterioration of the fat itself. In fact, studies have shown that the levels of FFA are not a reliable indication of deterioration of cooking fat [14].
When determining the smoke point, a small volume of oil is heated using a little brass cup in a confined and dark environment (Figure 1). Studies have shown that the smoke point rises when using a bigger container or a larger volume of oil in the presence of air. As a result, when cooking in a kitchen, smoke point temperatures could be greater than the ones that have been reported in the literature [22, 23, 24]. Thus, exact smoke point temperatures cannot be given [21, 24].
The standard procedure used to establish the smoke point relies heavily on the ability of the worker to determine visually the point at which the oil begins to smoke. This means that there can be analyst subjectivity when using this test procedure [19, 24].
The refining process used to produce other vegetable oils such as canola, peanut and rice bran oils involves high temperatures to neutralise FFAs. This gives the oils a higher smoke point but also produces secondary oxidation products which have been shown to have a detrimental effect on human health.
Smoke point determination equipment.
When heating oils, the process of fat oxidation is accelerated. Fat oxidation is where fat molecules interact with oxygen, leading to the potential formation of harmful compounds. Many authors agree that oxidative stability is the best predictor of the behaviour of oil during cooking [5, 16, 25].
Industrially and technically, the ability of an oil to withstand heat is measured by its resistance to the formation of polar compounds.
Non-volatile polar compounds, triacylglycerol (TAG) dimers and polymers are the main deterioration products of cooking oils. Several studies have associated these substances with certain types of cancer and neurodegenerative diseases including Alzheimer’s and Parkinson’s disease [26, 27]. However, this negative effect on health is related to the dose of these components. National and International legislation has identified that no more than 24–27% of polar materials in the final oil is a safe limit for human consumption [27]. These limits are made to ensure the oils used in cooking operations are safe for human consumption. When storing food after being cooked is required, then the recommended end point of polar compounds in the oil is <10% [14, 27].
Laboratory research is extremely important to understand the frying process and what the toxicological limits are to establish guidelines for consumers. However, it is important to highlight that sometimes the research completed with cooking oils has been pushed to the point of abusing the oils. These are extreme heating conditions and the results obtained do not always represent real-life situations, especially during home cooking. Therefore, proper judgement when drawing conclusions needs to be made. When cooking at home, normally one does not reach excessive temperatures for prolonged periods of time that deteriorate either the food or the oil in a way that makes them inedible or unsafe [27].
Edible oils are composed of triacylglycerols (> 96%) and endogenous minor components. It is generally agreed that the inherent composition of edible oils exerts considerable influence on their heating stability [15, 18]. In the interest of understanding better why we can, and we should cook with EVOO, it is important to review first its chemical composition. EVOO has a high level of oxidative stability when compared to other types of cooking oil and is less likely to undergo oxidation. This is primarily attributed to the following factors:
EVOO contains high levels of oleic acid, a monounsaturated fatty acid (MUFA) with just one double bond and low levels of linoleic and linolenic acids, which are polyunsaturated fatty acids (PUFAs) with multiple double bonds. This high MUFA/PUFA ratio confers good oxidative stability making it highly resistant to the production of harmful substances (such as polar compounds). The high levels of double bonds in PUFAs in seed oils make them sensitive to damage by heat [28, 29, 30].
The presence of natural antioxidants in EVOO, such as biophenols and Vitamin E, enhance the oil’s stability and resistance to oxidative degradation. Besides adding health benefits to the oil, these minor constituents boost EVOO’s stability reducing oxidative processes when the oil is heated [31, 32].
The phytosterols are a significant fraction of the unsaponifiable matter in EVOO. These substances add to the oil’s health profile. Some sterols have been shown to provide higher protection against lipid thermal deterioration by decreasing the production of TAG polymers [33]. These sterols are sometimes lost during oil refining and because EVOO does not require this manufacturing step, it retains high concentrations of phytosterols. It has been documented that phytosterols can be transferred to food while cooking, which could have a nutritionally positive impact on consumers [34].
In a comprehensive trial in Australia [5] conducted by an ISO 17025 accredited laboratory in 2018, ten of the most used cooking oils were selected from the supermarket to test their performance when heated. The oils tested were EVOO, virgin olive oil (VOO), olive, canola, rice bran, grapeseed, coconut, peanut, sunflower, and avocado oils.
Two different volumes of oils were heated in open pans (250 mL) for 20 minutes from 25–240°C and in deep fryers (3000 mL) at 180°C for 6 hours. Samples were collected at different intervals and then tested.
Authors specifically assessed the correlation between smoke point and other key chemical parameters related to an oils stability and likelihood to break down and form harmful compounds.
From this study, it was concluded that under different heating conditions, the generation of polar compounds with temperature and time was more pronounced for refined seed oils with higher initial values of smoke point, PUFAs, K232 and K270 (oxidative by-products). Reasonable predictors of how an oil will perform when heated have been oxidative stability, secondary products of oxidation, total level of PUFAs. EVOO was the most stable oil of those tested when heated, followed closely by coconut oil and other virgin oils such as avocado and high oleic acid seed oils. EVOO yielded lower levels of polar compounds and TFAs when compared with other oils.
This research also showed that an oil’s smoke point is not a relevant parameter to explain the oil’s behaviour when heated. Smoke point does not correlate with the stability of the oil during heating, as it showed a positive correlation with the increase in polar compounds (Table 2). That is to say that the higher the smoke point, the more polar compounds that are produced. PUFAs, K232 and K270 showed a positive correlation with polar compounds. Oxidative stability was negatively correlated with final content of polar compounds, demonstrating that a non-stable oil in terms of thermal degradation, will produce more polar compounds when heated (Table 2).
Myth | Assumptions based on the myth | Truth/reality based on scientific evidence |
---|---|---|
Smoke point is a relevant factor in determining how suitable an oil is to cook with. | EVOO is not suitable for cooking at high temperatures given its lower smoke point. | The utilisation of smoke point as an indicator of the ability of an oil to withstand heat, and to determine suitability for cooking is technically incorrect, and is not supported by scientific evidence. Recent evidence [5] shows that EVOO is the most stable oil when heated when compared to other edible oils with higher smoke points. Mediterranean cultures have used EVOO as their only source of cooking oil for centuries and their diet has the highest amount of scientifically proven health benefits [2, 6, 7]. |
Cooking with EVOO can ruin cookware, such as non-stick pans (e.g., Teflon coated pans). | EVOO could be damaging to cookware coating. | Although there is no published scientific evidence to support this, these beliefs are specifically supported by some cookware manufacturers’ specifications that oils with higher smoke points are more suitable for cooking with Teflon coated cookware [8, 9]. On the contrary, EVOO, like any other oil, acts as a lubricant, preventing the food from sticking to the pan [1]. Cooking with EVOO does not ruin non-stick Teflon coated pans at a different rate than other cooking oils. |
Heating olive oil will increase the amount of saturated or trans fats. | You cannot heat olive oil. | All oils will oxidise and hydrogenate to a minor degree when heated several times using high temperatures, such as those used in industrial frying processes [10]. It has been documented that olive oil is less prone to oxidation and hydrogenation when heated than other oils when heated because it is rich in monounsaturated fat [11, 12]. Cooking with EVOO does not produce significant traces of trans fatty acids. In fact, EVOO is less prone to hydrogenation than other vegetable oils. |
When you cook vegetables with EVOO, the vegetables lose antioxidants. | EVOO is not suitable to use when cooking vegetables. | This is incorrect. Recent evidence shows that when cooking with EVOO (including deep frying and sautéing), there is a resultant increase in total phenols (antioxidants) in the cooked food (particularly when cooking raw vegetables) [13]. Cooking with EVOO may in fact improve the nutritional properties of the food. |
Myths related to cooking with EVOO.
Initial Parameter | Correlation with final polar compounds levels (%) |
---|---|
Smoke Point | 83 |
Oxidative Stability | −65 |
FFA | −34 |
PUFAs | 74 |
UV Coefficient K232 | 80 |
UV Coefficient K270 | 54 |
Correlation between final polar compounds and initial oil’s chemical parameters.
These results are also supported by recent research carried out in New Zealand in 2019 [25]. The authors concluded that quality EVOO, in accordance with relevant olive oil standards, is the best cooking oil for use in the home from a stability and health viewpoint. These authors also recommended criteria to indicate an EVOO is stable for cooking:
Initial % free fatty acids (FFA) <0.2% (w/w as oleic acid)
Peroxide Value (PV) < 5.0 mEq/kg
Induction time in Rancimat >15 hours.
Total polar compounds after 8 hours heating at 180°C < 25%
p-Anisidine value after 8 hours at 180°C < 70
TFAs are formed during partial hydrogenation of oils. The interconversion from cis to trans requires a lot of energy (~65 kcal/mole), however the use of a high temperature or a catalyst can enhance the reaction [35]. Consumption of diets high in hydrogenated fat and/or TFAs has been shown to have an adverse effect on lipoprotein profiles with respect to cardiovascular disease risk [36, 37].
The formation of TFAs while cooking food using oil is closely related to the temperature and how many times oil is reused [38, 39]. Several European countries have determined that the frying oil temperature must not exceed 180°C. These measures not only contribute to decreased degradation of unsaturated fatty acids but also result in a lower formation of monounsaturated trans fatty acid (MTFAs) and polyunsaturated trans fatty acids (PTFAs) during frying.
Much research has been done to determine how typical cooking procedures used in food preparation affect TFAs formation in edible oils. Research suggests even applying normal and/or extreme temperatures when cooking does not significantly affect the amounts of TFAs in edible oils [40, 41]. Formation of minor amounts of trans-oleic acid, inferior to 0.2 g/100 g fatty acids was observed by [11, 12] for all the olive oil grades, which is lower than the trans amounts in other refined vegetable oils.
Recent research presented at the World Congress of Oils and Fats in 2020 [42] demonstrated that initially EVOO does not contain TFA and that the food TFA content decreased by approx. 70% or remained stable when using EVOO. The same behaviour was observed with oils: the lowest TFAs production was in EVOO in comparison with other vegetable oils.
Cooking with edible oils, such as deep frying, usually involves two phenomena. Firstly, when the oil, that acts as a heating medium to the food, reaches 100°C water starts to evaporate from the food. This in turn gives way to the oil being absorbed into the food which modifies the fatty acid composition of the food as it cooks. It has been proven that the fat content of the food after deep frying is more like the fat profile of the oil used to cook than the raw food itself [14]. In addition, although the antioxidant content is reduced somewhat during cooking many healthy substances still remain in EVOO and are absorbed by the food. The absorption of these antioxidants into the food gives the food a better nutritional profile. For this reason, the use of EVOO is a healthier option than using other oils with less bioactive components [13, 42, 43].
Frying is one of the oldest methods of food preparation. It improves the sensory quality of food by formation of aromatic compounds, attractive colour, crust and texture, which are all highly appreciated by consumers [44, 45]. The most common frying methods are deep-frying, being the food totally immersed in hot oil, and pan-frying, when the food is cooked in a pan with a little amount of oil [46, 47].
There is a higher degradation under pan-frying conditions for olive oil and other vegetable oils, that can be explained by the higher contact surface between the food and the oil, higher exposure to atmospheric oxygen, and lower temperature control under processing [46].
Frying with EVOO using a lower food:oil ratio presents lower total polar compound amounts than more unsaturated vegetable oils, and with apparently no interference by the presence of food [32, 48, 49]. Within olive oils, the higher the degree of polyunsaturation the higher the tendency for the formation of total polar compounds [50].
The volatile fraction formed during the heating process, apart from being important from the sensorial point of view, is rich in degradation compounds. The formation of low molecular weight volatile aldehydes has a clear dependence on the temperatures used, rather than frying time [51]. The high oleic acid content in olive oil, together with the presence of chlorophylls, pheophytins and carotenoids, seems to contribute to a reduced acrolein formation and lower amounts of toxic monoaromatic hydrocarbons, alkylbenzenes and alkenylbenzenes, in comparison with other vegetable oils with higher polyunsaturated acyl groups [51, 52, 53].
Furthermore, as mentioned previously, in comparison with other vegetable oils, the fried food is enriched with olive oil antioxidants, which improves the nutritional profile of the food [54].
Roasting with olive oil is common in both domestic and industrial food preparation in Mediterranean countries [55]. This procedure is highly prone to oxidation due to the higher surface area exposed to convention hot air and processing times. When comparing with other vegetable oils with a higher degree of unsaturation, olive oil is also more resistant to oxidation under these heating conditions [11, 56]. In opposition, the total polar compounds clearly increase with vegetable oils with higher unsaturation degrees such as sunflower and corn oil [57].
In general, heating olive oil using a microwave demonstrates an apparent higher oxidation when compared with conventional heating, despite being probably lower than those achieved with other vegetable oils [58]. Researchers have compared microwave and conventional heating (in an electric oven) in several vegetable oils including sunflower, high oleic sunflower and olive oil. Among the studied oils, the EVOO exhibited better performance against oxidation with both heating methods. This is mainly due to its composition, including minor compounds with antioxidant properties (phenolic compounds and tocopherols) and a lower percentage of linoleic acid [59]. Still, all studies were performed without the presence of food, meaning further studies using real processing conditions are required for correct inferences [15].
In 2019, Modern Olives Laboratory, an Australian oil specialist laboratory, conducted research to assess the suitability of various cooking oils, including EVOO, for use on Teflon coated (TC) pans.
To investigate the hypothesis of whether cooking with EVOO ruins pans, the researchers measured the release of elements and metals from the pans when separately heated with different oils. They used three different brands of TC pans. These pans were heated with an acidic solution of water vinegar (WV) both prior to and after 6 cycles of heating with different oils (EVOO, olive oil, canola oil, rice bran oil and grapeseed oil). The WV solutions were tested to study the release of various metals.
Combining all TC pans, the authors found no significant differences in the chemical elements content between the final WV solutions from TC pans treated with the different oils. This indicates there is no significant difference between the volume of metals released from the cookware when various cooking oils were used. Hence, the various cooking oils had no effect on the pans’ integrity and quality when cooking. However, differences of statistical significance for Ca, Cu, Fe, P, Zn and SiO2 were observed between the different TC pan types. Higher values of these metals were detected in the most expensive pan compared with the cheapest TC pan. For example, Ca average values (including initial and final treatment) in the most expensive pan were ~ 2.92 mg/L vs. ~1.75 mg/L in the cheapest pan and ~ 2.42 mg/L in the average price pan. When considering each brand of TC pan, phosphorus levels were significantly higher between treatments when using rice bran oil in the average priced TC pan (4.7 mg/L vs. 2.5 mg/L) versus a low- or high-priced TC pan. Silicon dioxide was not detected before treatment and significantly increased using olive (1.1 mg/L) and grapeseed (1.03 mg/L) oils only in the lowest priced TC pan.
After all treatments, no visual deterioration of any of the TC pans was observed. This investigation indicates that higher differences in metal leaching were between pans quality, rather than between the treatments with the different oils. In no case the use of EVOO lead to the release of significantly higher levels of metallic substances from the pan than when using any other oil.
Even though these results are limited considering the lifetime of the TC pan, they indicate no initial impact of the oils’ smoke point on the performance of the TC pan and that EVOO performs similarly to other oils under normal cooking conditions when it comes to TC pan degradation.
Sufficient research has been done to demonstrate that an oil’s smoke point is not a reliable measurement as an indicator of the ability of an oil to withstand heat, and to determine suitability for cooking. Reasonable predictors of how an oil will perform when heated are oxidative stability, secondary products of oxidation, and total level of PUFAs. EVOO has been demonstrated to be the most stable oil when heated given its unique chemical composition, which is rich in monounsaturated fatty acid and antioxidant content.
Experts have agreed that one of the most versatile and healthy oils to cook with is EVOO and many studies have linked it to better heart and overall health.
Food cooked with EVOO also had lower levels of undesirable products of degradation such as TFAs and polar compounds when compared with other vegetable oils such as canola, grapeseed, peanut, sunflower and rice bran oils, while deep-frying under normal cooking conditions.
Furthermore, based on scientific evidence EVOO does not deteriorate the coating when using Teflon cookware. On the contrary it acts as a lubricant to prevent food from sticking to the pans.
Selecting a true high quality EVOO, that is certified to meet EVOO grade and quality requirements is important to ensure high oxidative stability and safety while cooking.
We thank the Olive Wellness Institute (OWI) and Modern Olives Laboratory for their help during this work. To know more about OWI please visit https://olivewellnessinstitute.org/.
The authors declare no conflict of interest.
This is a brief overview of the main steps involved in publishing with IntechOpen Compacts, Monographs and Edited Books. Once you submit your proposal you will be appointed a Author Service Manager who will be your single point of contact and lead you through all the described steps below.
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Samim Al Azad and Slimane Ed-dafali",hash:"86a6d33cf601587e591064ce92effc02",volumeInSeries:1,fullTitle:"Leadership in a Changing World - A Multidimensional Perspective",editors:[{id:"418514",title:"Dr.",name:"Muhammad",middleName:null,surname:"Mohiuddin",slug:"muhammad-mohiuddin",fullName:"Muhammad Mohiuddin",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y000038UqSfQAK/Profile_Picture_2022-05-13T10:39:03.jpg",institutionString:null,institution:{name:"Université Laval",institutionURL:null,country:{name:"Canada"}}}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null}]},subseriesFiltersForPublishedBooks:[{group:"subseries",caption:"Business and Management",value:86,count:1}],publicationYearFilters:[{group:"publicationYear",caption:"2022",value:2022,count:1}],authors:{paginationCount:148,paginationItems:[{id:"165328",title:"Dr.",name:"Vahid",middleName:null,surname:"Asadpour",slug:"vahid-asadpour",fullName:"Vahid Asadpour",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/165328/images/system/165328.jpg",biography:"Vahid Asadpour, MS, Ph.D., is currently with the Department of Research and Evaluation, Kaiser Permanente Southern California. He has both an MS and Ph.D. in Biomedical Engineering. He was previously a research scientist at the University of California Los Angeles (UCLA) and visiting professor and researcher at the University of North Dakota. He is currently working in artificial intelligence and its applications in medical signal processing. In addition, he is using digital signal processing in medical imaging and speech processing. Dr. Asadpour has developed brain-computer interfacing algorithms and has published books, book chapters, and several journal and conference papers in this field and other areas of intelligent signal processing. He has also designed medical devices, including a laser Doppler monitoring system.",institutionString:"Kaiser Permanente Southern California",institution:null},{id:"169608",title:"Prof.",name:"Marian",middleName:null,surname:"Găiceanu",slug:"marian-gaiceanu",fullName:"Marian Găiceanu",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/169608/images/system/169608.png",biography:"Prof. Dr. Marian Gaiceanu graduated from the Naval and Electrical Engineering Faculty, Dunarea de Jos University of Galati, Romania, in 1997. He received a Ph.D. (Magna Cum Laude) in Electrical Engineering in 2002. Since 2017, Dr. Gaiceanu has been a Ph.D. supervisor for students in Electrical Engineering. He has been employed at Dunarea de Jos University of Galati since 1996, where he is currently a professor. Dr. Gaiceanu is a member of the National Council for Attesting Titles, Diplomas and Certificates, an expert of the Executive Agency for Higher Education, Research Funding, and a member of the Senate of the Dunarea de Jos University of Galati. He has been the head of the Integrated Energy Conversion Systems and Advanced Control of Complex Processes Research Center, Romania, since 2016. He has conducted several projects in power converter systems for electrical drives, power quality, PEM and SOFC fuel cell power converters for utilities, electric vehicles, and marine applications with the Department of Regulation and Control, SIEI S.pA. (2002–2004) and the Polytechnic University of Turin, Italy (2002–2004, 2006–2007). He is a member of the Institute of Electrical and Electronics Engineers (IEEE) and cofounder-member of the IEEE Power Electronics Romanian Chapter. He is a guest editor at Energies and an academic book editor for IntechOpen. He is also a member of the editorial boards of the Journal of Electrical Engineering, Electronics, Control and Computer Science and Sustainability. Dr. Gaiceanu has been General Chairman of the IEEE International Symposium on Electrical and Electronics Engineering in the last six editions.",institutionString:'"Dunarea de Jos" University of Galati',institution:{name:'"Dunarea de Jos" University of Galati',country:{name:"Romania"}}},{id:"4519",title:"Prof.",name:"Jaydip",middleName:null,surname:"Sen",slug:"jaydip-sen",fullName:"Jaydip Sen",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/4519/images/system/4519.jpeg",biography:"Jaydip Sen is associated with Praxis Business School, Kolkata, India, as a professor in the Department of Data Science. His research areas include security and privacy issues in computing and communication, intrusion detection systems, machine learning, deep learning, and artificial intelligence in the financial domain. He has more than 200 publications in reputed international journals, refereed conference proceedings, and 20 book chapters in books published by internationally renowned publishing houses, such as Springer, CRC press, IGI Global, etc. Currently, he is serving on the editorial board of the prestigious journal Frontiers in Communications and Networks and in the technical program committees of a number of high-ranked international conferences organized by the IEEE, USA, and the ACM, USA. He has been listed among the top 2% of scientists in the world for the last three consecutive years, 2019 to 2021 as per studies conducted by the Stanford University, USA.",institutionString:"Praxis Business School",institution:null},{id:"320071",title:"Dr.",name:"Sidra",middleName:null,surname:"Mehtab",slug:"sidra-mehtab",fullName:"Sidra Mehtab",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y00002v6KHoQAM/Profile_Picture_1584512086360",biography:"Sidra Mehtab has completed her BS with honors in Physics from Calcutta University, India in 2018. She has done MS in Data Science and Analytics from Maulana Abul Kalam Azad University of Technology (MAKAUT), Kolkata, India in 2020. Her research areas include Econometrics, Time Series Analysis, Machine Learning, Deep Learning, Artificial Intelligence, and Computer and Network Security with a particular focus on Cyber Security Analytics. Ms. Mehtab has published seven papers in international conferences and one of her papers has been accepted for publication in a reputable international journal. She has won the best paper awards in two prestigious international conferences – BAICONF 2019, and ICADCML 2021, organized in the Indian Institute of Management, Bangalore, India in December 2019, and SOA University, Bhubaneswar, India in January 2021. Besides, Ms. Mehtab has also published two book chapters in two books. Seven of her book chapters will be published in a volume shortly in 2021 by Cambridge Scholars’ Press, UK. Currently, she is working as the joint editor of two edited volumes on Time Series Analysis and Forecasting to be published in the first half of 2021 by an international house. Currently, she is working as a Data Scientist with an MNC in Delhi, India.",institutionString:"NSHM College of Management and Technology",institution:null},{id:"226240",title:"Dr.",name:"Andri Irfan",middleName:null,surname:"Rifai",slug:"andri-irfan-rifai",fullName:"Andri Irfan Rifai",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/226240/images/7412_n.jpg",biography:"Andri IRFAN is a Senior Lecturer of Civil Engineering and Planning. He completed the PhD at the Universitas Indonesia & Universidade do Minho with Sandwich Program Scholarship from the Directorate General of Higher Education and LPDP scholarship. He has been teaching for more than 19 years and much active to applied his knowledge in the project construction in Indonesia. His research interest ranges from pavement management system to advanced data mining techniques for transportation engineering. He has published more than 50 papers in journals and 2 books.",institutionString:null,institution:{name:"Universitas Internasional Batam",country:{name:"Indonesia"}}},{id:"314576",title:"Dr.",name:"Ibai",middleName:null,surname:"Laña",slug:"ibai-lana",fullName:"Ibai Laña",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/314576/images/system/314576.jpg",biography:"Dr. Ibai Laña works at TECNALIA as a data analyst. He received his Ph.D. in Artificial Intelligence from the University of the Basque Country (UPV/EHU), Spain, in 2018. He is currently a senior researcher at TECNALIA. His research interests fall within the intersection of intelligent transportation systems, machine learning, traffic data analysis, and data science. He has dealt with urban traffic forecasting problems, applying machine learning models and evolutionary algorithms. He has experience in origin-destination matrix estimation or point of interest and trajectory detection. Working with large volumes of data has given him a good command of big data processing tools and NoSQL databases. He has also been a visiting scholar at the Knowledge Engineering and Discovery Research Institute, Auckland University of Technology.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"314575",title:"Dr.",name:"Jesus",middleName:null,surname:"L. Lobo",slug:"jesus-l.-lobo",fullName:"Jesus L. Lobo",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/314575/images/system/314575.png",biography:"Dr. Jesús López is currently based in Bilbao (Spain) working at TECNALIA as Artificial Intelligence Research Scientist. In most cases, a project idea or a new research line needs to be investigated to see if it is good enough to take into production or to focus on it. That is exactly what he does, diving into Machine Learning algorithms and technologies to help TECNALIA to decide whether something is great in theory or will actually impact on the product or processes of its projects. So, he is expert at framing experiments, developing hypotheses, and proving whether they’re true or not, in order to investigate fundamental problems with a longer time horizon. He is also able to design and develop PoCs and system prototypes in simulation. He has participated in several national and internacional R&D projects.\n\nAs another relevant part of his everyday research work, he usually publishes his findings in reputed scientific refereed journals and international conferences, occasionally acting as reviewer and Programme Commitee member. Concretely, since 2018 he has published 9 JCR (8 Q1) journal papers, 9 conference papers (e.g. ECML PKDD 2021), and he has co-edited a book. He is also active in popular science writing data science stories for reputed blogs (KDNuggets, TowardsDataScience, Naukas). Besides, he has recently embarked on mentoring programmes as mentor, and has also worked as data science trainer.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"103779",title:"Prof.",name:"Yalcin",middleName:null,surname:"Isler",slug:"yalcin-isler",fullName:"Yalcin Isler",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRyQ8QAK/Profile_Picture_1628834958734",biography:"Yalcin Isler (1971 - Burdur / Turkey) received the B.Sc. degree in the Department of Electrical and Electronics Engineering from Anadolu University, Eskisehir, Turkey, in 1993, the M.Sc. degree from the Department of Electronics and Communication Engineering, Suleyman Demirel University, Isparta, Turkey, in 1996, the Ph.D. degree from the Department of Electrical and Electronics Engineering, Dokuz Eylul University, Izmir, Turkey, in 2009, and the Competence of Associate Professorship from the Turkish Interuniversity Council in 2019.\n\nHe was Lecturer at Burdur Vocational School in Suleyman Demirel University (1993-2000, Burdur / Turkey), Software Engineer (2000-2002, Izmir / Turkey), Research Assistant in Bulent Ecevit University (2002-2003, Zonguldak / Turkey), Research Assistant in Dokuz Eylul University (2003-2010, Izmir / Turkey), Assistant Professor at the Department of Electrical and Electronics Engineering in Bulent Ecevit University (2010-2012, Zonguldak / Turkey), Assistant Professor at the Department of Biomedical Engineering in Izmir Katip Celebi University (2012-2019, Izmir / Turkey). He is an Associate Professor at the Department of Biomedical Engineering at Izmir Katip Celebi University, Izmir / Turkey, since 2019. In addition to academics, he has also founded Islerya Medical and Information Technologies Company, Izmir / Turkey, since 2017.\n\nHis main research interests cover biomedical signal processing, pattern recognition, medical device design, programming, and embedded systems. He has many scientific papers and participated in several projects in these study fields. He was an IEEE Student Member (2009-2011) and IEEE Member (2011-2014) and has been IEEE Senior Member since 2014.",institutionString:null,institution:{name:"Izmir Kâtip Çelebi University",country:{name:"Turkey"}}},{id:"339677",title:"Dr.",name:"Mrinmoy",middleName:null,surname:"Roy",slug:"mrinmoy-roy",fullName:"Mrinmoy Roy",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/339677/images/16768_n.jpg",biography:"An accomplished Sales & Marketing professional with 12 years of cross-functional experience in well-known organisations such as CIPLA, LUPIN, GLENMARK, ASTRAZENECA across different segment of Sales & Marketing, International Business, Institutional Business, Product Management, Strategic Marketing of HIV, Oncology, Derma, Respiratory, Anti-Diabetic, Nutraceutical & Stomatological Product Portfolio and Generic as well as Chronic Critical Care Portfolio. A First Class MBA in International Business & Strategic Marketing, B.Pharm, D.Pharm, Google Certified Digital Marketing Professional. Qualified PhD Candidate in Operations and Management with special focus on Artificial Intelligence and Machine Learning adoption, analysis and use in Healthcare, Hospital & Pharma Domain. Seasoned with diverse therapy area of Pharmaceutical Sales & Marketing ranging from generating revenue through generating prescriptions, launching new products, and making them big brands with continuous strategy execution at the Physician and Patients level. Moved from Sales to Marketing and Business Development for 3.5 years in South East Asian Market operating from Manila, Philippines. Came back to India and handled and developed Brands such as Gluconorm, Lupisulin, Supracal, Absolut Woman, Hemozink, Fabiflu (For COVID 19), and many more. In my previous assignment I used to develop and execute strategies on Sales & Marketing, Commercialization & Business Development for Institution and Corporate Hospital Business portfolio of Oncology Therapy Area for AstraZeneca Pharma India Ltd. Being a Research Scholar and Student of ‘Operations Research & Management: Artificial Intelligence’ I published several pioneer research papers and book chapters on the same in Internationally reputed journals and Books indexed in Scopus, Springer and Ei Compendex, Google Scholar etc. Currently, I am launching PGDM Pharmaceutical Management Program in IIHMR Bangalore and spearheading the course curriculum and structure of the same. I am interested in Collaboration for Healthcare Innovation, Pharma AI Innovation, Future trend in Marketing and Management with incubation on Healthcare, Healthcare IT startups, AI-ML Modelling and Healthcare Algorithm based training module development. I am also an affiliated member of the Institute of Management Consultant of India, looking forward to Healthcare, Healthcare IT and Innovation, Pharma and Hospital Management Consulting works.",institutionString:null,institution:{name:"Lovely Professional University",country:{name:"India"}}},{id:"1063",title:"Prof.",name:"Constantin",middleName:null,surname:"Volosencu",slug:"constantin-volosencu",fullName:"Constantin Volosencu",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/1063/images/system/1063.png",biography:"Prof. Dr. Constantin Voloşencu graduated as an engineer from\nPolitehnica University of Timișoara, Romania, where he also\nobtained a doctorate degree. He is currently a full professor in\nthe Department of Automation and Applied Informatics at the\nsame university. Dr. Voloşencu is the author of ten books, seven\nbook chapters, and more than 160 papers published in journals\nand conference proceedings. He has also edited twelve books and\nhas twenty-seven patents to his name. He is a manager of research grants, editor in\nchief and member of international journal editorial boards, a former plenary speaker, a member of scientific committees, and chair at international conferences. His\nresearch is in the fields of control systems, control of electric drives, fuzzy control\nsystems, neural network applications, fault detection and diagnosis, sensor network\napplications, monitoring of distributed parameter systems, and power ultrasound\napplications. He has developed automation equipment for machine tools, spooling\nmachines, high-power ultrasound processes, and more.",institutionString:"Polytechnic University of Timişoara",institution:{name:"Polytechnic University of Timişoara",country:{name:"Romania"}}},{id:"221364",title:"Dr.",name:"Eneko",middleName:null,surname:"Osaba",slug:"eneko-osaba",fullName:"Eneko Osaba",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/221364/images/system/221364.jpg",biography:"Dr. Eneko Osaba works at TECNALIA as a senior researcher. He obtained his Ph.D. in Artificial Intelligence in 2015. He has participated in more than twenty-five local and European research projects, and in the publication of more than 130 papers. He has performed several stays at universities in the United Kingdom, Italy, and Malta. Dr. Osaba has served as a program committee member in more than forty international conferences and participated in organizing activities in more than ten international conferences. He is a member of the editorial board of the International Journal of Artificial Intelligence, Data in Brief, and Journal of Advanced Transportation. He is also a guest editor for the Journal of Computational Science, Neurocomputing, Swarm, and Evolutionary Computation and IEEE ITS Magazine.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"275829",title:"Dr.",name:"Esther",middleName:null,surname:"Villar-Rodriguez",slug:"esther-villar-rodriguez",fullName:"Esther Villar-Rodriguez",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/275829/images/system/275829.jpg",biography:"Dr. Esther Villar obtained a Ph.D. in Information and Communication Technologies from the University of Alcalá, Spain, in 2015. She obtained a degree in Computer Science from the University of Deusto, Spain, in 2010, and an MSc in Computer Languages and Systems from the National University of Distance Education, Spain, in 2012. Her areas of interest and knowledge include natural language processing (NLP), detection of impersonation in social networks, semantic web, and machine learning. Dr. Esther Villar made several contributions at conferences and publishing in various journals in those fields. Currently, she is working within the OPTIMA (Optimization Modeling & Analytics) business of TECNALIA’s ICT Division as a data scientist in projects related to the prediction and optimization of management and industrial processes (resource planning, energy efficiency, etc).",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"49813",title:"Dr.",name:"Javier",middleName:null,surname:"Del Ser",slug:"javier-del-ser",fullName:"Javier Del Ser",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/49813/images/system/49813.png",biography:"Prof. Dr. Javier Del Ser received his first PhD in Telecommunication Engineering (Cum Laude) from the University of Navarra, Spain, in 2006, and a second PhD in Computational Intelligence (Summa Cum Laude) from the University of Alcala, Spain, in 2013. He is currently a principal researcher in data analytics and optimisation at TECNALIA (Spain), a visiting fellow at the Basque Center for Applied Mathematics (BCAM) and a part-time lecturer at the University of the Basque Country (UPV/EHU). His research interests gravitate on the use of descriptive, prescriptive and predictive algorithms for data mining and optimization in a diverse range of application fields such as Energy, Transport, Telecommunications, Health and Industry, among others. In these fields he has published more than 240 articles, co-supervised 8 Ph.D. theses, edited 6 books, coauthored 7 patents and participated/led more than 40 research projects. He is a Senior Member of the IEEE, and a recipient of the Biscay Talent prize for his academic career.",institutionString:"Tecnalia Research & Innovation",institution:null},{id:"278948",title:"Dr.",name:"Carlos Pedro",middleName:null,surname:"Gonçalves",slug:"carlos-pedro-goncalves",fullName:"Carlos Pedro Gonçalves",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRcmyQAC/Profile_Picture_1564224512145",biography:'Carlos Pedro Gonçalves (PhD) is an Associate Professor at Lusophone University of Humanities and Technologies and a researcher on Complexity Sciences, Quantum Technologies, Artificial Intelligence, Strategic Studies, Studies in Intelligence and Security, FinTech and Financial Risk Modeling. He is also a progammer with programming experience in:\n\nA) Quantum Computing using Qiskit Python module and IBM Quantum Experience Platform, with software developed on the simulation of Quantum Artificial Neural Networks and Quantum Cybersecurity;\n\nB) Artificial Intelligence and Machine learning programming in Python;\n\nC) Artificial Intelligence, Multiagent Systems Modeling and System Dynamics Modeling in Netlogo, with models developed in the areas of Chaos Theory, Econophysics, Artificial Intelligence, Classical and Quantum Complex Systems Science, with the Econophysics models having been cited worldwide and incorporated in PhD programs by different Universities.\n\nReceived an Arctic Code Vault Contributor status by GitHub, due to having developed open source software preserved in the \\"Arctic Code Vault\\" for future generations (https://archiveprogram.github.com/arctic-vault/), with the Strategy Analyzer A.I. module for decision making support (based on his PhD thesis, used in his Classes on Decision Making and in Strategic Intelligence Consulting Activities) and QNeural Python Quantum Neural Network simulator also preserved in the \\"Arctic Code Vault\\", for access to these software modules see: https://github.com/cpgoncalves. He is also a peer reviewer with outsanding review status from Elsevier journals, including Physica A, Neurocomputing and Engineering Applications of Artificial Intelligence. Science CV available at: https://www.cienciavitae.pt//pt/8E1C-A8B3-78C5 and ORCID: https://orcid.org/0000-0002-0298-3974',institutionString:"University of Lisbon",institution:{name:"Universidade Lusófona",country:{name:"Portugal"}}},{id:"241400",title:"Prof.",name:"Mohammed",middleName:null,surname:"Bsiss",slug:"mohammed-bsiss",fullName:"Mohammed Bsiss",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/241400/images/8062_n.jpg",biography:null,institutionString:null,institution:null},{id:"276128",title:"Dr.",name:"Hira",middleName:null,surname:"Fatima",slug:"hira-fatima",fullName:"Hira Fatima",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/276128/images/14420_n.jpg",biography:"Dr. Hira Fatima\nAssistant Professor\nDepartment of Mathematics\nInstitute of Applied Science\nMangalayatan University, Aligarh\nMobile: no : 8532041179\nhirafatima2014@gmal.com\n\nDr. Hira Fatima has received his Ph.D. degree in pure Mathematics from Aligarh Muslim University, Aligarh India. Currently working as an Assistant Professor in the Department of Mathematics, Institute of Applied Science, Mangalayatan University, Aligarh. She taught so many courses of Mathematics of UG and PG level. Her research Area of Expertise is Functional Analysis & Sequence Spaces. She has been working on Ideal Convergence of double sequence. She has published 17 research papers in National and International Journals including Cogent Mathematics, Filomat, Journal of Intelligent and Fuzzy Systems, Advances in Difference Equations, Journal of Mathematical Analysis, Journal of Mathematical & Computer Science etc. She has also reviewed few research papers for the and international journals. She is a member of Indian Mathematical Society.",institutionString:null,institution:null},{id:"414880",title:"Dr.",name:"Maryam",middleName:null,surname:"Vatankhah",slug:"maryam-vatankhah",fullName:"Maryam Vatankhah",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Borough of Manhattan Community College",country:{name:"United States of America"}}},{id:"414879",title:"Prof.",name:"Mohammad-Reza",middleName:null,surname:"Akbarzadeh-Totonchi",slug:"mohammad-reza-akbarzadeh-totonchi",fullName:"Mohammad-Reza Akbarzadeh-Totonchi",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Ferdowsi University of Mashhad",country:{name:"Iran"}}},{id:"414878",title:"Prof.",name:"Reza",middleName:null,surname:"Fazel-Rezai",slug:"reza-fazel-rezai",fullName:"Reza Fazel-Rezai",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"American Public University System",country:{name:"United States of America"}}},{id:"302698",title:"Dr.",name:"Yao",middleName:null,surname:"Shan",slug:"yao-shan",fullName:"Yao Shan",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Dalian University of Technology",country:{name:"China"}}},{id:"125911",title:"Prof.",name:"Jia-Ching",middleName:null,surname:"Wang",slug:"jia-ching-wang",fullName:"Jia-Ching Wang",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"National Central University",country:{name:"Taiwan"}}},{id:"357085",title:"Mr.",name:"P. Mohan",middleName:null,surname:"Anand",slug:"p.-mohan-anand",fullName:"P. Mohan Anand",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Indian Institute of Technology Kanpur",country:{name:"India"}}},{id:"356696",title:"Ph.D. Student",name:"P.V.",middleName:null,surname:"Sai Charan",slug:"p.v.-sai-charan",fullName:"P.V. Sai Charan",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Indian Institute of Technology Kanpur",country:{name:"India"}}},{id:"357086",title:"Prof.",name:"Sandeep K.",middleName:null,surname:"Shukla",slug:"sandeep-k.-shukla",fullName:"Sandeep K. 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He obtained his Master’s degree in the Department of Information and Communications from Gwangju Institute of Science and Technology (GIST) in 2003. In 2010, he received his Ph.D. degree in the School of Information and Mechatronics from GIST. In the meantime, he was an executed team leader at Culture Technology Institute, GIST, 2010-2012. In 2011, he worked at Lancaster University, the UK as a visiting scholar. In September 2012, he joined Daegu University, where he is currently an associate professor in the School of ICT Conver, Daegu University. Also, he served as the Board of Directors of KSIIS since 2019, and HCI Korea since 2016. From 2017~2019, he worked as a center director of the Mixed Reality Convergence Research Center at Daegu University. From 2015-2017, He worked as a director in the Enterprise Supporting Office of LINC Project Group, Daegu University. 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