Balwinder Raj, PhD, is an associate professor in the Electronics and Communication Engineering Department, at the National Institute of Technical Teachers Training and Research, Chandigarh. He has published more than 100 research papers in national and international journals and conferences. Additionally, the European Commission awarded him a Mobility of Life research fellowship for postdoc research work at the University of Rome, Tor Vergata, Italy in 2010-2011. His areas of interest include nanoscale semiconductor device modeling, sensors design, FinFET-based memory design, and low-power VLSI design. Suman Lata Tripathi, PhD, is a professor at the Lovely Professional University with more than 20 years of experience in academics. She is also a remote post-doctoral researcher at Nottingham Trent University, London, UK. She has published more than 74 research papers in refereed science journals and conferences, as well as 13 Indian patents and two copyrights. Additionally, she has edited and authored more than 17 books in different areas of electronics and electrical engineering. Tarun Chaudhary, PhD, is an assistant professor in the Electronics and Communication Engineering Department at the Dr. B.R. Ambedkar National Institute of Technology, Jalandhar, India. During her PhD, she worked on the design and mathematical modeling of the vertical field effect transistor. She has five book chapters and more than 25 research papers in peer-reviewed national and international journals and conferences. K. Srinivasa Rao, PhD, is a professor and the head of the Microelectronics Research Group in the Department of Electronics and Communication Engineering at the Koneru Lakshmaiah Education Foundation, Andhra Pradesh, India. His areas of research include MEMS-based reconfigurable antennas, MEMS actuators, piezoresistive, and VLSI circuts. He is a reviewer for many SCI-indexed journals and an external reviewer for many universities. Mandeep Singh is a professor at the Indian Institute of Information Technology, Surat Gujarat. He has five years of teaching experience with undergraduate and master students. He has published various research papers in the domain of VLSI design and circuits.

• Preface xiii1 Comparative Analysis of MOSFET and FinFET 1Mandeep Singh, Tarun Chaudhary, Balwinder Raj, Girish Wadhwa and Suman Lata Tripathi1.1 Introduction 21.2 Double Gate 41.3 Advantages and Disadvantage of MOSFET 101.4 MOSFET Drawbacks 101.5 FinFET 101.6 SOI-FinFET 111.7 Issues with FinFET-Based Technology 121.8 Advantage of FinFET 131.9 Drawbacks of FinFET 131.10 Applications of FinFET Technology 141.11 Conclusion 162 Nanosheet FET for Future Technology Scaling 25Aruru Sai Kumar, V. Bharath Sreenivasulu, M. Deekshana, G. Shanthi and K. Srinivasa Rao2.1 Introduction 262.2 Device Description and Simulation Parameters 282.3 Conclusions 393 Comparison of Different TFETs: An Overview 49Rama Satya, Nageswara Rao and K. Srinivasa Rao3.1 Introduction 493.2 Tunnel FET 503.3 Gate Engineering 533.4 Tunneling-Junction Engineering 593.5 Materials Engineering 613.6 Conclusion 664 GaAs Nanowire Field Effect Transistor 75Shailendra Yadav, Mandeep Singh, Tarun Chaudhary, Balwinder Raj, Alok Kumar Shukla and Brajesh Kumar Kaushik4.1 Introduction 754.2 Properties of Nanowires 814.3 Nanowire-FET 834.4 Proposed Work (GaAs Nanowire-FET) 844.5 Conclusion 915 Graphene Nanoribbon for Future VLSI Applications: A Review 101Himanshu Sharma5.1 Introduction 1025.2 Future Applications of Graphene and Graphene-Based FETs 1146 Ferroelectric Random Access Memory (FeRAM) 125B. Vimala Reddy, Tarun Chaudhary, Mandeep Singh and Balwinder Raj6.1 Introduction 1256.2 Structure of Ferroelectric Memory Cells in Capacitor-Type FRAM Devices 1316.3 Write/Read Operations in the FRAM Using a Capacitor-Type Memory Cell that Resembles a DRAM 1326.4 Other Capacitor-Type FRAM 1356.5 FRAM of FET Type 1356.6 Memory Utilizing a Ferroelectric Tunnel Junction 1376.7 Cross Point Matrix Array 1376.8 Ferroelectric Shadow RAMs 1386.9 2T2C Ferroelectric RAM Architecture 1406.10 FeRAM vs. EEPROM 1456.11 FeRAM vs. Static RAM 1456.12 FeRAM vs. Dynamic RAM 1466.13 FeRAM vs. Flash Memory 1466.14 Conclusion and Upcoming Trends 1477 Applications of AI/ML Algorithms in VLSI Design and Technology 157Jaswinder Singh and Damanpreet Singh7.1 Introduction 1577.2 Artificial Intelligence and Machine Learning 1597.3 AI/ML Algorithms 1607.4 Supervised Machine Learning (SML) 1627.5 Classification Techniques 1637.6 K-Nearest Neighbors (KNN) 1647.7 Support Vector Machine (SVM) 1667.8 Linearly Separable Classification 1677.9 Decision Tree Classifier (DTC) 1687.10 Performance Measures in Classification 1707.11 Unsupervised Machine Learning (UML) 1737.12 Hierarchical Clustering 1747.13 Partitional Clustering 1767.14 K-Means 1767.15 Fuzzy (soft) Clustering 1777.16 Cluster Validation Measures 1787.17 Internal Clustering Validation Measures 1797.18 External Clustering Validation Criteria 1807.19 Limitation and Challenges — VLSI 1818 Advancement of Neuromorphic Computing Systems with Memristors 193Jeetendra Singh, Shailendra Singh, Balwant Raj, Vikas Patel and Balwinder Raj8.1 Introduction 1948.2 Summary 2069 Neuromorphic Computing and Its Application 217Tejasvini Thakral, Lucky Lamba, Manjeet Singh, Tarun Chaudhary and Mandeep Singh9.1 Introduction 2189.2 Evolution of Neuroinspired Computing Chips 2189.3 Science Behind Brain Physics 2209.4 Limitations of Semiconductor Devices 2219.5 Various Combination of Networks 2259.6 Artificial Intelligence 2289.7 A Summary of Neuromorphic Hardware Methodologies 2299.8 Neuromorphic Computing in Robotics 2319.9 Challenges in Neuromorphic Computing 2329.10 Applications of Neuromorphic Computing 2349.11 Conclusion 23710 Performance Evaluation of Prototype Microstrip Patch Antenna Fabrication Using Microwave Dielectric Ceramic Nanocomposite Materials for X-Band Applications 247Srilali Siragam10.1 Introduction 24810.2 Materials and Methods 25010.3 Results and Discussion 25110.4 Conclusions 25811 Build and Deploy a Smart Speaker with Biometric Authentication and Advanced Voice Interaction Capabilities 271Gur Sharan Kant and Kavi Bhushan11.1 Introduction 27211.2 Cybersecurity Risk as Smart Speakers Don't Have an Authentication Process 27311.3 Related Work 27511.4 Overview of Biometric Authentication and the Voice Algorithm-Based Smart Speaker 27511.5 Conclusion and Discussion 28312 Boron-Based Nanomaterials for Intelligent Drug Delivery Using Computer-Aided Tools 295Jupinder Kaur, Ravinder Kumar and Rajan Vohra12.1 Introduction 29612.2 Computational Details 29712.3 Results and Discussion 29813 Design and Analysis of Rectangular Wave Guide Using an HFSS Simulator 329Srilali Siragam13.1 Background 32913.2 Introduction 33113.3 Mathematical Computations 33313.4 Numerical Analysis 33613.5 Conclusion 344References 344Index 355

Balwinder Raj, PhD, is an associate professor in the Electronics and Communication Engineering Department, at the National Institute of Technical Teachers Training and Research, Chandigarh. He has published more than 100 research papers in national and international journals and conferences. Additionally, the European Commission awarded him a Mobility of Life research fellowship for postdoc research work at the University of Rome, Tor Vergata, Italy in 2010-2011. His areas of interest include nanoscale semiconductor device modeling, sensors design, FinFET-based memory design, and low-power VLSI design. Suman Lata Tripathi, PhD, is a professor at the Lovely Professional University with more than 20 years of experience in academics. She is also a remote post-doctoral researcher at Nottingham Trent University, London, UK. She has published more than 74 research papers in refereed science journals and conferences, as well as 13 Indian patents and two copyrights. Additionally, she has edited and authored more than 17 books in different areas of electronics and electrical engineering. Tarun Chaudhary, PhD, is an assistant professor in the Electronics and Communication Engineering Department at the Dr. B.R. Ambedkar National Institute of Technology, Jalandhar, India. During her PhD, she worked on the design and mathematical modeling of the vertical field effect transistor. She has five book chapters and more than 25 research papers in peer-reviewed national and international journals and conferences. K. Srinivasa Rao, PhD, is a professor and the head of the Microelectronics Research Group in the Department of Electronics and Communication Engineering at the Koneru Lakshmaiah Education Foundation, Andhra Pradesh, India. His areas of research include MEMS-based reconfigurable antennas, MEMS actuators, piezoresistive, and VLSI circuts. He is a reviewer for many SCI-indexed journals and an external reviewer for many universities. Mandeep Singh is a professor at the Indian Institute of Information Technology, Surat Gujarat. He has five years of teaching experience with undergraduate and master students. He has published various research papers in the domain of VLSI design and circuits.

• Preface xiii1 Comparative Analysis of MOSFET and FinFET 1Mandeep Singh, Tarun Chaudhary, Balwinder Raj, Girish Wadhwa and Suman Lata Tripathi1.1 Introduction 21.2 Double Gate 41.3 Advantages and Disadvantage of MOSFET 101.4 MOSFET Drawbacks 101.5 FinFET 101.6 SOI-FinFET 111.7 Issues with FinFET-Based Technology 121.8 Advantage of FinFET 131.9 Drawbacks of FinFET 131.10 Applications of FinFET Technology 141.11 Conclusion 162 Nanosheet FET for Future Technology Scaling 25Aruru Sai Kumar, V. Bharath Sreenivasulu, M. Deekshana, G. Shanthi and K. Srinivasa Rao2.1 Introduction 262.2 Device Description and Simulation Parameters 282.3 Conclusions 393 Comparison of Different TFETs: An Overview 49Rama Satya, Nageswara Rao and K. Srinivasa Rao3.1 Introduction 493.2 Tunnel FET 503.3 Gate Engineering 533.4 Tunneling-Junction Engineering 593.5 Materials Engineering 613.6 Conclusion 664 GaAs Nanowire Field Effect Transistor 75Shailendra Yadav, Mandeep Singh, Tarun Chaudhary, Balwinder Raj, Alok Kumar Shukla and Brajesh Kumar Kaushik4.1 Introduction 754.2 Properties of Nanowires 814.3 Nanowire-FET 834.4 Proposed Work (GaAs Nanowire-FET) 844.5 Conclusion 915 Graphene Nanoribbon for Future VLSI Applications: A Review 101Himanshu Sharma5.1 Introduction 1025.2 Future Applications of Graphene and Graphene-Based FETs 1146 Ferroelectric Random Access Memory (FeRAM) 125B. Vimala Reddy, Tarun Chaudhary, Mandeep Singh and Balwinder Raj6.1 Introduction 1256.2 Structure of Ferroelectric Memory Cells in Capacitor-Type FRAM Devices 1316.3 Write/Read Operations in the FRAM Using a Capacitor-Type Memory Cell that Resembles a DRAM 1326.4 Other Capacitor-Type FRAM 1356.5 FRAM of FET Type 1356.6 Memory Utilizing a Ferroelectric Tunnel Junction 1376.7 Cross Point Matrix Array 1376.8 Ferroelectric Shadow RAMs 1386.9 2T2C Ferroelectric RAM Architecture 1406.10 FeRAM vs. EEPROM 1456.11 FeRAM vs. Static RAM 1456.12 FeRAM vs. Dynamic RAM 1466.13 FeRAM vs. Flash Memory 1466.14 Conclusion and Upcoming Trends 1477 Applications of AI/ML Algorithms in VLSI Design and Technology 157Jaswinder Singh and Damanpreet Singh7.1 Introduction 1577.2 Artificial Intelligence and Machine Learning 1597.3 AI/ML Algorithms 1607.4 Supervised Machine Learning (SML) 1627.5 Classification Techniques 1637.6 K-Nearest Neighbors (KNN) 1647.7 Support Vector Machine (SVM) 1667.8 Linearly Separable Classification 1677.9 Decision Tree Classifier (DTC) 1687.10 Performance Measures in Classification 1707.11 Unsupervised Machine Learning (UML) 1737.12 Hierarchical Clustering 1747.13 Partitional Clustering 1767.14 K-Means 1767.15 Fuzzy (soft) Clustering 1777.16 Cluster Validation Measures 1787.17 Internal Clustering Validation Measures 1797.18 External Clustering Validation Criteria 1807.19 Limitation and Challenges — VLSI 1818 Advancement of Neuromorphic Computing Systems with Memristors 193Jeetendra Singh, Shailendra Singh, Balwant Raj, Vikas Patel and Balwinder Raj8.1 Introduction 1948.2 Summary 2069 Neuromorphic Computing and Its Application 217Tejasvini Thakral, Lucky Lamba, Manjeet Singh, Tarun Chaudhary and Mandeep Singh9.1 Introduction 2189.2 Evolution of Neuroinspired Computing Chips 2189.3 Science Behind Brain Physics 2209.4 Limitations of Semiconductor Devices 2219.5 Various Combination of Networks 2259.6 Artificial Intelligence 2289.7 A Summary of Neuromorphic Hardware Methodologies 2299.8 Neuromorphic Computing in Robotics 2319.9 Challenges in Neuromorphic Computing 2329.10 Applications of Neuromorphic Computing 2349.11 Conclusion 23710 Performance Evaluation of Prototype Microstrip Patch Antenna Fabrication Using Microwave Dielectric Ceramic Nanocomposite Materials for X-Band Applications 247Srilali Siragam10.1 Introduction 24810.2 Materials and Methods 25010.3 Results and Discussion 25110.4 Conclusions 25811 Build and Deploy a Smart Speaker with Biometric Authentication and Advanced Voice Interaction Capabilities 271Gur Sharan Kant and Kavi Bhushan11.1 Introduction 27211.2 Cybersecurity Risk as Smart Speakers Don't Have an Authentication Process 27311.3 Related Work 27511.4 Overview of Biometric Authentication and the Voice Algorithm-Based Smart Speaker 27511.5 Conclusion and Discussion 28312 Boron-Based Nanomaterials for Intelligent Drug Delivery Using Computer-Aided Tools 295Jupinder Kaur, Ravinder Kumar and Rajan Vohra12.1 Introduction 29612.2 Computational Details 29712.3 Results and Discussion 29813 Design and Analysis of Rectangular Wave Guide Using an HFSS Simulator 329Srilali Siragam13.1 Background 32913.2 Introduction 33113.3 Mathematical Computations 33313.4 Numerical Analysis 33613.5 Conclusion 344References 344Index 355

Balwinder Raj, PhD, is an associate professor in the Electronics and Communication Engineering Department, at the National Institute of Technical Teachers Training and Research, Chandigarh. He has published more than 100 research papers in national and international journals and conferences. Additionally, the European Commission awarded him a Mobility of Life research fellowship for postdoc research work at the University of Rome, Tor Vergata, Italy in 2010-2011. His areas of interest include nanoscale semiconductor device modeling, sensors design, FinFET-based memory design, and low-power VLSI design. Suman Lata Tripathi, PhD, is a professor at the Lovely Professional University with more than 20 years of experience in academics. She is also a remote post-doctoral researcher at Nottingham Trent University, London, UK. She has published more than 74 research papers in refereed science journals and conferences, as well as 13 Indian patents and two copyrights. Additionally, she has edited and authored more than 17 books in different areas of electronics and electrical engineering. Tarun Chaudhary, PhD, is an assistant professor in the Electronics and Communication Engineering Department at the Dr. B.R. Ambedkar National Institute of Technology, Jalandhar, India. During her PhD, she worked on the design and mathematical modeling of the vertical field effect transistor. She has five book chapters and more than 25 research papers in peer-reviewed national and international journals and conferences. K. Srinivasa Rao, PhD, is a professor and the head of the Microelectronics Research Group in the Department of Electronics and Communication Engineering at the Koneru Lakshmaiah Education Foundation, Andhra Pradesh, India. His areas of research include MEMS-based reconfigurable antennas, MEMS actuators, piezoresistive, and VLSI circuts. He is a reviewer for many SCI-indexed journals and an external reviewer for many universities. Mandeep Singh is a professor at the Indian Institute of Information Technology, Surat Gujarat. He has five years of teaching experience with undergraduate and master students. He has published various research papers in the domain of VLSI design and circuits.

• Preface xiii1 Comparative Analysis of MOSFET and FinFET 1Mandeep Singh, Tarun Chaudhary, Balwinder Raj, Girish Wadhwa and Suman Lata Tripathi1.1 Introduction 21.2 Double Gate 41.3 Advantages and Disadvantage of MOSFET 101.4 MOSFET Drawbacks 101.5 FinFET 101.6 SOI-FinFET 111.7 Issues with FinFET-Based Technology 121.8 Advantage of FinFET 131.9 Drawbacks of FinFET 131.10 Applications of FinFET Technology 141.11 Conclusion 162 Nanosheet FET for Future Technology Scaling 25Aruru Sai Kumar, V. Bharath Sreenivasulu, M. Deekshana, G. Shanthi and K. Srinivasa Rao2.1 Introduction 262.2 Device Description and Simulation Parameters 282.3 Conclusions 393 Comparison of Different TFETs: An Overview 49Rama Satya, Nageswara Rao and K. Srinivasa Rao3.1 Introduction 493.2 Tunnel FET 503.3 Gate Engineering 533.4 Tunneling-Junction Engineering 593.5 Materials Engineering 613.6 Conclusion 664 GaAs Nanowire Field Effect Transistor 75Shailendra Yadav, Mandeep Singh, Tarun Chaudhary, Balwinder Raj, Alok Kumar Shukla and Brajesh Kumar Kaushik4.1 Introduction 754.2 Properties of Nanowires 814.3 Nanowire-FET 834.4 Proposed Work (GaAs Nanowire-FET) 844.5 Conclusion 915 Graphene Nanoribbon for Future VLSI Applications: A Review 101Himanshu Sharma5.1 Introduction 1025.2 Future Applications of Graphene and Graphene-Based FETs 1146 Ferroelectric Random Access Memory (FeRAM) 125B. Vimala Reddy, Tarun Chaudhary, Mandeep Singh and Balwinder Raj6.1 Introduction 1256.2 Structure of Ferroelectric Memory Cells in Capacitor-Type FRAM Devices 1316.3 Write/Read Operations in the FRAM Using a Capacitor-Type Memory Cell that Resembles a DRAM 1326.4 Other Capacitor-Type FRAM 1356.5 FRAM of FET Type 1356.6 Memory Utilizing a Ferroelectric Tunnel Junction 1376.7 Cross Point Matrix Array 1376.8 Ferroelectric Shadow RAMs 1386.9 2T2C Ferroelectric RAM Architecture 1406.10 FeRAM vs. EEPROM 1456.11 FeRAM vs. Static RAM 1456.12 FeRAM vs. Dynamic RAM 1466.13 FeRAM vs. Flash Memory 1466.14 Conclusion and Upcoming Trends 1477 Applications of AI/ML Algorithms in VLSI Design and Technology 157Jaswinder Singh and Damanpreet Singh7.1 Introduction 1577.2 Artificial Intelligence and Machine Learning 1597.3 AI/ML Algorithms 1607.4 Supervised Machine Learning (SML) 1627.5 Classification Techniques 1637.6 K-Nearest Neighbors (KNN) 1647.7 Support Vector Machine (SVM) 1667.8 Linearly Separable Classification 1677.9 Decision Tree Classifier (DTC) 1687.10 Performance Measures in Classification 1707.11 Unsupervised Machine Learning (UML) 1737.12 Hierarchical Clustering 1747.13 Partitional Clustering 1767.14 K-Means 1767.15 Fuzzy (soft) Clustering 1777.16 Cluster Validation Measures 1787.17 Internal Clustering Validation Measures 1797.18 External Clustering Validation Criteria 1807.19 Limitation and Challenges — VLSI 1818 Advancement of Neuromorphic Computing Systems with Memristors 193Jeetendra Singh, Shailendra Singh, Balwant Raj, Vikas Patel and Balwinder Raj8.1 Introduction 1948.2 Summary 2069 Neuromorphic Computing and Its Application 217Tejasvini Thakral, Lucky Lamba, Manjeet Singh, Tarun Chaudhary and Mandeep Singh9.1 Introduction 2189.2 Evolution of Neuroinspired Computing Chips 2189.3 Science Behind Brain Physics 2209.4 Limitations of Semiconductor Devices 2219.5 Various Combination of Networks 2259.6 Artificial Intelligence 2289.7 A Summary of Neuromorphic Hardware Methodologies 2299.8 Neuromorphic Computing in Robotics 2319.9 Challenges in Neuromorphic Computing 2329.10 Applications of Neuromorphic Computing 2349.11 Conclusion 23710 Performance Evaluation of Prototype Microstrip Patch Antenna Fabrication Using Microwave Dielectric Ceramic Nanocomposite Materials for X-Band Applications 247Srilali Siragam10.1 Introduction 24810.2 Materials and Methods 25010.3 Results and Discussion 25110.4 Conclusions 25811 Build and Deploy a Smart Speaker with Biometric Authentication and Advanced Voice Interaction Capabilities 271Gur Sharan Kant and Kavi Bhushan11.1 Introduction 27211.2 Cybersecurity Risk as Smart Speakers Don't Have an Authentication Process 27311.3 Related Work 27511.4 Overview of Biometric Authentication and the Voice Algorithm-Based Smart Speaker 27511.5 Conclusion and Discussion 28312 Boron-Based Nanomaterials for Intelligent Drug Delivery Using Computer-Aided Tools 295Jupinder Kaur, Ravinder Kumar and Rajan Vohra12.1 Introduction 29612.2 Computational Details 29712.3 Results and Discussion 29813 Design and Analysis of Rectangular Wave Guide Using an HFSS Simulator 329Srilali Siragam13.1 Background 32913.2 Introduction 33113.3 Mathematical Computations 33313.4 Numerical Analysis 33613.5 Conclusion 344References 344Index 355