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For Authors
Submit a ProposalElectronic Devices and Circuits Beyond CMOS Technologies
One Line Description
Essential for researchers and VLSI engineers navigating the post-CMOS era, this comprehensive guide delivers the theoretical models, device physics, and cutting-edge fabrication techniques needed to master nanomaterials and overcome sub-nanometer scaling challenges.
Description
For more than five decades, complementary metal-oxide-semiconductor (CMOS) technology scaling has propelled unprecedented growth of the semiconductor industry. However, the scaling of planar silicon CMOS nanoscale technology has resulted in various short-channel effects such as velocity saturation, drain-induced barrier lowering, and threshold voltage roll-off effects, culminating in degraded device characteristics, increased leakage currents, and power dissipation. Extensive research is being carried out to address these challenges at multiple levels. This book uniquely explains nanomaterials, devices, and the analysis of their design parameters to meet the sub-nano-regime challenges beyond CMOS technologies. It comprehensively highlights conventional and novel nanomaterials, devices, and circuits, leakage current mitigation techniques, and other important trade-offs. Offering in-depth coverage of temporal degradation and interconnect delay, the book provides insight into state-of-the-art conduction mechanisms, device architecture, operation, performance evaluation, and applications of various nanoscale materials and devices in VLSI circuit design. This essential resource provides relevant theoretical frameworks that include device physics, modelling, circuit design, and the latest developments in experimental fabrication for nanoscale devices.
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For more than five decades, complementary metal-oxide-semiconductor (CMOS) technology scaling has propelled unprecedented growth of the semiconductor industry. However, the scaling of planar silicon CMOS nanoscale technology has resulted in various short-channel effects such as velocity saturation, drain-induced barrier lowering, and threshold voltage roll-off effects, culminating in degraded device characteristics, increased leakage currents, and power dissipation. Extensive research is being carried out to address these challenges at multiple levels. This book uniquely explains nanomaterials, devices, and the analysis of their design parameters to meet the sub-nano-regime challenges beyond CMOS technologies. It comprehensively highlights conventional and novel nanomaterials, devices, and circuits, leakage current mitigation techniques, and other important trade-offs. Offering in-depth coverage of temporal degradation and interconnect delay, the book provides insight into state-of-the-art conduction mechanisms, device architecture, operation, performance evaluation, and applications of various nanoscale materials and devices in VLSI circuit design. This essential resource provides relevant theoretical frameworks that include device physics, modelling, circuit design, and the latest developments in experimental fabrication for nanoscale devices.
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Author / Editor Details
Balwinder Raj, PhD is an Associate Professor and Associate Dean of Postgraduate Academics at the National Institute of Technology Jalandhar, India. He has published ten books, 25 book chapters, and more than 150 research papers in peer-reviewed national and international journals and conferences. His areas of interest include classical and non-classical nanoscale semiconductor device modeling, nanoelectronics and their applications in hardware security, sensors and circuit design, and FinFET-based memory design.
Balwinder Raj, PhD is an Associate Professor and Associate Dean of Postgraduate Academics at the National Institute of Technology Jalandhar, India. He has published ten books, 25 book chapters, and more than 150 research papers in peer-reviewed national and international journals and conferences. His areas of interest include classical and non-classical nanoscale semiconductor device modeling, nanoelectronics and their applications in hardware security, sensors and circuit design, and FinFET-based memory design.
Naushad Alam, PhD is a Professor in the Department of Electronics Engineering in the Zakir Husain College of Engineering and Technology at Aligarh Muslim University, Aligarh, India. He has filed two Indian patents and published 30 research papers in international journals and five book chapters. His research interests include device-circuit co-design, robust nanoscale circuit design, low-power circuit design, and PVT-tolerant circuit design.
Shiromani Balmukund Rahi, PhD is an Assistant Professor in the School of Information and Communication Technology at Gautam Buddha University, Greater Noida, Uttar Pradesh India. He has published 25 research articles, two conference proceedings, 25 book chapters, and seven books. His research interests include advanced semiconductor devices and the development of ultra-low power devices such as tunnel FETs and negative capacitance FETs.
Parveen Kumar, PhD is an Assistant Professor in the Department of Electronics and Communication Engineering at Chandigarh Engineering College, Jhanjeri, Punjab, India. He has authored and co-authored more than 20 research papers in peer-reviewed international journals and conferences. His areas of interest are VLSI design, nanoelectronics, nanoscale MOSFET modeling and simulation, VLSI circuit design, and embedded systems.
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Table of Contents
Preface
Acknowledgement
1. Ferroelectric Field-Effect Transistors Advancements and Applications
Shalini Chaudhary, Basudha Dewan, Sandeep Gupta and Shiromani Balmukund Rahi
1.1 Introduction
1.2 Development of Fe-FET
1.3 Properties of Ferroelectrics
1.3.1 Origin of Polarization in Crystal Structures
1.3.2 Ferroelectric Behavior in Organic Polymers
1.3.3 Field-Induced Polarization and Hysteresis Behavior
1.3.4 Mechanisms of Polarization Switching
1.3.5 Ferroelectric Materials
1.4 Device Physics
1.4.1 Physics of FeFET Based on Landau Theory
1.5 Fe-FETs Applications
1.5.1 Photodetectors
1.5.2 Multifunctional Devices
1.5.3 Sensors
1.5.4 Memory
1.5.5 Adaptive Analog Spiking Neuron
1.6 Prospect and Challenges
1.7 Conclusion
References
2. 18-nm FinFET Technology for Ring Oscillator Design and Comparison with 90-nm CMOS Technology
Beere Naveen Kumar, Midde Manohar, Suman Lata Tripathi and Balwinder Raj
2.1 Introduction
2.2 Ring Oscillator
2.2.1 Design Methodology
2.3 Ring Oscillator Designs on Cadence
2.3.1 Result Analysis
2.4 FinFET-Based Design of Ring Oscillator
2.4.1 Result Analysis
2.5 Comparative Analysis
2.5.1 Power Efficiency
2.5.2 Technology Advancement
2.6 Applications of Ring Oscillator
2.7 Conclusion
Acknowledgment
References
3. Device Simulation–Based Machine Learning Technique for Tunnel Field-Effect Transistors
Basudha Dewan, Shalini Chaudhary and Shiromani Balmukund Rahi
3.1 Introduction
3.1.1 Overview of Emerging Low-Power Device Needs
3.1.2 Significance of Tunnel Field-Effect Transistors in Next-Generation Electronics
3.1.3 Limitations of Traditional Device Design Approaches
3.2 Role of Machine Learning in Revolutionizing Device Simulation
3.3 Fundamentals of TFETs
3.3.1 Working Principle
3.3.2 Figures of Metrics Investigation of TFET for Low Power Applications
3.4 Materials Overview and Its Impact on TFET Performance
3.5 TFET Structural Configurations and Its Notable Figure of Merits
3.6 Simulation of TFET Devices
3.6.1 Importance of Technology Computer-Aided Design Tools
3.6.2 Essential Input Variables and Modeling Challenges in TFET Simulation
3.7 Machine Learning Integration in TFET Design
3.7.1 Need for Machine Learning in Large-Scale Device Optimization
3.7.2 Overview of Machine Learning (ML) Techniques Suitable for Physical Modeling
3.7.2.1 Regression Models
3.7.2.2 Decision Trees and Ensemble Methods
3.7.2.3 Artificial Neural Networks (ANNs)
3.8 Advantages, Limitations, and Interpretability
3.9 Future Scope
3.10 Conclusion
References
4. Memresistor and Its Applications with Challenges
Shahnaz Kossar, Asif Rasool, Kuljit Kaur, Barjinder Kaur, Yogesh Bhalla, Shriya, Burhan Basheer, Abdul Wajid Baht, Vishal Arora, Mohammad Ayaz Ahmad, Kasim Sakran Abass,
Jyoti Sharma and Mir Waqas Alam
4.1 Introduction
4.1.1 Structure of Memresistors
4.1.2 Types of Memresistors
4.1.2.1 Volatile and Non-Volatile Memresistors
4.1.2.2 Non-Volatile Memresistors
4.1.2.3 Volatile Memresistors
4.1.3 Memresistor Based on Various Materials
4.1.4 Binary Oxides for Memresistor Application and Challenges
4.1.5 Perovskite Materials for Memristors: Advantages and Challenges
4.2 Challenges in Memristor-Based Technologies
4.2.1 Material Challenges
4.2.2 Device Variability and Reliability
4.2.3 Power Consumption and Scaling Limitations
4.2.4 Sneak Path and Crossbar Integration Issues
4.2.5 CMOS Compatibility and Integration
4.2.6 Control of Switching Mechanisms
4.2.7 Lack of Standardization and Benchmarking
4.2.8 Environmental and Long-Term Stability
4.2.9 Integration with Neuromorphic Architectures
4.2.10 Commercial Viability and Yield
4.3 Conclusion
Acknowledgement
References
5. A Hybrid Approach for Soft Error Mitigation Using SEIFF
and Machine Learning for Radiation Hardened Electronic Circuits
Divyanshu Shakya and Menka Yadav
5.1 Introduction
5.2 Literature Survey
5.2.1 Introduction to Radiation-Induced Soft Errors
5.2.2 The Role of SRAM in High-Reliability Systems
5.2.3 The Challenges of Soft Errors in Advanced FinFET Technology
5.2.4 Understanding Single-Event Upsets
5.2.5 Understanding Single-Event Transients
5.2.6 Radiation Hardening of Devices
5.2.7 Traditional Mitigation Techniques: Error Correction Codes
5.2.8 Flip-Flop Duplication and Redundancy Techniques
5.2.9 The Soft Error Immune Flip-Flop
5.2.10 Adaptive Error Detection and Management
5.2.11 Real-Time Monitoring and Alerting Mechanisms
5.3 Methodology
5.3.1 Introduction to Radiation Hardening
5.3.2 Signal Input and SEIFF Processing
5.3.2.1 Figure 5.2: It is SEIFF Storage Unit
5.3.2.2 Figure 5.3: It is Complete SEIFF Design
5.3.2.3 Figure 5.4: It is Clocking Mechanism
5.3.3 SEIFF Design and Processing Flow
5.3.4 Updating Output and Comparison Process
5.3.5 Core Training Methodology
5.3.6 Machine Learning Model Integration
5.3.7 Comparison Process
5.3.8 Severity Assessment and Logging
5.3.9 Alert Generation and User Notification
5.3.10 System-Level Workflow and Data Flow
5.3.11 Conclusion of Methodology
5.4 Proposed Work
5.5 Results and Discussion
5.5.1 Performance of SEIFF
5.5.2 Neural Network Model Performance
5.5.3 Comparison Process Analysis
5.5.4 System Robustness and Scalability
5.5.5 Discussion
5.6 Conclusions
Bibliography
6. System Design Beyond MOSFET Using Nonmaterial Integration for Advanced Gas Sensing Applications
Prachi Kesharwani, Kamal Solanki and Manoj Kumar Majumder
6.1 Introduction
6.2 Landscape of Gas Sensing Technologies
6.2.1 FET-Driven Gas Sensors
6.2.2 Emerging Trends in FET-Based Gas Sensors
6.3 Evolution of Nanostructured Materials
6.4 Performance Evaluation of ArGNR-Based Gas Sensor
6.4.1 Overview of Particulate Matter (PM) Contaminant
6.4.2 Structural and Electronic Properties of GNRs for Sensing
6.4.3 Arena of Graphene Nanoribbon (GNR)–Based Sensor
6.4.4 Analytical Modeling of ArGNR-Based Sensors
6.4.4.1 Structural and Computational Modeling
6.4.4.2 Identification of an Optimal Width for the Gas Sensor
6.4.4.3 Optimized Site-Based Conductivity Evaluation
6.5 Characteristics of GNR-FET Devices for Gas Sensing Applications
6.5.1 Advantages of Integrating Nonmaterial in FET
6.5.2 Evolution of GNR-Based FETs
6.6 Conclusion
6.7 Future Outlook
References
7. Carbon Nanotube FET Fractional Voltage Controlled Oscillator Design and Analysis
Ankita Bhatt and Sajad A. Loan
7.1 Introduction
7.2 Fractional Calculus
7.2.1 RC Ladder Component Value Generation
7.3 Scaling MOS Issues with Smaller Technology Nodes
7.3.1 Short-Channel Effects
7.3.1.1 Drain-Induced Barrier Lowering (DIBL)
7.3.1.2 Threshold Voltage Roll-Off
7.3.1.3 Subthreshold Slope Degradation
7.3.2 Gate Control and Oxide Scaling Limits
7.4 Carbon Nanotube Field-Effect Transistor
7.5 Proposed VCO Topology
7.6 Characteristics of a Fractional VCO
7.7 Fractional VCO
7.8 CNTFET VCO
7.8.1 Similarities to MOSFET
7.8.2 Key Differences Semiconducting CNTFETs and Conventional MOSFET
7.8.3 Design of a CNTFET VCO
7.9 CNTFET Fractional VCO
7.10 Power Dissipation
7.11 Fabrication Challenges
7.12 Conclusion
7.13 Future Scope
References
8. Design of Combinational and Sequential Circuits Using
Quantum‑Dot Cellular Automata
V. Ramesh Kumar and Saakshi P. Aayasya
8.1 Introduction
8.1.1 Motivation for Beyond-CMOS Technologies
8.1.2 Introduction to Quantum-Dot Cellular Automata (QCA)
8.1.3 Physical Realizations and Research Developments
8.1.4 Need for New Design Methodologies
8.1.5 The Promise of QCA
8.2 Basics and Clocking Schemes
8.2.1 QCA Basics and Cells
8.2.2 QCA Array and Cell Interactions
8.2.3 Information Propagation and Clocking
8.2.4 Wire-Crossing Technique
8.2.5 Fabrication Technique
8.3 Combinational Circuits
8.3.1 XOR Gate Conventional Design
8.3.2 XOR Gate Multilayer Design
8.3.3 XOR Gate with Nine Cells
8.4 Sequential Circuits
8.4.1 Sequential Circuits
8.4.2 Sequential Circuit Development in QCA
8.4.2.1 Circuit Construction Principles
8.4.2.2 Clocking Scheme in QCA
8.4.3 Clock Edge Detection in QCA
8.4.4 D Latch
8.4.5 Designing the D Flip-Flop Using the D Latch
8.5 Applications and Future Scope of QCA
8.5.1 Applications and Use in Adders
8.5.2 Challenges and Breakthroughs in Large-Scale QCA
8.5.3 Future Scope
8.6 Conclusion
References
9. Evolution and Performance of Nanoscale Transistors: FinFET, Nanosheet, and Nanowire FETs
Shankhamitra Sunani, Satya Sopan Mahato, M. Suresh and Raghunandan Swain
9.1 Introduction
9.2 Related Work
9.3 SMG and TMG Tri-Gate FinFET with a Gate Length of 7 nm
9.4 SMG and TMG Nanosheet FET at 7-nm Gate Length
9.5 SMG and TMG CGAA NWFET at 7-nm Gate Length
9.6 Conclusion and Future Scope
References
10. Magnetic Tunnel Junction Devices and a its Application
Beyond CMOS Technology
Shahneela Jamal Kidwai, Naushad Alam, Subodh Wairya and Anurag Yadav
10.1 Introduction
10.2 CMOS Technology Limitations
10.3 Spin-Polarized Electronic Structure and Transport in Ferromagnetic Metals
10.4 Giant Magnetoresistance (GMR) and Tunnel Magnetoresistance (TMR)
10.5 Magnetic Tunnel Junction
10.5.1 Magnetic Tunnel Junction Device Structure
10.5.2 The Two Channel Model
10.5.3 Types of Magnetic Tunnel Junction
10.5.4 Magnetic Tunnel Junction Operation
10.6 Switching Techniques in MTJ
10.6.1 Spin Transfer Torque (STT)
10.6.2 Spin-Orbit Torque (SOT)
10.6.3 Voltage-Controlled Magnetic Anisotropy (VCMA)
10.7 Voltage-Gated Spin-Orbit Torque (VGSOT) Switching in MTJs
10.7.1 Modeling and Transient Analysis of VGSOT-MTJ in Cadence
10.7.2 Applications of VGSOT‑MTJ
10.8 Challenges in Integrating MTJs into CMOS Circuits
10.8.1 Thermal Budget and Material Compatibility
10.8.2 Process Variability and Device Reliability
10.8.3 Circuit-Level Issues: Read/Write Reliability
10.8.4 Thermal Stress and Joule Heating
10.8.5 Design-Level Complexity and Scalability
10.8.6 Endurance, Retention, and Read Disturb
10.9 Conclusion
10.10 Future Scope
References
11. Source-Engineered Tunnel FET for Mitigation of P-I-N Forward Leakage Current and Analysis
Syed Afzal Ahmad and Naushad Alam
11.1 Introduction
11.2 Principle of Operation, Device Structure, and Simulation
Setup
11.3 Results and Discussion
11.4 Conclusion
11.5 Future Scope
References
12. Electronic Devices in Smart Farming
Ashanand, Parveen Kumar, Harwinder Singh Rattan and Vivek Kumar
12.1 Introduction
12.2 Literature Review
12.2.1 Drones (Unmanned Aerial Vehicles) in Agriculture
12.2.1.1 Driverless Tractors and Field Machines
12.2.1.2 Robotic Harvesters and Picking Robots
12.2.1.3 Weeding Robots and Laser Systems
12.2.1.4 Milking and Livestock Robots
12.2.2 Automated Systems and Controlled-Environment Agriculture
12.2.2.1 Smart Irrigation Systems
12.2.2.2 Integrated Farm Management Systems (IFMSs)
12.2.3 Data-Driven Decision Support and Analytics
12.2.3.1 Predictive Analytics and AI Models
12.2.3.2 Variable Rate Technology (VRT)
12.2.3.3 Digital Twins and Modeling
12.3 Sustainability Benefits
12.4 Challenges and Barriers
12.4.1 Connectivity Limitations
12.4.2 Data Management and Security
12.5 Future Trends and Opportunities
12.6 Conclusion
References
13. E-Skin Technology and its Applications
Sachin Kumar, Karan Veer, Ankita Sharma and Shalini Sharma
13.1 Introduction
13.2 Materials and Fabrication Techniques
13.2.1 Materials for E-Skin
13.2.2 Fabrication Techniques
13.2.2.1 Photolithography and PCB Designing
13.2.3 Three-Dimensional (3D) Printing
13.2.4 Inkjet Printing
13.2.4.1 Printing Approaches
13.2.4.2 Ink’s Property
13.2.4.3 Substrate
13.2.4.4 High Resolution and Uniformity
13.2.5 Transfer Printing
13.3 Sensor Technologies in E-Skin
13.3.1 Tactile Sensors
13.3.2 Temperature Sensors
13.3.3 Biochemical Sensors
13.3.4 Optical Sensors
13.4 Applications of E-Skin
13.4.1 Healthcare and Wearable Equipment
13.4.2 Robotics and Prosthetics
13.4.3 Human-Machine Interfaces
13.4.3.1 Gesture Recognition Systems
13.4.3.2 Wearable AR and VR Control Systems
13.4.4 Environmental and Industrial Surveillance
13.5 Challenges and Limitations
13.6 Conclusion and Future Scope
References
14. Nanostructured Materials for In Vivo Dopamine Quantification Using Electrochemical Biosensors
Parthasarathy P. and Venkatesh M.
14.1 Introduction
14.2 Electroanalytical Methods
14.2.1 Amperometry
14.2.2 Cyclic Voltammetry
14.2.3 Differential Pulse Voltammetry
14.3 Modification Materials for Dopamine Electrochemical Sensing
14.3.1 Metal Oxide and Metal–Based Nanomaterials
14.3.2 Carbon and Graphene
14.4 Importance of Electrode Fabrication
14.5 Conclusion and Future Perspectives
References
15. Ultrasensitive Detection of Biomolecules Using Carbon
Nanotube FET Biosensors
Parthasarathy P. and Venkatesh M.
15.1 Introduction
15.2 CNT FET’s for Biochemical Sensing
15.2.1 Materials
15.2.2 Structure
15.3 Correlation between Performance of CNT FETs and Biosensors
15.3.1 Voltage Shift (ΔVth)
15.3.2 Absolute Current Change ΔL
15.4 Biosensing Surface Functionalization
15.5 Biosensor and Packaging Performance Index
15.6 Problems and Applications
15.7 Conclusion
References
16. Emerging Device Architectures for Beyond CMOS Technology
Nazia Haneef, Mohd. Adil Raushan, Md. Yasir Bashir and Mohd. Jawaid Siddiqui
16.1 Introduction
16.1.1 Transistor Action
16.1.2 The Need for Scaling
16.2 Short-Channel Effects
16.3 Requirements of New Design Device
16.4 Tunnel Field-Effect Transistor (TFET)
16.4.1 TFET Working Principle
16.5 Electrostatic Doping
16.6 Dopingless Tunnel Field-Effect Transistor (DLTFET)
16.7 Junctionless TFET
16.8 Challenges in TFETs
16.8.1 Low ON-State Current
16.8.2 Ambipolar Conduction
16.8.3 P-I-N Forward Leakage
16.8.4 Impact on Circuits
16.9 Conclusion
References
17. An Overview of Heterostructures and Its Applications Using Nano‑Substrates of GaAs and InAs
Ayan Mustafa Khan, Mohd. Suhaib Kidwai and Saima Beg
17.1 Introduction
17.2 Applications of Heterostructures/Heterojunctions
17.2.1 Heterojunction LEDs
17.2.2 Heterostructure Lasers
17.3 Classification of Heterojunctions
17.3.1 On Band Alignment Basis
17.3.2 On Conductivity Basis
17.3.3 On Refractive Index Profile Basis
17.4 Heterostructures with Demonstration of Lasing Mechanism
17.5 Epitaxial Growth of Heterostructures
17.6 Energy Bands of InGaAs (With Substrates GaAs andzInAs)
17.7 Energy Bands of GaAsSb (With Substrate GaAs)
17.8 Energy Bands of InAlAs (With Substrate AlAs)
17.9 Energy Bands of III-Nitride Semiconductor Compounds
17.10 Conclusion
17.11 Future Scope
References
18. Nanowire Field-Effect Transistors and Their Applications
Asif Rasool, Shahnaz Kossar, Ghulam Murtaza, Mohammed Salman Baig, Ramyashri S., R. Amiruddin and Mohsin Fayaz
18.1 Introduction
18.2 Nanowire-Based FET Biosensor and Its Applications
18.3 Gas Sensing Applications
18.4 Photodetection and Optoelectronics
18.4.1 High Photocurrent Generation
18.4.2 Gate-Tunable Photoresponse
18.4.3 High Responsivity and Photoconductive Gain
18.4.4 Fast Response and Recovery Times
18.4.5 Low Dark Current and High Signal-to-Noise Ratio
18.4.6 Spectral Selectivity
18.5 Performance Metrics
18.6 Materials and Fabrication Techniques
18.7 Emerging Trends and Research Directions
18.7.1 Integration with 2D Materials and Heterostructures
18.7.2 Quantum Computing and Single-Electron Transistors
18.7.3 AI Hardware and In-Memory Computing
18.8 Conclusion
References
Index
Back to Top
Preface
Acknowledgement
1. Ferroelectric Field-Effect Transistors Advancements and Applications
Shalini Chaudhary, Basudha Dewan, Sandeep Gupta and Shiromani Balmukund Rahi
1.1 Introduction
1.2 Development of Fe-FET
1.3 Properties of Ferroelectrics
1.3.1 Origin of Polarization in Crystal Structures
1.3.2 Ferroelectric Behavior in Organic Polymers
1.3.3 Field-Induced Polarization and Hysteresis Behavior
1.3.4 Mechanisms of Polarization Switching
1.3.5 Ferroelectric Materials
1.4 Device Physics
1.4.1 Physics of FeFET Based on Landau Theory
1.5 Fe-FETs Applications
1.5.1 Photodetectors
1.5.2 Multifunctional Devices
1.5.3 Sensors
1.5.4 Memory
1.5.5 Adaptive Analog Spiking Neuron
1.6 Prospect and Challenges
1.7 Conclusion
References
2. 18-nm FinFET Technology for Ring Oscillator Design and Comparison with 90-nm CMOS Technology
Beere Naveen Kumar, Midde Manohar, Suman Lata Tripathi and Balwinder Raj
2.1 Introduction
2.2 Ring Oscillator
2.2.1 Design Methodology
2.3 Ring Oscillator Designs on Cadence
2.3.1 Result Analysis
2.4 FinFET-Based Design of Ring Oscillator
2.4.1 Result Analysis
2.5 Comparative Analysis
2.5.1 Power Efficiency
2.5.2 Technology Advancement
2.6 Applications of Ring Oscillator
2.7 Conclusion
Acknowledgment
References
3. Device Simulation–Based Machine Learning Technique for Tunnel Field-Effect Transistors
Basudha Dewan, Shalini Chaudhary and Shiromani Balmukund Rahi
3.1 Introduction
3.1.1 Overview of Emerging Low-Power Device Needs
3.1.2 Significance of Tunnel Field-Effect Transistors in Next-Generation Electronics
3.1.3 Limitations of Traditional Device Design Approaches
3.2 Role of Machine Learning in Revolutionizing Device Simulation
3.3 Fundamentals of TFETs
3.3.1 Working Principle
3.3.2 Figures of Metrics Investigation of TFET for Low Power Applications
3.4 Materials Overview and Its Impact on TFET Performance
3.5 TFET Structural Configurations and Its Notable Figure of Merits
3.6 Simulation of TFET Devices
3.6.1 Importance of Technology Computer-Aided Design Tools
3.6.2 Essential Input Variables and Modeling Challenges in TFET Simulation
3.7 Machine Learning Integration in TFET Design
3.7.1 Need for Machine Learning in Large-Scale Device Optimization
3.7.2 Overview of Machine Learning (ML) Techniques Suitable for Physical Modeling
3.7.2.1 Regression Models
3.7.2.2 Decision Trees and Ensemble Methods
3.7.2.3 Artificial Neural Networks (ANNs)
3.8 Advantages, Limitations, and Interpretability
3.9 Future Scope
3.10 Conclusion
References
4. Memresistor and Its Applications with Challenges
Shahnaz Kossar, Asif Rasool, Kuljit Kaur, Barjinder Kaur, Yogesh Bhalla, Shriya, Burhan Basheer, Abdul Wajid Baht, Vishal Arora, Mohammad Ayaz Ahmad, Kasim Sakran Abass,
Jyoti Sharma and Mir Waqas Alam
4.1 Introduction
4.1.1 Structure of Memresistors
4.1.2 Types of Memresistors
4.1.2.1 Volatile and Non-Volatile Memresistors
4.1.2.2 Non-Volatile Memresistors
4.1.2.3 Volatile Memresistors
4.1.3 Memresistor Based on Various Materials
4.1.4 Binary Oxides for Memresistor Application and Challenges
4.1.5 Perovskite Materials for Memristors: Advantages and Challenges
4.2 Challenges in Memristor-Based Technologies
4.2.1 Material Challenges
4.2.2 Device Variability and Reliability
4.2.3 Power Consumption and Scaling Limitations
4.2.4 Sneak Path and Crossbar Integration Issues
4.2.5 CMOS Compatibility and Integration
4.2.6 Control of Switching Mechanisms
4.2.7 Lack of Standardization and Benchmarking
4.2.8 Environmental and Long-Term Stability
4.2.9 Integration with Neuromorphic Architectures
4.2.10 Commercial Viability and Yield
4.3 Conclusion
Acknowledgement
References
5. A Hybrid Approach for Soft Error Mitigation Using SEIFF
and Machine Learning for Radiation Hardened Electronic Circuits
Divyanshu Shakya and Menka Yadav
5.1 Introduction
5.2 Literature Survey
5.2.1 Introduction to Radiation-Induced Soft Errors
5.2.2 The Role of SRAM in High-Reliability Systems
5.2.3 The Challenges of Soft Errors in Advanced FinFET Technology
5.2.4 Understanding Single-Event Upsets
5.2.5 Understanding Single-Event Transients
5.2.6 Radiation Hardening of Devices
5.2.7 Traditional Mitigation Techniques: Error Correction Codes
5.2.8 Flip-Flop Duplication and Redundancy Techniques
5.2.9 The Soft Error Immune Flip-Flop
5.2.10 Adaptive Error Detection and Management
5.2.11 Real-Time Monitoring and Alerting Mechanisms
5.3 Methodology
5.3.1 Introduction to Radiation Hardening
5.3.2 Signal Input and SEIFF Processing
5.3.2.1 Figure 5.2: It is SEIFF Storage Unit
5.3.2.2 Figure 5.3: It is Complete SEIFF Design
5.3.2.3 Figure 5.4: It is Clocking Mechanism
5.3.3 SEIFF Design and Processing Flow
5.3.4 Updating Output and Comparison Process
5.3.5 Core Training Methodology
5.3.6 Machine Learning Model Integration
5.3.7 Comparison Process
5.3.8 Severity Assessment and Logging
5.3.9 Alert Generation and User Notification
5.3.10 System-Level Workflow and Data Flow
5.3.11 Conclusion of Methodology
5.4 Proposed Work
5.5 Results and Discussion
5.5.1 Performance of SEIFF
5.5.2 Neural Network Model Performance
5.5.3 Comparison Process Analysis
5.5.4 System Robustness and Scalability
5.5.5 Discussion
5.6 Conclusions
Bibliography
6. System Design Beyond MOSFET Using Nonmaterial Integration for Advanced Gas Sensing Applications
Prachi Kesharwani, Kamal Solanki and Manoj Kumar Majumder
6.1 Introduction
6.2 Landscape of Gas Sensing Technologies
6.2.1 FET-Driven Gas Sensors
6.2.2 Emerging Trends in FET-Based Gas Sensors
6.3 Evolution of Nanostructured Materials
6.4 Performance Evaluation of ArGNR-Based Gas Sensor
6.4.1 Overview of Particulate Matter (PM) Contaminant
6.4.2 Structural and Electronic Properties of GNRs for Sensing
6.4.3 Arena of Graphene Nanoribbon (GNR)–Based Sensor
6.4.4 Analytical Modeling of ArGNR-Based Sensors
6.4.4.1 Structural and Computational Modeling
6.4.4.2 Identification of an Optimal Width for the Gas Sensor
6.4.4.3 Optimized Site-Based Conductivity Evaluation
6.5 Characteristics of GNR-FET Devices for Gas Sensing Applications
6.5.1 Advantages of Integrating Nonmaterial in FET
6.5.2 Evolution of GNR-Based FETs
6.6 Conclusion
6.7 Future Outlook
References
7. Carbon Nanotube FET Fractional Voltage Controlled Oscillator Design and Analysis
Ankita Bhatt and Sajad A. Loan
7.1 Introduction
7.2 Fractional Calculus
7.2.1 RC Ladder Component Value Generation
7.3 Scaling MOS Issues with Smaller Technology Nodes
7.3.1 Short-Channel Effects
7.3.1.1 Drain-Induced Barrier Lowering (DIBL)
7.3.1.2 Threshold Voltage Roll-Off
7.3.1.3 Subthreshold Slope Degradation
7.3.2 Gate Control and Oxide Scaling Limits
7.4 Carbon Nanotube Field-Effect Transistor
7.5 Proposed VCO Topology
7.6 Characteristics of a Fractional VCO
7.7 Fractional VCO
7.8 CNTFET VCO
7.8.1 Similarities to MOSFET
7.8.2 Key Differences Semiconducting CNTFETs and Conventional MOSFET
7.8.3 Design of a CNTFET VCO
7.9 CNTFET Fractional VCO
7.10 Power Dissipation
7.11 Fabrication Challenges
7.12 Conclusion
7.13 Future Scope
References
8. Design of Combinational and Sequential Circuits Using
Quantum‑Dot Cellular Automata
V. Ramesh Kumar and Saakshi P. Aayasya
8.1 Introduction
8.1.1 Motivation for Beyond-CMOS Technologies
8.1.2 Introduction to Quantum-Dot Cellular Automata (QCA)
8.1.3 Physical Realizations and Research Developments
8.1.4 Need for New Design Methodologies
8.1.5 The Promise of QCA
8.2 Basics and Clocking Schemes
8.2.1 QCA Basics and Cells
8.2.2 QCA Array and Cell Interactions
8.2.3 Information Propagation and Clocking
8.2.4 Wire-Crossing Technique
8.2.5 Fabrication Technique
8.3 Combinational Circuits
8.3.1 XOR Gate Conventional Design
8.3.2 XOR Gate Multilayer Design
8.3.3 XOR Gate with Nine Cells
8.4 Sequential Circuits
8.4.1 Sequential Circuits
8.4.2 Sequential Circuit Development in QCA
8.4.2.1 Circuit Construction Principles
8.4.2.2 Clocking Scheme in QCA
8.4.3 Clock Edge Detection in QCA
8.4.4 D Latch
8.4.5 Designing the D Flip-Flop Using the D Latch
8.5 Applications and Future Scope of QCA
8.5.1 Applications and Use in Adders
8.5.2 Challenges and Breakthroughs in Large-Scale QCA
8.5.3 Future Scope
8.6 Conclusion
References
9. Evolution and Performance of Nanoscale Transistors: FinFET, Nanosheet, and Nanowire FETs
Shankhamitra Sunani, Satya Sopan Mahato, M. Suresh and Raghunandan Swain
9.1 Introduction
9.2 Related Work
9.3 SMG and TMG Tri-Gate FinFET with a Gate Length of 7 nm
9.4 SMG and TMG Nanosheet FET at 7-nm Gate Length
9.5 SMG and TMG CGAA NWFET at 7-nm Gate Length
9.6 Conclusion and Future Scope
References
10. Magnetic Tunnel Junction Devices and a its Application
Beyond CMOS Technology
Shahneela Jamal Kidwai, Naushad Alam, Subodh Wairya and Anurag Yadav
10.1 Introduction
10.2 CMOS Technology Limitations
10.3 Spin-Polarized Electronic Structure and Transport in Ferromagnetic Metals
10.4 Giant Magnetoresistance (GMR) and Tunnel Magnetoresistance (TMR)
10.5 Magnetic Tunnel Junction
10.5.1 Magnetic Tunnel Junction Device Structure
10.5.2 The Two Channel Model
10.5.3 Types of Magnetic Tunnel Junction
10.5.4 Magnetic Tunnel Junction Operation
10.6 Switching Techniques in MTJ
10.6.1 Spin Transfer Torque (STT)
10.6.2 Spin-Orbit Torque (SOT)
10.6.3 Voltage-Controlled Magnetic Anisotropy (VCMA)
10.7 Voltage-Gated Spin-Orbit Torque (VGSOT) Switching in MTJs
10.7.1 Modeling and Transient Analysis of VGSOT-MTJ in Cadence
10.7.2 Applications of VGSOT‑MTJ
10.8 Challenges in Integrating MTJs into CMOS Circuits
10.8.1 Thermal Budget and Material Compatibility
10.8.2 Process Variability and Device Reliability
10.8.3 Circuit-Level Issues: Read/Write Reliability
10.8.4 Thermal Stress and Joule Heating
10.8.5 Design-Level Complexity and Scalability
10.8.6 Endurance, Retention, and Read Disturb
10.9 Conclusion
10.10 Future Scope
References
11. Source-Engineered Tunnel FET for Mitigation of P-I-N Forward Leakage Current and Analysis
Syed Afzal Ahmad and Naushad Alam
11.1 Introduction
11.2 Principle of Operation, Device Structure, and Simulation
Setup
11.3 Results and Discussion
11.4 Conclusion
11.5 Future Scope
References
12. Electronic Devices in Smart Farming
Ashanand, Parveen Kumar, Harwinder Singh Rattan and Vivek Kumar
12.1 Introduction
12.2 Literature Review
12.2.1 Drones (Unmanned Aerial Vehicles) in Agriculture
12.2.1.1 Driverless Tractors and Field Machines
12.2.1.2 Robotic Harvesters and Picking Robots
12.2.1.3 Weeding Robots and Laser Systems
12.2.1.4 Milking and Livestock Robots
12.2.2 Automated Systems and Controlled-Environment Agriculture
12.2.2.1 Smart Irrigation Systems
12.2.2.2 Integrated Farm Management Systems (IFMSs)
12.2.3 Data-Driven Decision Support and Analytics
12.2.3.1 Predictive Analytics and AI Models
12.2.3.2 Variable Rate Technology (VRT)
12.2.3.3 Digital Twins and Modeling
12.3 Sustainability Benefits
12.4 Challenges and Barriers
12.4.1 Connectivity Limitations
12.4.2 Data Management and Security
12.5 Future Trends and Opportunities
12.6 Conclusion
References
13. E-Skin Technology and its Applications
Sachin Kumar, Karan Veer, Ankita Sharma and Shalini Sharma
13.1 Introduction
13.2 Materials and Fabrication Techniques
13.2.1 Materials for E-Skin
13.2.2 Fabrication Techniques
13.2.2.1 Photolithography and PCB Designing
13.2.3 Three-Dimensional (3D) Printing
13.2.4 Inkjet Printing
13.2.4.1 Printing Approaches
13.2.4.2 Ink’s Property
13.2.4.3 Substrate
13.2.4.4 High Resolution and Uniformity
13.2.5 Transfer Printing
13.3 Sensor Technologies in E-Skin
13.3.1 Tactile Sensors
13.3.2 Temperature Sensors
13.3.3 Biochemical Sensors
13.3.4 Optical Sensors
13.4 Applications of E-Skin
13.4.1 Healthcare and Wearable Equipment
13.4.2 Robotics and Prosthetics
13.4.3 Human-Machine Interfaces
13.4.3.1 Gesture Recognition Systems
13.4.3.2 Wearable AR and VR Control Systems
13.4.4 Environmental and Industrial Surveillance
13.5 Challenges and Limitations
13.6 Conclusion and Future Scope
References
14. Nanostructured Materials for In Vivo Dopamine Quantification Using Electrochemical Biosensors
Parthasarathy P. and Venkatesh M.
14.1 Introduction
14.2 Electroanalytical Methods
14.2.1 Amperometry
14.2.2 Cyclic Voltammetry
14.2.3 Differential Pulse Voltammetry
14.3 Modification Materials for Dopamine Electrochemical Sensing
14.3.1 Metal Oxide and Metal–Based Nanomaterials
14.3.2 Carbon and Graphene
14.4 Importance of Electrode Fabrication
14.5 Conclusion and Future Perspectives
References
15. Ultrasensitive Detection of Biomolecules Using Carbon
Nanotube FET Biosensors
Parthasarathy P. and Venkatesh M.
15.1 Introduction
15.2 CNT FET’s for Biochemical Sensing
15.2.1 Materials
15.2.2 Structure
15.3 Correlation between Performance of CNT FETs and Biosensors
15.3.1 Voltage Shift (ΔVth)
15.3.2 Absolute Current Change ΔL
15.4 Biosensing Surface Functionalization
15.5 Biosensor and Packaging Performance Index
15.6 Problems and Applications
15.7 Conclusion
References
16. Emerging Device Architectures for Beyond CMOS Technology
Nazia Haneef, Mohd. Adil Raushan, Md. Yasir Bashir and Mohd. Jawaid Siddiqui
16.1 Introduction
16.1.1 Transistor Action
16.1.2 The Need for Scaling
16.2 Short-Channel Effects
16.3 Requirements of New Design Device
16.4 Tunnel Field-Effect Transistor (TFET)
16.4.1 TFET Working Principle
16.5 Electrostatic Doping
16.6 Dopingless Tunnel Field-Effect Transistor (DLTFET)
16.7 Junctionless TFET
16.8 Challenges in TFETs
16.8.1 Low ON-State Current
16.8.2 Ambipolar Conduction
16.8.3 P-I-N Forward Leakage
16.8.4 Impact on Circuits
16.9 Conclusion
References
17. An Overview of Heterostructures and Its Applications Using Nano‑Substrates of GaAs and InAs
Ayan Mustafa Khan, Mohd. Suhaib Kidwai and Saima Beg
17.1 Introduction
17.2 Applications of Heterostructures/Heterojunctions
17.2.1 Heterojunction LEDs
17.2.2 Heterostructure Lasers
17.3 Classification of Heterojunctions
17.3.1 On Band Alignment Basis
17.3.2 On Conductivity Basis
17.3.3 On Refractive Index Profile Basis
17.4 Heterostructures with Demonstration of Lasing Mechanism
17.5 Epitaxial Growth of Heterostructures
17.6 Energy Bands of InGaAs (With Substrates GaAs andzInAs)
17.7 Energy Bands of GaAsSb (With Substrate GaAs)
17.8 Energy Bands of InAlAs (With Substrate AlAs)
17.9 Energy Bands of III-Nitride Semiconductor Compounds
17.10 Conclusion
17.11 Future Scope
References
18. Nanowire Field-Effect Transistors and Their Applications
Asif Rasool, Shahnaz Kossar, Ghulam Murtaza, Mohammed Salman Baig, Ramyashri S., R. Amiruddin and Mohsin Fayaz
18.1 Introduction
18.2 Nanowire-Based FET Biosensor and Its Applications
18.3 Gas Sensing Applications
18.4 Photodetection and Optoelectronics
18.4.1 High Photocurrent Generation
18.4.2 Gate-Tunable Photoresponse
18.4.3 High Responsivity and Photoconductive Gain
18.4.4 Fast Response and Recovery Times
18.4.5 Low Dark Current and High Signal-to-Noise Ratio
18.4.6 Spectral Selectivity
18.5 Performance Metrics
18.6 Materials and Fabrication Techniques
18.7 Emerging Trends and Research Directions
18.7.1 Integration with 2D Materials and Heterostructures
18.7.2 Quantum Computing and Single-Electron Transistors
18.7.3 AI Hardware and In-Memory Computing
18.8 Conclusion
References
Index
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