| Description |
1 online resource |
| Contents |
Cover; Half Title; Title Page; Copyright Page; Contents; Preface; 1. Introduction to Graphene; 1.1 Physical Geometry and Properties; 1.2 Graphene Nanoribbon; 2. Graphene for Integrated Circuits; 2.1 Introduction; 2.2 Scaling Challenges of Silicon Electronics; 2.3 Graphene-Based Field-Effect Transistors; 2.4 Graphene-Based Integrated Circuits; 3. Computational Carrier Transport Model of GNRFET; 3.1 Introduction; 3.2 Quantum Transport Model; 3.3 Quantum Capacitance in GNRFET; 3.4 Computational Time; 3.5 Summary; 4. Scaling Effects on Performance of GNRFETs; 4.1 Introduction |
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4.2 Device Structure4.3 Transfer Characteristics of GNRFETs; 4.4 Scaling Effects on Static Metric of GNRFETs; 4.4.1 OFF-Current; 4.4.2 I[sub(ON)]/I[sub(OFF)] Ratio; 4.4.3 Subthreshold Swing; 4.4.4 Drain-Induced Barrier Lowering; 4.4.5 Voltage Transfer Characteristic; 4.5 Scaling Effects on Switching Attributes of GNRFETs; 4.5.1 Intrinsic Gate Capacitance; 4.5.2 Intrinsic Cut-off Frequency; 4.5.3 Intrinsic Gate-Delay Time; 4.5.4 Power-Delay Product; 4.6 Summary; 5. Width-Dependent Performance of GNRFETs; 5.1 Introduction; 5.2 Device Structure; 5.3 GNR Sub-bands |
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5.4 Width-Dependent Static Metrics of GNRFETs5.4.1 OFF-Current; 5.4.2 I[sub(ON)]/I[sub(OFF)] Ratio; 5.4.3 Subthreshold Swing; 5.5 Width-Dependent Switching Attribute of GNRFETs; 5.5.1 Threshold Voltage; 5.5.2 Transconductance; 5.5.3 Intrinsic Gate Capacitance; 5.5.4 Intrinsic Cut-off Frequency; 5.5.5 Intrinsic Gate-Delay Time; 5.6 Summary; 6. A SPICE Physics-Based Circuit Model of GNRFETs; 6.1 Introduction; 6.2 GNRFET Structure; 6.3 GNRFET Model; 6.3.1 Computing GNR Sub-bands; 6.3.2 Finding Channel Surface Potential; 6.3.2.1 Computing channel charge |
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6.3.2.2 Computing transient capacitance charge6.3.3 Current Modeling; 6.3.3.1 Computing thermionic current; 6.3.3.2 BTBT current and charge; 6.3.4 Non-ballistic Transport; 6.3.5 Extracting Fitting Parameters; 6.4 Model Validation; 6.4.1 Comparing with Computational NEGF Formalism; 6.4.2 Comparing with Many-Body Problem; 6.5 Effect of Edge Roughness on Device Characteristic; 6.5.1 Transfer Characteristics of GNRFETs; 6.5.2 OFF-State Characteristics of GNRFETs; 6.6 Summary; 7. Graphene-Based Circuit Design; 7.1 Introduction; 7.2 All-Graphene Circuits; 7.3 Graphene Inverter |
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7.4 Power and Delay of GNRFET Circuits7.5 GNRFET-Based Energy Recovery Logic Design; 7.6 Summary; 8. Graphene Sensing and Energy Recovery; 8.1 Introduction; 8.2 GNRFET-Based Temperature Sensors; 8.3 GNRFET for Energy Harvesting; 8.3.1 Thermoelectric Model; 8.3.2 Electrical Conductivity; 8.3.3 Seebeck Coefficient; 8.3.4 Electrical Thermal Conductivity; 8.3.5 Power Factor; 8.3.6 Thermoelectric Figure-of-Merit ZT; 8.4 Summary; 9. Graphene Photonic Properties and Applications; 9.1 Introduction; 9.2 Photonic Properties; 9.3 Graphene Photonic Applications |
| Summary |
Tremendous innovations in electronics and photonics over the past few decades have resulted in the downsizing of transistors in integrated circuits, which are now approaching atomic scales. This will soon result in the creation of a growing knowledge gap between the underlying technology and state-of-the-art electronic device modeling and simulations. This book bridges the gap by presenting cutting-edge research in the computational analysis and mathematical modeling of graphene nanostructures as well as the recent progress on graphene transistors for nanoscale circuits. It inspires and educates fellow circuit designers and students in the field of emerging low-power and high-performance circuit designs based on graphene. While most of the books focus on the synthesis, fabrication, and characterization of graphene, this book shines a light on graphene models and their circuit simulations and applications in photonics. It will serve as a textbook for graduate-level courses in nanoscale electronics and photonics design and appeal to anyone involved in electrical engineering, applied physics, materials science, or nanotechnology research |
| Notes |
Introduction to Graphene. Graphene for Integrated Circuits. Computational Carrier Transport Model of GNRFET. Scaling Effects on Performance of GNRFETs. Width-dependent Performance of GNRFETs. A Spice Physics-based Circuit Model of GNRFET. Graphene-based Circuits Design. Graphene Sensing and Energy Recovery. Graphene Photonic Properties and Applications. Graphene-based Thermal Emitter |
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Yaser M. Banadaki is assistant professor at the Department of Computer Science, College of Science and Engineering, Southern University and A & M College, Baton Rouge, Louisiana, USA. He received his PhD in electrical and computer engineering from Louisiana State University (LSU), USA, in 2016. His current research focuses on the computational modeling and experimental validation of novel materials and nanostructures for information technology and sensor devices. He is also interested in material knowledge discovery techniques using machine learning algorithms. Safura Sharifi is a quantum technology researcher at the Hearne Institute for Theoretical Physics, LSU. She received her PhD in electrical engineering from LSU in 2019. Her current research focuses on machine learning, quantum technology, and 2D materials for information technology |
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CIP data; resource not viewed |
| Subject |
Graphene.
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Nanostructures.
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Nanoelectromechanical systems.
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Nanostructures
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SCIENCE -- Life Sciences -- General.
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TECHNOLOGY -- Electronics -- General.
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TECHNOLOGY -- Nanotechnology.
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Graphene
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Nanoelectromechanical systems
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Nanostructures
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| Form |
Electronic book
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| Author |
Sharifi, Safura, author
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| ISBN |
9780429663871 |
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0429663870 |
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9780429666599 |
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0429666594 |
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9780429661150 |
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0429661150 |
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9780429022210 |
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0429022212 |
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