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FinFET Modeling for IC Simulation and Design: Using the BSIM-CMG Standard [Kõva köide]

(Thomas J. Watson Research Center 1101 Kitchawan Road, Yorktown Heights, New York, United States of America), (Skyworks Solutions, I), , , , , , (Chair Professor, Department of Electrical Engineering, Indian Institute of Technology Kanpur, India)
  • Formaat: Hardback, 304 pages, kõrgus x laius: 235x191 mm, kaal: 810 g, 200 illustrations; Illustrations, unspecified
  • Ilmumisaeg: 20-Feb-2015
  • Kirjastus: Academic Press Inc
  • ISBN-10: 0124200311
  • ISBN-13: 9780124200319
Teised raamatud teemal:
  • Formaat: Hardback, 304 pages, kõrgus x laius: 235x191 mm, kaal: 810 g, 200 illustrations; Illustrations, unspecified
  • Ilmumisaeg: 20-Feb-2015
  • Kirjastus: Academic Press Inc
  • ISBN-10: 0124200311
  • ISBN-13: 9780124200319
Teised raamatud teemal:

This book is the first to explain FinFET modeling for IC simulation and the industry standard – BSIM-CMG - describing the rush in demand for advancing the technology from planar to 3D architecture, as now enabled by the approved industry standard.

The book gives a strong foundation on the physics and operation of FinFET, details aspects of the BSIM-CMG model such as surface potential, charge and current calculations, and includes a dedicated chapter on parameter extraction procedures, providing a step-by-step approach for the efficient extraction of model parameters.

With this book you will learn:

  • Why you should use FinFET
  • The physics and operation of FinFET
  • Details of the FinFET standard model (BSIM-CMG)
  • Parameter extraction in BSIM-CMG
  • FinFET circuit design and simulation

    • Authored by the lead inventor and developer of FinFET, and developers of the BSIM-CM standard model, providing an experts’ insight into the specifications of the standard
    • The first book on the industry-standard FinFET model - BSIM-CMG

    Muu info

    Learn how to do FinFET modeling using the BSIM-CMG standard from the experts
    Author Biographies ix
    Preface xi
    Chapter 1 FinFET---From device concept to standard compact model
    1(14)
    1.1 The root cause of short-channel effects in the twenty-first century MOSFETs
    2(2)
    1.2 The thin-body MOSFET concept
    4(1)
    1.3 The FinFET and a new scaling path for MOSFETs
    4(2)
    1.4 Ultra-thin-body FET
    6(1)
    1.5 FinFET compact model---the bridge between FinFET technology and IC design
    7(1)
    1.6 A brief history of the first standard compact model, BSIM
    8(1)
    1.7 Core and real-device models
    9(2)
    1.8 The industry standard FinFET compact model
    11(4)
    References
    12(3)
    Chapter 2 Compact models for analog and RF applications
    15(56)
    2.1 Introduction
    15(1)
    2.2 Important compact model metrics
    16(1)
    2.3 Analog metrics
    16(28)
    2.3.1 Quiescent operating point
    17(2)
    2.3.2 Geometric scalability
    19(4)
    2.3.3 Variability model
    23(1)
    2.3.4 Intrinsic voltage gain
    24(7)
    2.3.5 Speed: Unity gain frequency
    31(1)
    2.3.6 Noise
    32(4)
    2.3.7 Linearity and symmetry
    36(6)
    2.3.8 Symmetry
    42(2)
    2.4 RF metrics
    44(24)
    2.4.1 Two-port parameters
    44(2)
    2.4.2 The need for speed
    46(9)
    2.4.3 Non-quasi-static model
    55(3)
    2.4.4 Noise
    58(6)
    2.4.5 Linearity
    64(4)
    2.5 Conclusion
    68(3)
    References
    68(3)
    Chapter 3 Core model for FinFETs
    71(28)
    3.1 Core model for double-gate FinFETs
    72(8)
    3.2 Unified FinFET compact model
    80(19)
    Chapter 3 Appendix: Explicit surface potential model
    87(1)
    3A.1 Continuous starting function
    88(3)
    3A.2 Quartic modified iteration: Implementation and evaluation
    91(5)
    References
    96(3)
    Chapter 4 Channel current and real device effects
    99(28)
    4.1 Introduction
    99(1)
    4.2 Threshold voltage roll-off
    100(6)
    4.3 Subthreshold slope degradation
    106(1)
    4.4 Quantum mechanical vth correction
    107(2)
    4.5 Vertical-field mobility degradation
    109(1)
    4.6 Drain saturation voltage, vdsat
    109(5)
    4.6.1 Extrinsic case (RDSMOD = 1 and 2)
    110(1)
    4.6.2 Intrinsic case (RDSMOD = 0)
    111(3)
    4.7 Velocity saturation model
    114(1)
    4.8 Quantum mechanical effects
    115(4)
    4.8.1 Effective width model
    118(1)
    4.8.2 Effective oxide thickness/effective capacitance
    118(1)
    4.8.3 Charge centroid calculation for accumulation
    119(1)
    4.9 Lateral nonuniform doping model
    119(1)
    4.10 Body effect model for a bulk FinFET (BULKMOD = 1)
    119(1)
    4.11 Output resistance model
    120(3)
    4.11.1 Channel-length modulation
    121(1)
    4.11.2 Drain-induced barrier lowering
    122(1)
    4.12 Channel current
    123(4)
    References
    124(3)
    Chapter 5 Leakage currents
    127(16)
    5.1 Weak-inversion current
    129(1)
    5.2 Gate-induced source and drain leakages
    130(3)
    5.2.1 GIDL/GISL current formulation in BSIM-CMG
    132(1)
    5.3 Gate oxide tunneling
    133(7)
    5.3.1 Gate oxide tunneling formulation in BSIM-CMG
    134(1)
    5.3.2 Gate-to-body tunneling current in depletion/inversion
    135(1)
    5.3.3 Gate-to-body tunneling current in accumulation
    136(1)
    5.3.4 Gate-to-channel tunneling current in inversion
    137(1)
    5.3.5 Gate-to-source/drain tunneling current
    138(2)
    5.4 Impact ionization
    140(3)
    References
    141(2)
    Chapter 6 Charge, capacitance, and non-quasi-static effects
    143(14)
    6.1 Terminal charges
    144(2)
    6.1.1 Gate charge
    144(1)
    6.1.2 Drain charge
    145(1)
    6.1.3 Source charge
    146(1)
    6.2 Transcapacitances
    146(1)
    6.3 Non-quasi-static effects models
    147(10)
    6.3.1 Relaxation time approximation model
    149(2)
    6.3.2 Channel-induced gate resistance model
    151(1)
    6.3.3 Charge segmentation model
    152(3)
    References
    155(2)
    Chapter 7 Parasitic resistances and capacitances
    157(38)
    7.1 FinFET device structure and symbol definitions
    158(3)
    7.2 Modeling of geometry-dependent source/drain resistances in FinFETs
    161(8)
    7.2.1 Contact resistance
    162(2)
    7.2.2 Spreading resistance
    164(3)
    7.2.3 Extension resistance
    167(2)
    7.3 Parasitic resistance model verification
    169(9)
    7.3.1 TCAD simulation setup
    169(1)
    7.3.2 Device optimization
    170(2)
    7.3.3 Extraction of source and drain resistances
    172(4)
    7.3.4 Discussion
    176(2)
    7.4 Implementation considerations of the parasitic resistance model
    178(1)
    7.4.1 Physical parameters
    178(1)
    7.4.2 Resistance components
    178(1)
    7.5 Gate electrode resistance model
    179(1)
    7.6 FinFET parasitic capacitance models
    179(8)
    7.6.1 Connection of parasitic capacitance components
    179(2)
    7.6.2 Derivation of two-dimensional fringe capacitance
    181(6)
    7.7 Modeling of FinFET fringe capacitance in three dimensions: CGEOMOD = 2
    187(1)
    7.8 Parasitic capacitance model verification
    188(4)
    7.9 Summary
    192(3)
    References
    193(2)
    Chapter 8 Noise
    195(8)
    8.1 Introduction
    195(1)
    8.2 Thermal noise
    196(2)
    8.3 Flicker noise
    198(3)
    8.4 Other noise components
    201(1)
    8.5 Summary
    201(2)
    References
    201(2)
    Chapter 9 Junction diode I-V and C-V models
    203(14)
    9.1 Junction diode current model
    205(5)
    9.1.1 Reverse-bias additional leakage model
    208(2)
    9.2 Junction diode charge/capacitance model
    210(7)
    9.2.1 Reverse-bias model
    210(3)
    9.2.2 Forward-bias model
    213(3)
    References
    216(1)
    Chapter 10 Benchmark tests for compact models
    217(14)
    10.1 Asymptotic correctness
    218(1)
    10.2 Benchmark tests
    219(12)
    10.2.1 Tests for checking physical behavior in weak-inversion and strong-inversion regions
    219(3)
    10.2.2 Symmetry tests
    222(4)
    10.2.3 Reciprocity test for capacitances in a compact model
    226(1)
    10.2.4 Test for the self-heating effect model
    227(1)
    10.2.5 Tests for the thermal noise model
    227(1)
    References
    228(3)
    Chapter 11 BSIM-CMG model parameter extraction
    231(14)
    11.1 Parameter extraction background
    232(1)
    11.2 BSIM-CMG parameter extraction strategy
    233(9)
    11.3 Conclusion
    242(3)
    References
    242(3)
    Chapter 12 Temperature dependence
    245(16)
    12.1 Semiconductor properties
    246(1)
    12.1.1 Band gap temperature dependence
    246(1)
    12.1.2 Temperature dependence of Nc, vbi, and Φb
    246(1)
    12.1.3 Temperature dependence of the intrinsic carrier concentration
    247(1)
    12.2 Temperature dependence of the threshold voltage
    247(2)
    12.2.1 Temperature dependence of drain-induced barrier lowering
    248(1)
    12.2.2 Temperature dependence of the body effect
    248(1)
    12.2.3 Subthreshold swing
    248(1)
    12.3 Temperature dependence of mobility
    249(1)
    12.4 Temperature dependence of velocity saturation
    249(1)
    12.4.1 Temperature dependence of the nonsaturation effect
    250(1)
    12.5 Temperature dependence of leakage currents
    250(1)
    12.5.1 Gate current
    250(1)
    12.5.2 Gate-induced drain/source leakage
    250(1)
    12.5.3 Impact ionization
    251(1)
    12.6 Temperature dependence of parasitic source/drain resistances
    251(1)
    12.7 Temperature dependence of source/drain diode characteristics
    252(4)
    12.7.1 Direct current model
    252(2)
    12.7.2 Capacitance
    254(1)
    12.7.3 Trap-assisted tunneling current
    254(2)
    12.8 Self-heating effect
    256(1)
    12.9 Validation range
    257(1)
    12.10 Model validation on measured data
    257(4)
    References
    260(1)
    Appendix 261(26)
    Index 287
    Yogesh Singh Chauhan is a Chair Professor in the Department of Electrical Engineering at the Indian Institute of Technology Kanpur, India. He is the developer of several industry standard models: ASM-HEMT, BSIM-BULK (formerly BSIM6), BSIM-CMG, BSIM-IMG, BSIM4 and BSIM-SOI models. His research group is involved in developing compact models for GaN transistors, FinFET, nanosheet/gate-all-around FETs, FDSOI transistors, negative capacitance FETs and 2D FETs. His research interests are RF characterization, modeling, and simulation of semiconductor devices.

    Darsen D. Lu was one of the key contributors of the industry standard FinFET compact model, BSIM-CMG, and thin-body SOI compact model, BSIM-IMG. He received his B.Sc. in electrical engineering in 2005, from National Tsing Hua University, Hsinchu, Taiwan, and his M.Sc. and Ph.D. in electrical engineering from the University of California, Berkeley, in 2007 and 2011 respectively. From 2011 to 2015, he has been a research scientist at the IBM Thomas J. Watson Research Center, Yorktown Heights, New York. He is currently a Macronix Endowed Chair (Associate) Professor at National Cheng Kung University, Tainan, Taiwan. His current research focuses on the fabrication and modeling of ferroelectric memory (ferroelectric FinFET) devices, cryogenic CMOS modeling for high-performance and quantum computation, and the design of AI/neuromorphic circuits and systems.

    Sriramkumar Venugopalan received his M.Sc. and Ph.D. in electrical engineering at the University of California, Berkeley and his B.Sc. from the Indian Institute of Technology (IIT), Kanpur. While pursuing his doctoral degree he contributed to research and development of multi-gate transistor compact SPICE models. He lead the industry standardization effort for BSIM-CMG model representing the BSIM Group at the Compact Model Council. He was the recipient of Outstanding Researcher Award from TSMC for his contributions to multi-gate SPICE models. He has authored and co- authored more than 30 research papers in the area of semiconductor device SPICE models and RF integrated circuit design. Dr. Venugopalan is currently leading wireless system design group at Skyworks Solutions, Inc. Prior to that he co-founded and was the CEO of RF Pixels, a 5G mmWave Radio startup which was later acquired by Skyworks. Dr. Venugopalan was also with Samsung Electronics pursuing RF integrated circuit design in advanced semiconductor technology nodes.

    Sourabh Khandelwal is an Associate Professor at Macquarie University. He is the lead author of two industry standard compact models: ASM-HEMT for GaN RF and power technology, and ASM-ESD for silicon ESD applications. He has also co-authored BSIM-CMG, BSIM-IMG and BSIM6 compact models during his tenure at the BSIM group at the University of California Berkeley. Dr Khandelwal has published 3 books and over 150 research papers. He regularly serves as consultant to multi-national semiconductor companies.

    Juan Pablo Duarte Sepúlveda obtained his Ph.D. at the University of California, Berkeley in 2018. He received his B.Sc. in 2010 and his M.Sc. in 2012, both in electrical engineering from the Korea Advanced Institute of Science and Technology (KAIST). He held a position as a lecturer at the Universidad Tecnica Federico Santa Maria, Valparaiso, Chile, in 2012. He has authored many papers on nanoscale semiconductor device modeling and characterization. He received the Best Student Paper Award at the 2013 International Conference on Simulation of Semiconductor Processes and Devices (SISPAD) for the paper: Unified FinFET Compact Model: Modelling Trapezoidal Triple-Gate FinFETs.

    Navid Paydavosi is a seasoned hardware engineer with a decade of experience in advanced Si process technology and GPU and memory subsystem optimization. He excels in optimizing PPAC for complex SoC systems. He holds a Ph.D. in Electrical Engineering from the University of Alberta and completed a postdoctoral scholarship at UC Berkeley under supervision of Prof. Chenming Hu, contributing to the development of FinFET and SOI SPICE compact models. Navid began his Intel career in 2014 as a Logic Technology Development Device Engineer, where he contributed to key advancements in Intel 4 and Intel 3 technology nodes. He then served as a GPU Micro-Arch Power Optimization Engineer, leading innovations such as a novel Glitch minimization algorithm. As a NAND Flash Power and Performance Optimization Engineer, Navid significantly improved the power and performance of Intel's 3D NAND Flash products. Currently, he is a Senior Staff Intel Foundry Device Engineer, customizing the Intel 3 technology node for customers. Navid's expertise spans device physics, semiconductor manufacturing, and power optimization. His goal is to deliver world-class AI hardware solutions for Data Center and Edge computing environments.

    Ali M. Niknejad received his B.Sc in electrical engineering from the University of California, Los Angeles, in 1994, and his M.Sc. and Ph.D., also in electrical engineer- ing, from the University of California, Berkeley, in 1997 and 2000 respectively. He is currently a professor in the EECS department at UC Berkeley and Faculty Director of the Berkeley Wireless Research Center (BWRC) Group. He is also the Associate Director of the Center for Ubiquitous Connectivity (CUbiC) and also served as the Associate Director for the Center for Converged TeraHertz Communications and Sensing (ComSenTer). Prof. Niknejad received the 2020 SIA/SRC University Research Award, recognized for noteworthy achievements that have advanced analog, RF, and mm-wave circuit design and modeling, which serve as the foundation of 5G+ technologies.” Professor Niknejad was the recipient of the 2012 ASEE Frederick Emmons Terman Award for his work and textbook on electromagnetics and RF integrated circuits. He has co-authored over 400 conference and journal publications in the field of integrated circuits and device compact modeling. His focus areas of research include analog, RF, mixed-signal, mm-wave circuits, device physics and compact modeling, and numerical techniques in electromagnetics.

    Chenming Hu is TSMC Distinguished Chair Professor Emeritus at the University of California Berkeley, United States. He was the Chief Technology Officer of TSMC. He received the US Presidential Medal of Technology and Innovation from Pres. Barack Obama for developing the first 3D thin-body transistor FinFET, MOSFET reliability models and leading the development of BSIM industry standard transistor model that is used in designing most of the integrated circuits in the world. He is a member of the US Academy of Engineering, the Chinese Academy of Science, and Academia Sinica. He received the highest honor of IEEE, the IEEE Medal of Honor, and its Andrew Grove Award, Solid Circuits Award, and the Nishizawa Medal. He also received the Taiwan Presidential Science Prize and UC Berkeleys highest honor for teaching the Berkeley Distinguished Teaching Award.