Intelligent Engineering of Advanced Surrounding Gate Tunnel FETs: From Core Device Physics to Machine Learning-Assisted Many-Objective Evolutionary Optimization - Softcover

Inhaltsangabe

This book explores the design and optimization of advanced Surrounding Gate Tunnel Field-Effect Transistors (SGTFETs) for future low-power semiconductor technologies. It presents analytical models and TCAD-based investigations of conventional SGTFETs, Triple Material SGTFETs (TMSGTFETs), and III-V High-k SGTFETs, with emphasis on improving switching performance, reducing leakage, and enhancing energy efficiency. The work integrates evolutionary multiobjective optimization using NSGA-III and machine-learning-assisted Pareto Active Learning to identify optimal trade-offs among delay, dynamic power, on-off current ratio, switching speed, and device variability. By combining device physics, computational intelligence, and optimization techniques, the book offers a scalable framework for the development of high-performance nanoscale transistor architectures suitable for next-generation integrated circuits and emerging nanoelectronic applications.

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