Multi-objective optimization and inverse design of complementary field-effect transistor using combined approach of machine learning and non-dominated sorting genetic algorithms for next-generation semiconductor devices

Author:

Kim Sangpill,Min Seong-Ji,Jung Seung-Geun,Yu Hyun-YongORCID

Funder

Samsung Group

National Research Foundation of Korea

IC Design Education Center

Ministry of Science, ICT and Future Planning

Publisher

Elsevier BV

Reference49 articles.

1. A framework for data-driven analysis of materials under uncertainty: countering the curse of dimensionality;Bessa;Comput. Methods Appl. Mech. Eng.,2017

2. Pymoo: multi-objective optimization in Python;Blank;IEEE Access,2020

3. Application of long short-term memory modeling technique to predict process variation effects of stacked gate-all-around Si nanosheet complementary-field effect transistors;Butola;Comput. Electr. Eng.,2023

4. First demonstration of CMOS inverter and 6T-SRAM based on GAA CFETs structure for 3D-IC applications;Chang;Technical Digest - International Electron Devices Meeting, IEDM 2019-December,2019

5. Complementary-FET (CFET) standard cell synthesis framework for design and system technology Co-optimization using SMT;Cheng;IEEE Trans Very Large Scale Integr VLSI Syst,2021

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