Machine Learning for Semiconductor Materials

Neeraj Gupta, Rashmi Gupta, Rekha Yadav , Sandeep Dhariwal

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Hardback

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English

CRC Press
22 August 2025

Materials science; Electrical engineering; Electronic devices & materials; Automatic control engineering; Machine learning

Series: Emerging Materials and Technologies

Machine Learning for Semiconductor Materials studies recent techniques and methods of machine learning to mitigate the use of technology computer-aided design (TCAD). It provides various algorithms of machine learning, such as regression, decision tree, support vector machine, K-means clustering and so forth. This book also highlights semiconductor materials and their uses in multi-gate devices and the analog and radio-frequency (RF) behaviours of semiconductor devices with different materials.

Features:

Focuses on semiconductor materials and the use of machine learning to facilitate understanding and decision-making Covers RF and noise analysis to formulate the frequency behaviour of semiconductor devices at high frequency Explores pertinent biomolecule detection methods Reviews recent methods in the field of machine learning for semiconductor materials with real-life applications Examines the limitations of existing semiconductor materials and steps to overcome the limitations of existing TCAD software

This book is aimed at researchers and graduate students in semiconductor materials, machine learning and electrical engineering.

Edited by: Neeraj Gupta, Rashmi Gupta, Rekha Yadav, Sandeep Dhariwal, Rajkumar Sarma
Imprint: CRC Press
Country of Publication: United Kingdom
Dimensions: Height: 234mm, Width: 156mm,
Weight: 453g
ISBN: 9781032796888
ISBN 10: 103279688X
Series: Emerging Materials and Technologies
Pages: 208
Publication Date: 22 August 2025
Audience: College/higher education , Professional and scholarly , Primary , Undergraduate
Format: Hardback
Publisher's Status: Forthcoming

Neeraj Gupta is an Associate Professor at Amity University Haryana with over 16 years of teaching experience. His expertise includes VLSI design, low-power and analog design, AI and embedded systems. He has published 40+ papers, two book chapters, one book and 12 patents and has received the Best Researcher and Best Teacher Award (2024). Rashmi Gupta is an Assistant Professor at Amity University Haryana with 13+ years of experience. Her research interests include AI, software engineering and IoT. She has authored 20+ papers, two book chapters, one book and five patents. Rekha Yadav is an Assistant Professor at DCRUST, Murthal. She specializes in semiconductor device modeling and VLSI design, with 15 years of experience, over 30 publications and four book chapters. Sandeep Dhariwal is an Associate Professor at Alliance University, Bengaluru. With 14+ years of experience, he focuses on low-power CMOS and semiconductor modeling. He has published 40+ articles, three books and holds three patents. Rajkumar Sarma is a Postdoctoral Researcher at the University of Limerick, Ireland. With 11+ years of experience, his research spans digital VLSI, FPGA prototyping and quantum architectures. He has 25+ publications, 15+ patents and two books.