Search results for “nano-device modeling”

Published Subscription Review Article 20 Mar 2026

Machine Learning Assisted Optimization of Nanoscale MOSFET Parameters Using TCAD Simulation

By Amit Pandhare, Aditya Kumbhar, Vaibhav Godase

Abstract: This paper presents a machine learning (ML) assisted framework for the multi-objective optimization of nanoscale bulk n-channel metal-oxide-semiconductor field-effect transistors (nMOSFETs) with a 10 nm physical gate length, high-k HfO₂ gate dielectric, and TiN metal gate. Technology computer-aided design (TCAD) simulations employing drift-diffusion transport, Shockley-Read-Hall recombination, Lombardi mobility degradation, and density- gradient quantum correction models are used to generate a parametric dataset of 2,400 device configurations spanning gate length (L₝), …

Published in Journal of Microelectronics and Solid State Devices · Vol. 13, Issue 1, 2026 · pp. 10–19 Read article

Published Ahead of print Open access Article 10 May 2023

Comparative Study of Drain Current of Symmetric and Asymmetric DG-MOSFET with Simulation in Silvaco TCAD Software

By Abhishek Saha, Vedatrayee Chakraborty

Abstract: One of the most attractive and promising devices for the nanoscale devices is the double gate MOSFET. The double gate MOSFET can control the Si channel very efficiently and it chooses a very small width of the Si channel. It controls the Si channel by applying gate contact to either side of the channel. The idea of controlling the S channel in such a way reduces the short channel effects …

Published in Journal of Semiconductor Devices and Circuits Read article

Published Subscription Original Research Special issue 13 Feb 2026

Implement Explainable Machine Learning to Improve Conductivity in Polymer-CNT Nanocomposites: Supporting Adaptive, Flexible, and Long-Lasting IoT Wrap-Around Electronics Applications

By M. Muthupandi, M. Sukanya, C.L. Annapoorani, W. Nancy, Jinugu Ranjith, Murali Krishna Atmakuri, D. Marichamy

Abstract: The rapid growth of Internet of Things (IoT) technologies requires electronic components that are adaptable, lightweight, and durable, and that can continue to function well in diverse contexts and circumstances. Polymer–carbon nanotube (CNT) nanocomposites have become interesting choices for these kinds of uses because they are more flexible, conduct electricity better, and can be made to fit specific needs. However, improving conductivity in these heterogeneous systems remains a major challenge …

Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 238–254 Read article

Published Subscription Original Research 15 May 2025

Comparative Analysis of 3D-Printed and Molded Shape-Stabilized Phase Change Composites

By Deepak Kumar Yadav, Pushpendra Kumar Singh Rathore, Rajeev Kumar Singh, Arvind Kumar Gupta, Basant Singh Sikarwar

Abstract: Thermal energy storage (TES) has become essential for efficiently storing and utilizing thermal energy across applications like industrial heating, power plants, batteries, medical devices, food preservation, and aerospace technology. Because of their high energy density, affordability, and environmental friendliness, phase change materials, or PCMs, are employed extensively. However, challenges like poor thermal conductivity and leakage limit their performance. To address these issues, 3D printing has emerged as a powerful tool …

Published in Journal of Polymer & Composites · Vol. 13, Issue 3, 2025 · pp. 184–192 Read article