A fourier neural operator-based subband-BTE solver for sub-10 nm ultra-scaled devices

To reliably capture quantum and scattering phenomenon, it has been a common practice to design the ultra-scaled gate-all-around transistors (GAAFET) by solving the subband Boltzmann transport equation (BTE), e.g., in synopsys sentaurus QTX (S-QTX). However, it is extremely computationally intensive to solve the subband-BTE using conventional numerical methods. For instance, it may take several hours, or even days, to obtain one current-voltage (IV) curve, hindering efficient design and development of sub-10 nm devices. To mitigate this problem, here we propose a fast subband-BTE solver using the Fourier neural operator (FNO), which can significantly accelerate the convergence speed and can achieve acceleration by more than one order of magnitude without sacrificing accuracy, compared to state-of-the-art numerical methods as implemented in the mainstream S-QTX. The proposed method might be useful to shorten turnaround time during design-technology co-optimization (DTCO) of sub-10 nm advanced technology nodes.

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Publication Details

Journal
Scientific Reports
Published
2026-07-24
DOI
https://doi.org/10.1038/s41598-026-62360-2
Primary Topic
Advancements in Semiconductor Devices and Circuit Design
Type
article
Field-Weighted Citation Impact
0.00

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article

A fourier neural operator-based subband-BTE solver for sub-10 nm ultra-scaled devices

J Liu, Xi Ding, H Wang, Hailong Zhang et al.
Scientific Reports
Advancements in Semiconductor Devices and Circuit Design
article

A fourier neural operator-based subband-BTE solver for sub-10 nm ultra-scaled devices

J Liu, Xi Ding, H Wang, Hailong Zhang, Hao Ruan, Youyuan Tao, Fei Liu, Zhehan Pang
article en

Abstract

To reliably capture quantum and scattering phenomenon, it has been a common practice to design the ultra-scaled gate-all-around transistors (GAAFET) by solving the subband Boltzmann transport equation (BTE), e.g., in synopsys sentaurus QTX (S-QTX). However, it is extremely computationally intensive to solve the subband-BTE using conventional numerical methods. For instance, it may take several hours, or even days, to obtain one current-voltage (IV) curve, hindering efficient design and development of sub-10 nm devices. To mitigate this problem, here we propose a fast subband-BTE solver using the Fourier neural operator (FNO), which can significantly accelerate the convergence speed and can achieve acceleration by more than one order of magnitude without sacrificing accuracy, compared to state-of-the-art numerical methods as implemented in the mainstream S-QTX. The proposed method might be useful to shorten turnaround time during design-technology co-optimization (DTCO) of sub-10 nm advanced technology nodes.

Scientific Reports
Hunan University (CN), Changsha University (CN), Peking University (CN), Institute for History of Natural Sciences (CN), Advanced Energy Materials (United States) (US), Institute of Applied Physics and Computational Mathematics (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 15%
Advancements in Semiconductor Devices and Circuit Design
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