Dissertation Machine Learning in Materials Science -- A case study in Carbon Nanotube field effect transistors

Shulin Tan

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arXiv · 2501.14813

Dissertation Machine Learning in Materials Science -- A case study in Carbon Nanotube field effect transistors

Shulin Tan

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Abstract

In this thesis, I explored the use of several machine learning techniques, including neural networks, simulation-based inference, and generative flow networks, on predicting CNTFETs performance, probing the conductivity properties of CNT network, and generating CNTFETs processing information for target performance.

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physics.app-ph cond-mat.mes-hall cs.LG physics.data-an

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Shulin Tan. 2025-01-19. Dissertation Machine Learning in Materials Science -- A case study in Carbon Nanotube field effect transistors. https://arxiv.org/abs/2501.14813

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