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