Semiconductor nanotechnologies are among the most consequential ones for almost every aspect of modern society. Conventionally, the design towards desired technological specifications is by no means trivial. It comprises interactions of simulations and experiments that often translate into lengthy periods and high costs. While ML has been successfully employed to tackle problems in numerous areas, few studies have been carried to investigate how to use ML to create semiconductor nanotechnologies comprising sophisticated structures. In this project, the PIs would utilize ML to design semiconductor nanotechnologies. Specifically, the structural variables will be inferred by regression models, genetic algorithms, and other generative models. To prove its effectiveness, experiments would be carried out using advanced semiconductor equipment in the PI lab and Core Labs.
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