3 papers
cond-mat.mtrl-sci2024
High-throughput discovery of metal oxides with high thermoelectric performance via interpretable feature engineering on small data
Shengluo Ma, Yongchao Rao, Xiang Huang +1
In this work, we have proposed a data-driven screening framework combining the interpretable machine learning with high-throughput calculations to identify a series of metal oxides…
cond-mat.soft2024
Tutorial: AI-assisted exploration and active design of polymers with high intrinsic thermal conductivity
Xiang Huang, Shenghong Ju
Designing polymers with high intrinsic thermal conductivity (TC) is critically important for the thermal management of organic electronics and photonics. However, this is a challen…
cond-mat.soft2024
AI-assisted inverse design of sequence-ordered high intrinsic thermal conductivity polymers
Xiang Huang, C. Y. Zhao, Hong Wang +1
Artificial intelligence (AI) promotes the polymer design paradigm from a traditional trial-and-error approach to a data-driven style. Achieving high thermal conductivity (TC) for i…