71 citations · 145 across the 5 of their papers we have counts for
5 papers
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…
Data-driven design of multilayer hyperbolic metamaterials for near-field thermal radiative modulator with high modulation contrast
Tuwei Liao, C. Y. Zhao, Hong Wang +1
The thermal modulator based on the near-field radiative heat transfer has wide applications in thermoelectric diodes, thermoelectric transistors, and thermal storage. However, the…
Exploring high thermal conductivity polymers via interpretable machine learning with physical descriptors
Xiang Huang, Shengluo Ma, C. Y. Zhao +2
The efficient and economical exploitation of polymers with high thermal conductivity is essential to solve the issue of heat dissipation in organic devices. Currently, the experime…
Enhancing thermoelectric properties of isotope graphene nanoribbons via machine learning guided manipulation of disordered antidots and interfaces
Xiang Huang, Shengluo Ma, Haidong Wang +4
Structural manipulation at the nanoscale breaks the intrinsic correlations among different energy carrier transport properties, achieving high thermoelectric performance. However,…
Designing thermal radiation metamaterials via hybrid adversarial autoencoder and Bayesian optimization
Dezhao Zhu, Jiang Guo, Gang Yu +3
Designing thermal radiation metamaterials is challenging especially for problems with high degrees of freedom and complex objective. In this letter, we have developed a hybrid mate…