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20222026
most citedExploring high thermal conductivity polymers via interpretable machine learning with physical descriptors

71 citations · 94 across the 4 of their papers we have counts for

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cond-mat.mes-hall2022★ 23 cited

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,…