Our work "Machine-learned atomic cluster expansion potentials for fast and quantum-accurate thermal simulations of wurtzite AlN" was published on Journal of Applied Physics
Our work "Machine-learned atomic cluster expansion potentials for fast and quantum-accurate thermal simulations of wurtzite AlN" was published on Journal of Applied Physics: G. Yang, Y.B. Liu, L. Yang, B.Y. Cao. Machine-learned atomic cluster expansion potentials for fast and quantum-accurate thermal simulations of wurtzite AlN. Journal of Applied Physics, 2024, 135(8): 085105. The paper was selected as Editor's Pick, and we were also invited to contribute a tutorial article in terms of machine learning potential for thermal transport.
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