8 citations · 8 across the 6 of their papers we have counts for
4 papers · 1 filter
MatterSim-MT: A multi-task foundation model for in silico materials characterization
Han Yang, Xixian Liu, Chenxi Hu +25
Accurate property characterization is a major bottleneck in materials design. While first-principles methods and task-specific machine-learning models have driven important progres…
KappaFormer: Physics-aware Transformer for lattice thermal conductivity via cross-domain transfer learning
Mengfan Wu, Junfu Tan, Yu Zhu +1
Machine learning has been widely used for predicting material properties. However, efficient prediction of lattice thermal conductivity () remains a long-standing cha…
Temperature dependent ferroelectricity in strained KTaO3 with machine learned force field
Yu Zhu, Luigi Ranalli, Taikang Chen +2
Ferroelectric materials are a class of dielectrics that exhibit spontaneous polarization which can be reversed under an external electric field. The emergence of ferroelectric orde…
Probing the Limit of Heat Transfer in Inorganic Crystals with Deep Learning
Jielan Li, Zekun Chen, Qian Wang +21
Heat transfer is a fundamental property of matter. Research spanning decades has attempted to discover materials with exceptional thermal conductivity, yet the upper limit remains…