5 papers
Efficient small-cell sampling for machine-learning potentials of multi-principal element alloys
Yan Liu, Jiantao Wang, Hongkun Deng +3
Multi-principal element alloys (MPEAs) exhibit exceptional properties but face significant challenges in developing accurate machine-learning potentials (MLPs) due to their vast co…
Atomistic mechanisms of phase transitions in all-temperature barocaloric material KPF
Jiantao Wang, Yi-Chi Zhang, Yan Liu +6
Conventional barocaloric materials typically exhibit limited operating temperature ranges. In contrast, KPF has recently been reported to achieve an exceptional all-temperature…
Diverse polymorphs and phase transitions in van der Waals InSe
Mingfeng Liu, Jiantao Wang, Peitao Liu +4
Van der Waals InSe has garnered significant attention due to its unique properties and wide applications associated with its rich polymorphs and polymorphic phase transitio…
Quantum Delocalization Enables Water Dissociation on Ru(0001)
Yu Cao, Jiantao Wang, Mingfeng Liu +7
We revisit the long-standing question of whether water molecules dissociate on the Ru(0001) surface through nanosecond-scale path-integral molecular dynamics simulations on a sizab…
Efficient moment tensor machine-learning interatomic potential for accurate description of defects in Ni-Al Alloys
Jiantao Wang, Peitao Liu, Heyu Zhu +5
Combining the efficiency of semi-empirical potentials with the accuracy of quantum mechanical methods, machine-learning interatomic potentials (MLIPs) have significantly advanced a…