5 papers · 1 filter
Interfacial-melt stability as a thermodynamic prerequisite for solid-state synthesis
Zihan Zhang, Mengyi Chen, Qianxiao Li +1
Computational materials discovery commonly ranks candidate materials by their thermodynamic stability on the formation energy convex hull, yet many predicted-stable phases resist s…
Differentiable hybrid force fields support scalable autonomous electrolyte discovery
Xintian Wang, Junmin Chen, Zhuoying Zhu +1
Autonomous electrolyte discovery demands a computational engine that satisfies a critical trilemma: it must be fast enough for high-throughput screening, accurate enough for quanti…
Atomistic Modeling of Chemical Disorder in Materials: Bridging Classical Methods and AI-Assisted Approaches
Jiayu Peng, Peichen Zhong
Chemical disorder, originating from the mixed occupation of crystallographic sites by multiple elements, is widespread in alloys, ceramics, and compositionally complex materials, w…
Intrinsic structure of relaxor ferroelectrics from first principles
Xinyu Xu, Kehan Cai, Yubai Shi +2
We develop FIRE-Swap, a first-principles framework for sampling intrinsic compositional structures in complex perovskites with machine-learning interatomic potentials (MLIPs). Usin…
Machine learning interatomic potential can infer electrical response
Peichen Zhong, Dongjin Kim, Daniel S. King +1
Modeling the response of material and chemical systems to electric fields remains a longstanding challenge. Machine learning interatomic potentials (MLIPs) offer an efficient and s…