8 papers
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…
A universal augmentation framework for long-range electrostatics in machine learning interatomic potentials
Dongjin Kim, Xiaoyu Wang, Peichen Zhong +3
Most current machine learning interatomic potentials (MLIPs) rely on short-range approximations, without explicit treatment of long-range electrostatics. To address this, we recent…
Foundation Models for Atomistic Simulation of Chemistry and Materials
Eric C. -Y. Yuan, Yunsheng Liu, Junmin Chen +11
Given the power of large language and large vision models, it is of profound and fundamental interest to ask if a foundational model based on data and parameter scaling laws and pr…