arXiv subjects

Yihan Nie

Publications and source records attributed to Yihan Nie.

4 recordsLinked to original sources

arXiv2026

UniMatSim: A High-Throughput Materials Simulation Automation Framework Based on Universal Machine Learning Potentials

Universal machine learning interatomic potentials (UMLIPs) offer accuracy close to first-principles calculations at a fraction of the cost, showing significant potential for large-scale material simulations. However, the fragmented UMLIPs ecosystem lacks unified interface standards and integration frameworks, hindering their automated deployment in high-throughput workflows. To address this, we present UniMatSim, a modular Python framework. It systematically integrates various UMLIPs (e.g., CHGNet, M3GNet, MACE) and automates workflows from structural optimization to stability verification. The framework enables seamless model switching via abstracted interfaces, incorporates task orchestration, and provides standardized modules for key properties (elasticity, phonons, molecular dynamics), including automated handling for low-dimensional materials. As a test case, using the 2D Lieb lattice system, we constructed a multi-stage high-throughput screening workflow covering structural optimization, elastic stability, and phonon spectrum calculations. Starting from 1,176 candidate compositions, a four-model consensus pipeline yields 393 stable structures. These are refined by magnetic-state screening and DFT band-structure calculations to 59 Lieb-lattice candidates with staggered-magnetic-band characteristics. Results show UniMatSim significantly improves computational efficiency and reproducibility, providing a reliable infrastructure for data-driven materials discovery and design.

cond-mat.mtrl-sci↗

arXiv2025

Ferroelectric Domains and Evolution Dynamics in Twisted CuInP2S6 Bilayers

Polar domains and their manipulation-particularly the creation and dynamic control-have garnered significant attention, owing to their rich physics and promising applications in digital memory devices. In this work, using density functional theory (DFT) and deep learning molecular dynamics (DLMD) simulations, we demonstrate that polar domains can be created and manipulated in twisted bilayers of ferroelectric CuInP2S6, as a result of interfacial ferroelectric (antiferroelectric) coupling in AA (AB) stacked region. Unlike the topological polar vortex and skyrmions observed in superlattices of (PbTiO3)n/(SrTiO3)n and sliding bilayers of BN and MoS2, the underlying mechanism of polar domain formation in this system arises from stacking-dependent energy barriers for ferroelectric switching and variations in switching speeds under thermal perturbations. Notably, the thermal stability and polarization lifetimes are highly sensitive to twist angles and temperature, and can be further manipulated by external electric fields and strain. Through multi-scale simulations, our study provides a novel approach to exploring how twist angles influence domain evolution and underscores the potential for controlling local polarization in ferroelectric materials via rotational manipulation.

cond-mat.mtrl-sci↗

arXiv2023

Ferroelectric Domain and Switching Dynamics in Curved In2Se3: First Principle and Deep Learning Molecular Dynamics Simulations

Complex strain status can exist in 2D materials during their synthesis process, resulting in significant impacts on the physical and chemical properties. Despite their prevalence in experiments, their influence on the material properties and the corresponding mechanism are often understudied due to the lack of effective simulation methods. In this work, we investigated the effects of bending, rippling, and bubbling on the ferroelectric domains in In2Se3 monolayer by density functional theory (DFT) and deep learning molecular dynamics (DLMD) simulations. The analysis of the tube model shows that bending deformation imparts asymmetry into the system, and the polarization direction tends to orient towards the tensile side, which has a lower energy state than the opposite polarization direction. The energy barrier for polarization switching can be reduced by compressive strain according DFT results. The dynamics of the polarization switching is investigated by the DLMD simulations. The influence of curvature and temperature on the switching time follows the Arrhenius-style function. For the complex strain status in the rippling and bubbling model, the lifetime of the local transient polarization is analyzed by the autocorrelation function, and the size of the stable polarization domain is identified. Local curvature and temperature can influence the local polarization dynamics following the proposed Arrhenius-style equation. Through cross-scale simulations, this study demonstrates the capability of deep-learning potentials in simulating polarization for ferroelectric materials. It further reveals the potential to manipulate local polarization in ferroelectric materials through strain engineering.

cond-mat.mtrl-sci↗

arXiv2019

Thermal Transport in 3D Nanostructures

This work summarizes recent progress on the thermal transport properties of three-dimensional (3D) nanostructures, with an emphasis on experimental results. Depending on the applications, different 3D nanostructures can be prepared or designed to either achieve a low thermal conductivity for thermal insulation or thermoelectric devices, or a high thermal conductivity for thermal interface materials used in the continuing miniaturization of electronics. A broad range of 3D nanostructures have been discussed, ranging from colloidal crystals/assemblies, array structures, holey structures, hierarchical structures, 3D nanostructured fillers for metal matrix composites and polymer composites. Different factors that impact the thermal conductivity of these 3D structures are compared and analyzed. This work provides an overall understanding of the thermal transport properties of various 3D nanostructures, which will shed light on the thermal management at nanoscale.

physics.app-ph↗