Cover Image

Anisotropic Crystallization Kinetics and Interfacial Dynamics of Phase-Change Material Sb$_2$S$_3$ from Machine Learning Force Field Simulations

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Chakraborty, Souvik, Li, Wen-Qing, Liu, Yun
Format:	Preprint
Published:	2026
Subjects:	Materials Science Disordered Systems and Neural Networks
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Unraveling the Crystallization Kinetics of the Ge$_2$Sb$_2$Te$_5$ Phase Change Compound with a Machine-Learned Interatomic Potential
by: Kheir, Omar Abou El, et al.
Published: (2023)

Tunable Electronic Interactions and Weak Antilocalization in Bulk Ge$_2$Sb$_2$Te$_{5-5x}$Se$_{5x}$ Phase Change Materials
by: Mazzucca, Nicholas, et al.
Published: (2025)

Field-Induced Ferroelectric Phase Transition Dynamics in PMN-PT compositions near the Morphotropic Phase Boundary
by: Chanan, Shivjeet, et al.
Published: (2026)

X-ray photo-induced atomic motion in Phase Change Materials and conventional covalent chalcogenide glasses
by: Festi, Irene, et al.
Published: (2026)

Deep Learning-Based Quantum Transport Simulations in Two-Dimensional Materials
by: Zou, Jijie, et al.
Published: (2025)

FerroAI: A Deep Learning Model for Predicting Phase Diagrams of Ferroelectric Materials
by: Zhang, Chenbo, et al.
Published: (2025)

Neural Network Kinetics for Exploring Diffusion Multiplicity and Chemical Ordering in Compositionally Complex Materials
by: Xing, Bin, et al.
Published: (2023)

Mechanistic Insights into the Oxygen Evolution Reaction on Nickel-Doped Barium Titanate via Machine Learning-Accelerated Simulations
by: Boonpalit, Kajjana, et al.
Published: (2024)

Rapid Assessment of Stable Crystal Structures in Single Phase High Entropy Alloys Via Graph Neural Network Based Surrogate Modelling
by: Beaver, Nicholas, et al.
Published: (2024)

On the origin of in-gap states in amorphous Ge$_2$Sb$_2$Te$_5$
by: Kheir, Omar Abou El, et al.
Published: (2026)

KAN-Enhanced Contrastive Learning Accelerating Crystal Structure Identification from XRD Patterns
by: Xu, Chenlei, et al.
Published: (2025)

Amorphization-induced topological and insulator-metal transitions in bidimensional Bi$_x$Sb$_{1-x}$ alloys
by: Uría-Álvarez, A. J., et al.
Published: (2024)

Reexamining Machine Learning Models on Predicting Thermoelectric Properties
by: Ma, Chung T., et al.
Published: (2025)

High-Throughput GW Calculations via Machine Learning
by: Abdelghany, Ragab. A., et al.
Published: (2025)

Force field optimization by end-to-end differentiable atomistic simulation
by: Gangan, Abhijeet S., et al.
Published: (2024)

Calculating the Stability of Different Surfaces of GaAsxP1-x Mixed-Crystals using the Virtual Crystal Approximation
by: Karmo, Marsel, et al.
Published: (2023)

Machine-Learning Recognition of Dzyaloshinskii-Moriya Interaction from Magnetometry
by: Fugetta, Bradley J., et al.
Published: (2023)

Crystal-like thermal transport in amorphous carbon
by: Moon, Jaeyun, et al.
Published: (2024)

High-efficiency computational methodologies for electronic properties and structural characterization of Ge-Sb-Te based phase change materials
by: Xie, Shanzhong, et al.
Published: (2025)

Specific Heat Anomalies and Local Symmetry Breaking in (Anti-)Fluorite Materials: A Machine Learning Molecular Dynamics Study
by: Kobayashi, Keita, et al.
Published: (2024)

Corner-Sharing PS$_4$-BS$_4$ Modes Facilitate Fast Ion Conduction in Lithium Thioborophosphate Iodide Glassy Solid Electrolytes
by: An, Yun
Published: (2025)

Interpretable Machine Learning of Nanoparticle Stability through Topological Layer Embeddings
by: Hawthorne, Felipe, et al.
Published: (2026)

Developing a Neural Network Machine Learning Interatomic Potential for Molecular Dynamics Simulations of La-Si-P Systems
by: Tang, Ling, et al.
Published: (2025)

On phase separation and crystallization of Ge-rich GeSbTe alloys from atomistic simulations with a machine learning interatomic potential
by: Kheir, Omar Abou El, et al.
Published: (2026)

Large Scale Raman Spectrum Calculations in Defective 2D Materials using Deep Learning
by: Malenfant-Thuot, Olivier, et al.
Published: (2024)

Machine Learning Potential Powered Insights into the Mechanical Stability of Amorphous Li-Si Alloys
by: Wei, Zixiong, et al.
Published: (2024)

Multi-Output Convolutional Neural Network for Improved Parameter Extraction in Time-Resolved Electrostatic Force Microscopy Data
by: Breshears, Madeleine D., et al.
Published: (2025)

Performance Assessment of Universal Machine Learning Interatomic Potentials: Challenges and Directions for Materials' Surfaces
by: Focassio, Bruno, et al.
Published: (2024)

Is the Future of Materials Amorphous? Challenges and Opportunities in Simulations of Amorphous Materials
by: Madanchi, Ata, et al.
Published: (2024)

Hexatic Phase in Covalent Two-Dimensional Silver Iodide
by: Bui, Thuy An, et al.
Published: (2025)

Machine learning the local electronic density of states
by: Aryanpour, A., et al.
Published: (2025)

Learning Atoms from Crystal Structure
by: Vasylenko, Andrij, et al.
Published: (2024)

Morphotropic Phase Boundary (MPB) Induced Enhancement of Ferroelectric and Piezoelectric Properties in Li and Ta modified K0.5Na0.5NbO3
by: Sahoo, Satyaranjan, et al.
Published: (2025)

Revealing Nanostructures in High-Entropy Alloys via Machine-Learning Accelerated Scalable Monte Carlo Simulation
by: Liu, Xianglin, et al.
Published: (2025)

Descriptor-Enabled Rational Design of High-Entropy Materials Over Vast Chemical Spaces
by: Dey, Dibyendu, et al.
Published: (2023)

Accelerated Discovery of Vanadium Oxide Compositions: A WGAN-VAE Framework for Materials Design
by: Ebrahimzadeh, Danial, et al.
Published: (2025)

Topological Phase Transition and Geometrical Frustration in Fourier Photonic Simulator
by: Sun, Yuxuan, et al.
Published: (2025)

Simulations of High Temperature Decomposition of Metal-Organic Frameworks to form Amorphous Catalysts
by: Edwards, Connor W., et al.
Published: (2026)

Machine learning intermolecular transfer integrals with compact atomic cluster representations
by: Keeratikarn, Keerati, et al.
Published: (2025)

Machine learning potential as a guide for eutectic in ultra-refractory multicomponent ceramics
by: Valiulin, V. E., et al.
Published: (2026)