Cover Image

Discovery of 2D Materials via Symmetry-Constrained Diffusion Model

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Xu, Shihang, Chu, Shibing, Mrad, Rami, Zhang, Zhejun, Li, Zhelin, Jiao, Runxian, Chen, Yuanping
Format:	Preprint
Published:	2024
Subjects:	Materials Science Machine Learning Chemical Physics
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Generative Design of Crystal Structures by Point Cloud Representations and Diffusion Model
by: Li, Zhelin, et al.
Published: (2024)

D3MES: Diffusion Transformer with multihead equivariant self-attention for 3D molecule generation
by: Zhang, Zhejun, et al.
Published: (2025)

Learning Ordering in Crystalline Materials with Symmetry-Aware Graph Neural Networks
by: Peng, Jiayu, et al.
Published: (2024)

Foundation Models for Discovery and Exploration in Chemical Space
by: Wadell, Alexius, et al.
Published: (2025)

Clever Materials: When Models Identify Good Materials for the Wrong Reasons
by: Jablonka, Kevin Maik
Published: (2026)

Generative Chemical Language Models for Energetic Materials Discovery
by: Salij, Andrew, et al.
Published: (2026)

Adapting OC20-trained EquiformerV2 Models for High-Entropy Materials
by: Clausen, Christian M., et al.
Published: (2024)

Many-body Expansion Based Machine Learning Models for Octahedral Transition Metal Complexes
by: Meyer, Ralf, et al.
Published: (2024)

Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry
by: Zimmermann, Yoel, et al.
Published: (2024)

Evaluating Large Language Models in Scientific Discovery
by: Song, Zhangde, et al.
Published: (2025)

Knowledge-Reuse Transfer Learning Methods in Molecular and Material Science
by: Chen, An, et al.
Published: (2024)

The Open DAC 2025 Dataset for Sorbent Discovery in Direct Air Capture
by: Sriram, Anuroop, et al.
Published: (2025)

Leveraging Data Mining, Active Learning, and Domain Adaptation in a Multi-Stage, Machine Learning-Driven Approach for the Efficient Discovery of Advanced Acidic Oxygen Evolution Electrocatalysts
by: Ding, Rui, et al.
Published: (2024)

Enhancing Diffusion-Based Sampling with Molecular Collective Variables
by: Nam, Juno, et al.
Published: (2025)

Accelerating Complex Materials Discovery with Universal Machine-Learning Potential-Driven Structure Prediction
by: An, Yuqi, et al.
Published: (2026)

Manifold Diffusion for Structure Generation of Transition Metal Complexes
by: Schaufelberger, Luca, et al.
Published: (2026)

Building-Block Aware Generative Modeling for 3D Crystals of Metal Organic Frameworks
by: Duan, Chenru, et al.
Published: (2025)

Accelerating Scientific Discovery with Autonomous Goal-evolving Agents
by: Du, Yuanqi, et al.
Published: (2025)

Symmetry-Constrained Generation of Diverse Low-Bandgap Molecules with Monte Carlo Tree Search
by: Subramanian, Akshay, et al.
Published: (2024)

Synthesis of single-layered fluorographdiyne nanosheets via selective on-surface 2D covalent polymerization
by: Shu, Chen-Hui, et al.
Published: (2026)

DFT and Model Hamiltonian Study of Optoelectronic Properties of Some Low-Symmetry Graphene Quantum Dots
by: Das, Samayita, et al.
Published: (2024)

Spectral/Spatial Tensor Atomic Cluster Expansion with Universal Embeddings in Cartesian Space
by: Xu, Zemin, et al.
Published: (2025)

An Explainable AI Model for Binary LJ Fluids
by: Hashmi, Israrul H, et al.
Published: (2025)

General-Purpose Models for the Chemical Sciences: LLMs and Beyond
by: Alampara, Nawaf, et al.
Published: (2025)

Active Learning Enables Extrapolation in Molecular Generative Models
by: Antoniuk, Evan R., et al.
Published: (2025)

A chemical language model for reticular materials design
by: Menon, Dhruv, et al.
Published: (2026)

QT-Net: Rethinking Evaluation of AI Models in Atomic Chemical Space
by: Crespo, Pablo Martínez, et al.
Published: (2026)

XANE(3): An E(3)-Equivariant Graph Neural Network for Accurate Prediction of XANES Spectra from Atomic Structures
by: Grizzi, Vitor F., et al.
Published: (2026)

Cartesian-nj: Extending e3nn to Irreducible Cartesian Tensor Product and Contracion
by: Xu, Zemin, et al.
Published: (2025)

Active Learning for Generalizable Detonation Performance Prediction of Energetic Materials
by: Ullberg, R. Seaton, et al.
Published: (2026)

Model-free quantification of completeness, uncertainties, and outliers in atomistic machine learning using information theory
by: Schwalbe-Koda, Daniel, et al.
Published: (2024)

Deep Learning for GWP Prediction: A Framework Using PCA, Quantile Transformation, and Ensemble Modeling
by: Rajapriya, Navin, et al.
Published: (2024)

Symmetry- and Gradient-enhanced Gaussian Process Regression for the Active Learning of Potential Energy Surfaces in Porous Materials
by: Krondorfer, Johannes K., et al.
Published: (2025)

Known Unknowns: Out-of-Distribution Property Prediction in Materials and Molecules
by: Segal, Nofit, et al.
Published: (2025)

Breaking scaling relations with inverse catalysts: a machine learning exploration of trends in $\mathrm{CO_2}$ hydrogenation energy barriers
by: Kempen, Luuk H. E., et al.
Published: (2025)

Equivariant Matrix Function Neural Networks
by: Batatia, Ilyes, et al.
Published: (2023)

Revealing Nanoscale Ni-Oxidation State Variations in Single-Crystal NMC811 via 2D and 3D Spectro-Ptychography
by: Ziesche, Ralf F., et al.
Published: (2025)

A Comprehensive Computational Framework for Materials Design, Ab Initio Modeling, and Molecular Docking
by: Akanda, Md Rakibul Karim, et al.
Published: (2026)

Towards Fast, Specialized Machine Learning Force Fields: Distilling Foundation Models via Energy Hessians
by: Amin, Ishan, et al.
Published: (2025)

Atomistic Modeling of Chemical Disorder in Materials: Bridging Classical Methods and AI-Assisted Approaches
by: Peng, Jiayu, et al.
Published: (2026)