Cover Image

Design Topological Materials by Reinforcement Fine-Tuned Generative Model

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Xu, Haosheng, Qian, Dongheng, Liu, Zhixuan, Jiang, Yadong, Wang, Jing
Format:	Preprint
Published:	2025
Subjects:	Materials Science Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Predicting Many Crystal Properties via an Adaptive Transformer-based Framework
by: Xu, Haosheng, et al.
Published: (2024)

AIMatDesign: Knowledge-Augmented Reinforcement Learning for Inverse Materials Design under Data Scarcity
by: Yu, Yeyong, et al.
Published: (2025)

MatterTune: An Integrated, User-Friendly Platform for Fine-Tuning Atomistic Foundation Models to Accelerate Materials Simulation and Discovery
by: Kong, Lingyu, et al.
Published: (2025)

TopoMAS: Large Language Model Driven Topological Materials Multiagent System
by: Zhang, Baohua, et al.
Published: (2025)

Discovering two-dimensional magnetic topological insulators by machine learning
by: Xu, Haosheng, et al.
Published: (2023)

A Generation Framework with Strict Constraints for Crystal Materials Design
by: Huang, Chao, et al.
Published: (2024)

Materials Generation in the Era of Artificial Intelligence: A Comprehensive Survey
by: Li, Zhixun, et al.
Published: (2025)

Reinforcement Fine-Tuning for Materials Design
by: Cao, Zhendong, et al.
Published: (2025)

Interaction Topological Transformer for Multiscale Learning in Porous Materials
by: Chen, Dong, et al.
Published: (2025)

Generative Hierarchical Materials Search
by: Yang, Sherry, et al.
Published: (2024)

Interpretable Nanoporous Materials Design with Symmetry-Aware Networks
by: Zhou, Zhenhao, et al.
Published: (2025)

Agentic Design of Compositional Descriptors via Autoresearch for Materials Science Applications
by: Cobelli, Matteo, et al.
Published: (2026)

LLMatDesign: Autonomous Materials Discovery with Large Language Models
by: Jia, Shuyi, et al.
Published: (2024)

QMBench: A Research Level Benchmark for Quantum Materials Research
by: Wang, Yanzhen, et al.
Published: (2025)

Fine-Tuning Vision-Language Models for Multimodal Polymer Property Prediction
by: Vuong, An, et al.
Published: (2025)

Language-Native Materials Processing Design by Lightly Structured Text Database and Reasoning Large Language Model
by: Liu, Yuze, et al.
Published: (2025)

PRISMat: Policy-Driven, Permutation-Invariant Autoregressive Material Generation
by: Schlesinger, Claire, et al.
Published: (2026)

Towards Agentic Intelligence for Materials Science
by: Zhang, Huan, et al.
Published: (2026)

AGAPI-Agents: An Open-Access Agentic AI Platform for Accelerated Materials Design on AtomGPT.org
by: Lee, Jaehyung, et al.
Published: (2025)

Isolated nearly flat higher Chern band in monolayer transition metal trihalides
by: Bao, Kejie, et al.
Published: (2024)

DREAMS: Density Functional Theory Based Research Engine for Agentic Materials Simulation
by: Wang, Ziqi, et al.
Published: (2025)

From Text to Test: AI-Generated Control Software for Materials Science Instruments
by: Fébba, Davi M, et al.
Published: (2024)

Flexible, Model-Agnostic Method for Materials Data Extraction from Text Using General Purpose Language Models
by: Polak, Maciej P., et al.
Published: (2023)

Artificial Intelligence and Generative Models for Materials Discovery -- A Review
by: Handoko, Albertus Denny, et al.
Published: (2025)

Vector Field Oriented Diffusion Model for Crystal Material Generation
by: Klipfel, Astrid, et al.
Published: (2023)

MatFormBench: A Benchmarking Evaluation Framework for Target-Driven Materials Formulation
by: Wu, Linhan, et al.
Published: (2026)

DISO: A Domain Ontology for Modeling Dislocations in Crystalline Materials
by: Ihsan, Ahmad Zainul, et al.
Published: (2024)

Data-Driven Learnability Transition of Measurement-Induced Entanglement
by: Qian, Dongheng, et al.
Published: (2025)

Revealing Superconducting Chiral Edge Modes via Resistance Distributions
by: Huang, Linghao, et al.
Published: (2025)

Coupling Language Models with Physics-based Simulation for Synthesis of Inorganic Materials
by: Staley, Edward W., et al.
Published: (2026)

The Rise of Generative AI for Metal-Organic Framework Design and Synthesis
by: Duan, Chenru, et al.
Published: (2025)

From Data to Theory: Autonomous Large Language Model Agents for Materials Science
by: Alfred, Samuel Onimpa, et al.
Published: (2026)

An Agentic Framework for Autonomous Metamaterial Modeling and Inverse Design
by: Lu, Darui, et al.
Published: (2025)

Research Paradigm of Materials Science Tetrahedra with Artificial Intelligence
by: Zhang, Shiyun, et al.
Published: (2026)

FlowLLM: Flow Matching for Material Generation with Large Language Models as Base Distributions
by: Sriram, Anuroop, et al.
Published: (2024)

MSP-LLM: A Unified Large Language Model Framework for Complete Material Synthesis Planning
by: Noh, Heewoong, et al.
Published: (2026)

Toward Greater Autonomy in Materials Discovery Agents: Unifying Planning, Physics, and Scientists
by: Zhou, Lianhao, et al.
Published: (2025)

From Knowledge to Action: Outcomes of the 2025 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry
by: Roy, Aritra, et al.
Published: (2026)

An Agentic Framework for Autonomous Materials Computation
by: Xia, Zeyu, et al.
Published: (2025)

Open Materials 2024 (OMat24) Inorganic Materials Dataset and Models
by: Barroso-Luque, Luis, et al.
Published: (2024)