Imagen de Portada

Agentic Design of Compositional Descriptors via Autoresearch for Materials Science Applications

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Cobelli, Matteo, Sanvito, Stefano
Formato:	Preprint
Publicado:	2026
Materias:	Materials Science Artificial Intelligence
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

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

Sampling Latent Material-Property Information From LLM-Derived Embedding Representations
por: Gilligan, Luke P. J., et al.
Publicado: (2024)

A rule-free workflow for the automated generation of databases from scientific literature
por: Gilligan, Luke P. J., et al.
Publicado: (2023)

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

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

Bilevel Autoresearch: Meta-Autoresearching Itself
por: Qu, Yaonan, et al.
Publicado: (2026)

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

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

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

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

Toward Autonomous Computational Catalysis Research via Agentic Systems
por: Chen, Honghao, et al.
Publicado: (2026)

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

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

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

Design Topological Materials by Reinforcement Fine-Tuned Generative Model
por: Xu, Haosheng, et al.
Publicado: (2025)

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

Agentic workflow enables the recovery of critical materials from complex feedstocks via selective precipitation
por: Ritchhart, Andrew, et al.
Publicado: (2026)

GENIUS: An Agentic AI Framework for Autonomous Design and Execution of Simulation Protocols
por: Soleymanibrojeni, Mohammad, et al.
Publicado: (2025)

Quantum-Accurate Machine Learning Potentials for Metal-Organic Frameworks using Temperature Driven Active Learning
por: Sharma, Abhishek, et al.
Publicado: (2024)

XxaCT-NN: Structure Agnostic Multimodal Learning for Materials Science
por: Subramanian, Jithendaraa, et al.
Publicado: (2025)

CASCADE: Cumulative Agentic Skill Creation through Autonomous Development and Evolution
por: Huang, Xu, et al.
Publicado: (2025)

Beyond Structure: Revolutionising Materials Discovery via AI-Driven Synthesis Protocol-Property Relationships
por: Lambard, Guillaume
Publicado: (2026)

Enhanced Hydrogen Evolution Activity of MOS$_2$-rGO Composite Synthesized via Hydrothermal Technique
por: Sebastian, Abhishek, et al.
Publicado: (2024)

Matter-of-Fact: A Benchmark for Verifying the Feasibility of Literature-Supported Claims in Materials Science
por: Jansen, Peter, et al.
Publicado: (2025)

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

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

Generative Hierarchical Materials Search
por: Yang, Sherry, et al.
Publicado: (2024)

HalluMat: Detecting Hallucinations in LLM-Generated Materials Science Content Through Multi-Stage Verification
por: Vangala, Bhanu Prakash, et al.
Publicado: (2025)

Sustainable Materials Discovery in the Era of Artificial Intelligence
por: Mannan, Sajid, et al.
Publicado: (2026)

GraphAgents: Knowledge Graph-Guided Agentic AI for Cross-Domain Materials Design
por: Stewart, Isabella A., et al.
Publicado: (2026)

Artificial Intelligence in Concrete Materials: A Scientometric View
por: Li, Zhanzhao, et al.
Publicado: (2022)

"DIVE" into Hydrogen Storage Materials Discovery with AI Agents
por: Zhang, Di, et al.
Publicado: (2025)

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

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

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

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

Probabilistic Phase Labeling and Lattice Refinement for Autonomous Material Research
por: Chang, Ming-Chiang, et al.
Publicado: (2023)

Erratum: Photovoltage from ferroelectric domain walls in BiFeO$_3$
por: Körbel, Sabine, et al.
Publicado: (2019)

Born-Qualified: An Autonomous Framework for Deploying Advanced Energy and Electronic Materials
por: Spurgeon, Steven R., et al.
Publicado: (2026)

Property Prediction of Stacked Bilayer Materials: A Multimodal Learning Approach
por: Vuong, An, et al.
Publicado: (2026)