Copertina

From Phase Prediction to Phase Design: A ReAct Agent Framework for High-Entropy Alloy Discovery

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Peivaste, Iman, Belouettar, Salim
Natura:	Preprint
Pubblicazione:	2026
Soggetti:	Materials Science Artificial Intelligence
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Teaching Artificial Intelligence to Perform Rapid, Resolution-Invariant Grain Growth Modeling via Fourier Neural Operator
di: Peivaste, Iman, et al.
Pubblicazione: (2025)

Escaping the Hydrolysis Trap: An Agentic Workflow for Inverse Design of Durable Photocatalytic Covalent Organic Frameworks
di: Peivaste, Iman, et al.
Pubblicazione: (2026)

ChemNavigator: Agentic AI Discovery of Design Rules for Organic Photocatalysts
di: Peivaste, Iman, et al.
Pubblicazione: (2026)

Co-ReAct: Rubrics as Step-Level Collaborators for ReAct Agents
di: Kang, Jiazheng, et al.
Pubblicazione: (2026)

Focused ReAct: Improving ReAct through Reiterate and Early Stop
di: Li, Shuoqiu, et al.
Pubblicazione: (2024)

ReAct! An Interactive Tool for Hybrid Planning in Robotics
di: Dogmus, Zeynep, et al.
Pubblicazione: (2013)

Artificial Intelligence in Materials Science and Engineering: Current Landscape, Key Challenges, and Future Trajectorie
di: Peivaste, Iman, et al.
Pubblicazione: (2026)

GEM: Graph-Enhanced Mixture-of-Experts with ReAct Agents for Dialogue State Tracking
di: Zhu, Ziqi, et al.
Pubblicazione: (2026)

FAMOSE: A ReAct Approach to Automated Feature Discovery
di: Burghardt, Keith, et al.
Pubblicazione: (2026)

MATAI: A Generalist Machine Learning Framework for Property Prediction and Inverse Design of Advanced Alloys
di: Deng, Yanchen, et al.
Pubblicazione: (2025)

Crystal Fractional Graph Neural Network for Energy Prediction of High-Entropy Alloys
di: Kotama, Takanori, et al.
Pubblicazione: (2026)

Reason-Plan-ReAct: A Reasoner-Planner Supervising a ReAct Executor for Complex Enterprise Tasks
di: Molinari, Gianni, et al.
Pubblicazione: (2025)

Gradientsys: A Multi-Agent LLM Scheduler with ReAct Orchestration
di: Song, Xinyuan, et al.
Pubblicazione: (2025)

LLM-Driven Discovery of High-Entropy Catalysts via Retrieval-Augmented Generation
di: Scientists, AI, et al.
Pubblicazione: (2026)

Breaking ReAct Agents: Foot-in-the-Door Attack Will Get You In
di: Nakash, Itay, et al.
Pubblicazione: (2024)

ReAct Meets ActRe: When Language Agents Enjoy Training Data Autonomy
di: Yang, Zonghan, et al.
Pubblicazione: (2024)

From Quantum Annealing to Alloy Discovery: Towards Accelerated Design of High-Entropy Alloys
di: Ibarra-Hoyos, Diego, et al.
Pubblicazione: (2025)

Beyond ReAct: A Planner-Centric Framework for Complex Tool-Augmented LLM Reasoning
di: Wei, Xiaolong, et al.
Pubblicazione: (2025)

RA-Gen: A Controllable Code Generation Framework Using ReAct for Multi-Agent Task Execution
di: Liu, Aofan, et al.
Pubblicazione: (2025)

The Role of Allotropy on Phase Formation in High Entropy Alloys
di: Kaufmann, Kevin, et al.
Pubblicazione: (2024)

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

On the Brittle Foundations of ReAct Prompting for Agentic Large Language Models
di: Verma, Mudit, et al.
Pubblicazione: (2024)

OLIVIA: Online Learning via Inference-time Action Adaptation for Decision Making in LLM ReAct Agents
di: Yu, Sheldon, et al.
Pubblicazione: (2026)

UAV-CodeAgents: Scalable UAV Mission Planning via Multi-Agent ReAct and Vision-Language Reasoning
di: Sautenkov, Oleg, et al.
Pubblicazione: (2025)

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

Autonomous Multi-Agent AI for High-Throughput Polymer Informatics: From Property Prediction to Generative Design Across Synthetic and Bio-Polymers
di: Roy, Mahule, et al.
Pubblicazione: (2026)

Repeton: Structured Bug Repair with ReAct-Guided Patch-and-Test Cycles
di: Vinh, Nguyen Phu, et al.
Pubblicazione: (2025)

Exploring ReAct Prompting for Task-Oriented Dialogue: Insights and Shortcomings
di: Elizabeth, Michelle, et al.
Pubblicazione: (2024)

Domain-specific ReAct for physics-integrated iterative modeling: A case study of LLM agents for gas path analysis of gas turbines
di: Song, Tao, et al.
Pubblicazione: (2024)

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

Autonomous Multi-objective Alloy Design through Simulation-guided Optimization
di: Yang, Penghui, et al.
Pubblicazione: (2025)

Dynamic ReAct: Scalable Tool Selection for Large-Scale MCP Environments
di: Gaurav, Nishant, et al.
Pubblicazione: (2025)

AI-Driven Phase Identification from X-ray Hyperspectral Imaging of cycled Na-ion Cathode Materials
di: Adrar, Fayçal, et al.
Pubblicazione: (2026)

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

Large Language Model Agent for Structural Drawing Generation Using ReAct Prompt Engineering and Retrieval Augmented Generation
di: Zhang, Xin, et al.
Pubblicazione: (2025)

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

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

Quantum-Annealing Enhanced Machine Learning for Interpretable Phase Classification of High-Entropy Alloys
di: Hoyos, Diego Ibarra, et al.
Pubblicazione: (2025)

Multi-AI Agent Framework Reveals the "Oxide Gatekeeper" in Aluminum Nanoparticle Oxidation
di: Lu, Yiming, et al.
Pubblicazione: (2025)

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