Image de couverture de livre

Crystalyse: a multi-tool agent for materials design

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Nduma, Ryan, Park, Hyunsoo, Walsh, Aron
Format:	Preprint
Publié:	2025
Sujets:	Materials Science
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Materealize: a multi-agent deliberation system for end-to-end material design and synthesis
par: Kim, Seongmin, et autres
Publié: (2026)

Continuous SUN (Stable, Unique, and Novel) Metric for Generative Modeling of Inorganic Crystals
par: Negishi, Masahiro, et autres
Publié: (2025)

Platonic representation of foundation machine learning interatomic potentials
par: Li, Zhenzhu, et autres
Publié: (2025)

Na Vacancy Driven Phase Transformation and Fast Ion Conduction in W-doped Na$_3$SbS$_4$ from Machine Learning Force Fields
par: Klarbring, Johan, et autres
Publié: (2024)

Dynamic Vacancy Levels in CsPbCl3 Obey Equilibrium Defect Thermodynamics
par: Mosquera-Lois, Irea, et autres
Publié: (2025)

Phase Stability and Transformations in Lead Mixed Halide Perovskites from Machine Learning Force Fields
par: Liang, Xia, et autres
Publié: (2025)

Sulfur Vacancies Limit the Open-circuit Voltage of Sb2S3 Solar Cells
par: Wang, Xinwei, et autres
Publié: (2024)

Multi-fidelity Machine Learning Interatomic Potentials for Charged Point Defects
par: Wang, Xinwei, et autres
Publié: (2026)

Guiding Generative Models to Uncover Diverse and Novel Crystals via Reinforcement Learning
par: Park, Hyunsoo, et autres
Publié: (2025)

Illuminating the property space in crystal structure prediction using Quality-Diversity algorithms
par: Wolinska, Marta, et autres
Publié: (2024)

S1-MatAgent: A planner driven multi-agent system for material discovery
par: Wang, Xinrui, et autres
Publié: (2025)

Point defect formation at finite temperatures with machine learning force fields
par: Mosquera-Lois, Irea, et autres
Publié: (2024)

Upper efficiency limit of Sb2Se3 solar cells
par: Wang, Xinwei, et autres
Publié: (2024)

Generative design of inorganic materials
par: Recatala-Gomez, Jose, et autres
Publié: (2026)

Sustainability-informed materials design
par: Woods-Robinson, Rachel, et autres
Publié: (2026)

aflow++: a C++ framework for autonomous materials design
par: Oses, C., et autres
Publié: (2022)

Four-electron Negative-U Vacancy Defects in Antimony Selenide
par: Wang, Xinwei, et autres
Publié: (2023)

Crystalline-dependent magnon torques in all-sputtered Hf/Cr2O3/ferromagnet heterostructures
par: Pu, Yuchen, et autres
Publié: (2026)

Machine-learning structural reconstructions for accelerated point defect calculations
par: Mosquera-Lois, Irea, et autres
Publié: (2024)

Substrate-aware computational design of two-dimensional materials
par: Mazitov, Arslan, et autres
Publié: (2024)

Materials design based on a material-motif network and heterogeneous graphs
par: Aryal, Anoj, et autres
Publié: (2026)

MLIP Arena: Advancing Fairness and Transparency in Machine Learning Interatomic Potentials via an Open, Accessible Benchmark Platform
par: Chiang, Yuan, et autres
Publié: (2025)

A tool to check whether a symmetry-compensated collinear magnetic material is antiferro- or altermagnetic
par: Smolyanyuk, Andriy, et autres
Publié: (2024)

Kinetically Arrested Twin-Domain State in Formamidinium Lead Iodide
par: Liang, Xia, et autres
Publié: (2026)

T2MAT (text-to-materials): A universal agent for generating material structures with goal properties from a single sentence
par: Song, Zhilong, et autres
Publié: (2024)

Optical materials discovery and design with federated databases and machine learning
par: Trinquet, Victor, et autres
Publié: (2024)

Imperfections are not 0 K: free energy of point defects in crystals
par: Mosquera-Lois, Irea, et autres
Publié: (2023)

AI-driven materials design: a mini-review
par: Cheng, Mouyang, et autres
Publié: (2025)

Defect-Limited Efficiency of Pnictogen Chalcohalide Solar Cells
par: López, Cibrán, et autres
Publié: (2025)

Chalcogen Vacancies Rule Charge Recombination in Pnictogen Chalcohalide Solar-Cell Absorbers
par: López, Cibrán, et autres
Publié: (2025)

Learning disentangled latent representations facilitates discovery and design of functional materials
par: Cha, Jaehoon, et autres
Publié: (2025)

Developments and applications of the OPTIMADE API for materials discovery, design, and data exchange
par: Evans, Matthew L., et autres
Publié: (2024)

Crystallographic defects in Weyl semimetal LaAlGe
par: Kim, Inseo, et autres
Publié: (2024)

Generative deep learning for the inverse design of materials
par: Long, Teng, et autres
Publié: (2024)

MatterGen: a generative model for inorganic materials design
par: Zeni, Claudio, et autres
Publié: (2023)

Helium atom micro-diffraction as a characterisation tool for 2D materials
par: von Jeinsen, Nick, et autres
Publié: (2024)

tda-segmentor: A tool to extract and analyze local structure and porosity features in porous materials
par: Vasudevan, Aditya, et autres
Publié: (2023)

A case study of multi-modal, multi-institutional data management for the combinatorial materials science community
par: Allec, Sarah I., et autres
Publié: (2023)

Polarization Domain Mapping From 4D-STEM Using Deep Learning
par: Hardy, Fintan G., et autres
Publié: (2025)

A closed-loop AI framework for hypothesis-driven and interpretable materials design
par: Ji, Kangyu, et autres
Publié: (2025)