Image de couverture de livre

Enhancing Magnetocaloric Material Discovery: A Machine Learning Approach Using an Autogenerated Database by Large Language Models

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Yuan, Jiaoyue, Yang, Runqing, Patra, Lokanath, Liao, Bolin
Format:	Preprint
Publié:	2024
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

Indirect Exchange Interaction Leads to Large Lattice Contribution to Magnetocaloric Entropy Change
par: Patra, Lokanath, et autres
Publié: (2023)

Impact of Dimensionality on the Magnetocaloric Effect in Two-dimensional Magnets
par: Patra, Lokanath, et autres
Publié: (2024)

Coupled Spin-lattice Dynamics across a Magnetostructural Phase Transition
par: Patra, Lokanath, et autres
Publié: (2026)

Room-temperature Magnetic Thermal Switching by Suppressing Phonon-Magnon Scattering
par: Zhang, Fanghao, et autres
Publié: (2024)

Magnetic Polarons Enable Exceptional Magnetocaloric Response
par: Ancheta, Joshua, et autres
Publié: (2026)

Anharmonic Quantum Transport Analysis of Thermal Transport Anomalies in Ultrathin Silicon Nanowires
par: Patra, Lokanath, et autres
Publié: (2026)

Unveiling the Reactivity of Oxygen and Ozone on C2N Monolayer: A First-Principles Study
par: Das, Soumendra Kumar, et autres
Publié: (2024)

Revealing Phonon Bridge Effect for Amorphous vs Crystalline Metal-Silicide Layers at Si/Ti Interfaces by a Machine Learning Potential
par: Singh, Mayur, et autres
Publié: (2025)

TXL Fusion: A Hybrid Machine Learning Framework Integrating Chemical Heuristics and Large Language Models for Topological Materials Discovery
par: Ullah, Arif, et autres
Publié: (2025)

Materials Discovery With Quantum-Enhanced Machine Learning Algorithms
par: Graña, Ignacio F., et autres
Publié: (2025)

Fostering Innovation: Streamlining Magnetocaloric Materials Research by Digitalization
par: Bekemeier, Simon, et autres
Publié: (2025)

High-throughput Discovery of Anti-gap Semiconductors
par: Xiang, Zeyu, et autres
Publié: (2025)

Large Language Model-Driven Database for Thermoelectric Materials
par: Itani, Suman, et autres
Publié: (2024)

Symmetry Relation Database and Its Application to Ferroelectric Materials Discovery
par: Zhu, Qiang, et autres
Publié: (2022)

High-Throughput Search for Photostrictive Materials based on a Thermodynamic Descriptor
par: Xiang, Zeyu, et autres
Publié: (2024)

Agentic AI and Machine Learning for Accelerated Materials Discovery and Applications
par: Chen, Jihua, et autres
Publié: (2026)

Electron Drag Effect on Thermal Conductivity in Two-dimensional Semiconductors
par: Quan, Yujie, et autres
Publié: (2024)

A Materials Map Integrating Experimental and Computational Data via Graph-Based Machine Learning for Enhanced Materials Discovery
par: Hashimoto, Yusuke, et autres
Publié: (2025)

Decoratypes: An Extensible Crystal Taxonomy for Machine Learning-Guided Materials Discovery
par: Miller, Kyle D., et autres
Publié: (2025)

Beyond Predicted ZT: Machine Learning Strategies for the Experimental Discovery of Thermoelectric Materials
par: Athar, Shoeb, et autres
Publié: (2026)

LLMatDesign: Autonomous Materials Discovery with Large Language Models
par: Jia, Shuyi, et autres
Publié: (2024)

Language Models for Materials Discovery and Sustainability: Progress, Challenges, and Opportunities
par: Pei, Zongrui, et autres
Publié: (2025)

Engineering the Magnetocaloric Effect in Nd$T_4$B
par: Fruhling, Kyle W., et autres
Publié: (2025)

Language-Native Materials Processing Design by Lightly Structured Text Database and Reasoning Large Language Model
par: Liu, Yuze, et autres
Publié: (2025)

Learning Magnetic Order Classification from Large-Scale Materials Databases
par: Fahmy, Ahmed E.
Publié: (2025)

Large Language Models for Superconductor Discovery
par: Itani, Suman, et autres
Publié: (2025)

Machine Learning-Guided Discovery of Temperature-Induced Solid-Solid Phase Transitions in Inorganic Materials
par: López, Cibrán, et autres
Publié: (2025)

Machine Learning-Enhanced Design of Lead-Free Halide Perovskite Materials Using Density Functional Theory
par: Kumar, Upendra, et autres
Publié: (2024)

Coupled electron-phonon hydrodynamics in two-dimensional semiconductors
par: Quan, Yujie, et autres
Publié: (2024)

Enhancing Materials Discovery with Valence Constrained Design in Generative Modeling
par: Cheng, Mouyang, et autres
Publié: (2025)

A Prompt-Engineered Large Language Model, Deep Learning Workflow for Materials Classification
par: Liu, Siyu, et autres
Publié: (2024)

Role of Large Language Models and Retrieval-Augmented Generation for Accelerating Crystalline Material Discovery: A Systematic Review
par: Oche, Agada Joseph, et autres
Publié: (2025)

Machine Learning - Driven Materials Discovery: Unlocking Next-Generation Functional Materials - A review
par: Nematov, Dilshod, et autres
Publié: (2025)

Machine Learning Approaches to Point Defects in Non-Metallic Materials: A Review of Methods
par: Kumagai, Yu, et autres
Publié: (2026)

A New Workflow for Materials Discovery Bridging the Gap Between Experimental Databases and Graph Neural Networks
par: Schoener, Brandon, et autres
Publié: (2026)

Active Learning Guided Computational Discovery of 2D Materials with Large Spin Hall Conductivity
par: Kale, Abhijeet J., et autres
Publié: (2025)

Bridging Theory and Experiment in Materials Discovery: Machine-Learning-Assisted Prediction of Synthesizable Structures
par: Xin, Yu, et autres
Publié: (2025)

Accelerating Complex Materials Discovery with Universal Machine-Learning Potential-Driven Structure Prediction
par: An, Yuqi, et autres
Publié: (2026)

Deep-Learning Database of Density Functional Theory Hamiltonians for Twisted Materials
par: Bao, Ting, et autres
Publié: (2024)

Magnetocaloric properties of single-crystalline Eu$_5$In$_2$Sb$_6$
par: Synoradzki, Karol, et autres
Publié: (2024)