most citedReflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry

5 citations · 9 across the 5 of their papers we have counts for

collaborators

5 papers

cs.LG2025

Accurate and Uncertainty-Aware Multi-Task Prediction of HEA Properties Using Prior-Guided Deep Gaussian Processes

Sk Md Ahnaf Akif Alvi, Mrinalini Mulukutla, Nicolas Flores +6

Surrogate modeling techniques have become indispensable in accelerating the discovery and optimization of high-entropy alloys(HEAs), especially when integrating computational predi…

cs.LG20252 cited

34 Examples of LLM Applications in Materials Science and Chemistry: Towards Automation, Assistants, Agents, and Accelerated Scientific Discovery

Yoel Zimmermann, Adib Bazgir, Alexander Al-Feghali +32

Large Language Models (LLMs) are reshaping many aspects of materials science and chemistry research, enabling advances in molecular property prediction, materials design, scientifi…

cond-mat.mtrl-sci2024

Magnetic properties and growth kinetics of Co/Gd bilayers with perpendicular magnetic anisotropy

T. J. Kools, J. Hintermayr, Y. L. W. van Hees +5

Ultrathin 3d-4f synthetic ferrimagnets with perpendicular magnetic anisotropy (PMA) exhibit a range of intriguing magnetic phenomena, including all-optical switching of magnetizati…

cs.LG20245 cited

Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry

Yoel Zimmermann, Adib Bazgir, Zartashia Afzal +141

Here, we present the outcomes from the second Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry, which engaged participants across global hyb…

cond-mat.mtrl-sci20242 cited

From electrons to phase diagrams with classical and machine learning potentials: automated workflows for materials science with pyiron

Sarath Menon, Yury Lysogorskiy, Alexander L. M. Knoll +10

We present a comprehensive and user-friendly framework built upon the pyiron integrated development environment (IDE), enabling researchers to perform the entire Machine Learning P…