214 citations · 289 across the 6 of their papers we have counts for
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14 Examples of How LLMs Can Transform Materials Science and Chemistry: A Reflection on a Large Language Model Hackathon
Kevin Maik Jablonka, Qianxiang Ai, Alexander Al-Feghali +50
Large-language models (LLMs) such as GPT-4 caught the interest of many scientists. Recent studies suggested that these models could be useful in chemistry and materials science. To…
Machine Learning Prediction of Critical Cooling Rate for Metallic Glasses From Expanded Datasets and Elemental Features
Benjamin T. Afflerbach, Carter Francis, Lane E. Schultz +9
We use a random forest model to predict the critical cooling rate (RC) for glass formation of various alloys from features of their constituent elements. The random forest model wa…
A high-throughput structural and electrochemical study of metallic glass formation in Ni-Ti-Al
Howie Joress, Brian L. DeCost, Suchismita Sarker +7
Based on a set of machine learning predictions of glass formation in the Ni-Ti-Al system, we have undertaken a high-throughput experimental study of that system. We utilized rapid…
A Data Ecosystem to Support Machine Learning in Materials Science
Ben Blaiszik, Logan Ward, Marcus Schwarting +5
Facilitating the application of machine learning to materials science problems will require enhancing the data ecosystem to enable discovery and collection of data from many source…
Ternary mixed-anion semiconductors with tunable band gaps from machine-learning and crystal structure prediction
Maximilian Amsler, Logan Ward, Vinay I. Hegde +3
We report the computational investigation of a series of ternary XYZ and XYZ compounds with X={Mg, Ca, Sr, Ba}, Y={P, As, Sb, Bi}, and Z={S, Se, Te}. The compos…
Rapid Production of Accurate Embedded-Atom Method Potentials for Metal Alloys
Logan Ward, Anupriya Agrawal, Katharine M. Flores +1
The most critical limitation to the wide-scale use of classical molecular dynamics for alloy design is the availability of suitable interatomic potentials. In this work, we demonst…