699 citations · 2.4k across the 17 of their papers we have counts for
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From Knowledge to Action: Outcomes of the 2025 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry
Aritra Roy, Kevin Shen, Andrew MacBride +350
Large language models (LLMs) are rapidly changing how researchers in materials science and chemistry discover, organize, and act on scientific knowledge. This paper analyzes a broa…
Reciprocal Space Attention for Learning Long-Range Interactions
Hariharan Ramasubramanian, Alvaro Vazquez-Mayagoitia, Ganesh Sivaraman +1
Machine learning interatomic potentials (MLIPs) have revolutionized the modeling of materials and molecules by directly fitting to ab initio data. However, while these models excel…
An Experimentally Driven Automated Machine Learned lnter-Atomic Potential for a Refractory Oxide
Ganesh Sivaraman, Leighanne Gallington, Anand Narayanan Krishnamoorthy +4
Understanding the structure and properties of refractory oxides are critical for high temperature applications. In this work, a combined experimental and simulation approach uses a…
Machine Learning Inter-Atomic Potentials Generation Driven by Active Learning: A Case Study for Amorphous and Liquid Hafnium dioxide
Ganesh Sivaraman, Anand Narayanan Krishnamoorthy, Matthias Baur +5
We propose a novel active learning scheme for automatically sampling a minimum number of uncorrelated configurations for fitting the Gaussian Approximation Potential (GAP). Our act…
Genarris 2.0: A Random Structure Generator for Molecular Crystals
Rithwik Tom, Timothy Rose, Imanuel Bier +3
Genarris is an open-source Python package for generating random molecular crystal structures with physical constraints for seeding crystal structure prediction algorithms and train…
Tunable Semiconductors: Control over Carrier States and Excitations in Layered Hybrid Organic-Inorganic Perovskites
Chi Liu, William Huhn, Ke-Zhao Du +6
For a class of 2D hybrid organic-inorganic perovskite semiconductors based on -conjugated organic cations, we predict quantitatively how varying the organic and inorganic compon…
GAtor: A First Principles Genetic Algorithm for Molecular Crystal Structure Prediction
Farren Curtis, Xiayue Li, Timothy Rose +4
We present the implementation of GAtor, a massively parallel, first principles genetic algorithm (GA) for molecular crystal structure prediction. GAtor is written in Python and cur…