214 citations · 431 across the 11 of their papers we have counts for
11 papers
Steering an Active Learning Workflow Towards Novel Materials Discovery via Queue Prioritization
Marcus Schwarting, Logan Ward, Nathaniel Hudson +5
Generative AI poses both opportunities and risks for solving inverse design problems in the sciences. Generative tools provide the ability to expand and refine a search space auton…
MOFA: Discovering Materials for Carbon Capture with a GenAI- and Simulation-Based Workflow
Xiaoli Yan, Nathaniel Hudson, Hyun Park +15
We present MOFA, an open-source generative AI (GenAI) plus simulation workflow for high-throughput generation of metal-organic frameworks (MOFs) on large-scale high-performance com…
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…
Twins in rotational spectroscopy: Does a rotational spectrum uniquely identify a molecule?
Marcus Schwarting, Nathan A. Seifert, Michael J. Davis +3
Rotational spectroscopy is the most accurate method for determining structures of molecules in the gas phase. It is often assumed that a rotational spectrum is a unique "fingerprin…
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…
The eBible Corpus: Data and Model Benchmarks for Bible Translation for Low-Resource Languages
Vesa Akerman, David Baines, Damien Daspit +7
Efficiently and accurately translating a corpus into a low-resource language remains a challenge, regardless of the strategies employed, whether manual, automated, or a combination…
3D Convolutional Neural Networks for Dendrite Segmentation Using Fine-Tuning and Hyperparameter Optimization
Jim James, Nathan Pruyne, Tiberiu Stan +6
Dendritic microstructures are ubiquitous in nature and are the primary solidification morphologies in metallic materials. Techniques such as x-ray computed tomography (XCT) have pr…
HydroNet: Benchmark Tasks for Preserving Intermolecular Interactions and Structural Motifs in Predictive and Generative Models for Molecular Data
Sutanay Choudhury, Jenna A. Bilbrey, Logan Ward +5
Intermolecular and long-range interactions are central to phenomena as diverse as gene regulation, topological states of quantum materials, electrolyte transport in batteries, and…
Towards Online Steering of Flame Spray Pyrolysis Nanoparticle Synthesis
Maksim Levental, Ryan Chard, Joseph A. Libera +8
Flame Spray Pyrolysis (FSP) is a manufacturing technique to mass produce engineered nanoparticles for applications in catalysis, energy materials, composites, and more. FSP instrum…
Targeting SARS-CoV-2 with AI- and HPC-enabled Lead Generation: A First Data Release
Yadu Babuji, Ben Blaiszik, Tom Brettin +15
Researchers across the globe are seeking to rapidly repurpose existing drugs or discover new drugs to counter the the novel coronavirus disease (COVID-19) caused by severe acute re…
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…