Marcus Schwarting
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An open experimental database for exploring inorganic materials
A Zakutayev, N Wunder, M Schwarting, JD Perkins, R White, K Munch, ...
Scientific data 5 (1), 1-12, 2018
A data ecosystem to support machine learning in materials science
B Blaiszik, L Ward, M Schwarting, J Gaff, R Chard, D Pike, K Chard, ...
MRS Communications 9 (4), 1125-1133, 2019
14 examples of how LLMs can transform materials science and chemistry: a reflection on a large language model hackathon
KM Jablonka, Q Ai, A Al-Feghali, S Badhwar, JD Bocarsly, AM Bran, ...
Digital Discovery 2 (5), 1233-1250, 2023
Synergistic plasma-assisted electrochemical reduction of nitrogen to ammonia
S Kumari, S Pishgar, ME Schwarting, WF Paxton, JM Spurgeon
Chemical communications 54 (95), 13347-13350, 2018
Research data infrastructure for high-throughput experimental materials science
KR Talley, R White, N Wunder, M Eash, M Schwarting, D Evenson, ...
Patterns 2 (12), 2021
Targeting sars-cov-2 with ai-and hpc-enabled lead generation: A first data release
Y Babuji, B Blaiszik, T Brettin, K Chard, R Chard, A Clyde, I Foster, Z Hong, ...
arXiv preprint arXiv:2006.02431, 2020
Automated algorithms for band gap analysis from optical absorption spectra
M Schwarting, S Siol, K Talley, A Zakutayev, C Phillips
Materials Discovery 10, 43-52, 2017
Graph network based deep learning of bandgaps
XG Li, B Blaiszik, ME Schwarting, R Jacobs, A Scourtas, KJ Schmidt, ...
The Journal of Chemical Physics 155 (15), 2021
High throughput experimental materials database
A Zakutayev, J Perkins, M Schwarting, R White, K Munch, W Tumas, ...
National Renewable Energy Laboratory-Data (NREL-DATA), Golden, CO (United …, 2017
In silico active learning for small molecule properties
L Schneider, M Schwarting, J Mysona, H Liang, M Han, PM Rauscher, ...
Molecular Systems Design & Engineering 7 (12), 1611-1621, 2022
On the obfuscation of image sensor fingerprints
M Schwarting, T Burton, R Yampolskiy
2015 Annual Global Online Conference on Information and Computer Technology …, 2015
Segmentation of tomography datasets using 3D convolutional neural networks
J James, N Pruyne, T Stan, M Schwarting, J Yeom, S Hong, P Voorhees, ...
Computational Materials Science 216, 111847, 2023
Truth and regret: Large language models, the quran, and misinformation
AR Bhojani, M Schwarting
Theology and Science 21 (4), 557-563, 2023
HydroNet: Benchmark tasks for preserving intermolecular interactions and structural motifs in predictive and generative models for molecular data
S Choudhury, JA Bilbrey, L Ward, SS Xantheas, I Foster, JP Heindel, ...
arXiv preprint arXiv:2012.00131, 2020
Towards online steering of flame spray pyrolysis nanoparticle synthesis
M Levental, R Chard, JA Libera, K Chard, A Koripelly, JR Elias, ...
2020 IEEE/ACM 2nd Annual Workshop on Extreme-scale Experiment-in-the-Loop …, 2020
Twins in rotational spectroscopy: Does a rotational spectrum uniquely identify a molecule?
M Schwarting, NA Seifert, MJ Davis, B Blaiszik, I Foster, K Prozument
arXiv preprint arXiv:2404.04225, 2024
Foundry-ML-Software and Services to Simplify Access to Machine Learning Datasets in Materials Science
K Schmidt, A Scourtas, L Ward, S Wangen, M Schwarting, I Darling, ...
Journal of Open Source Software 9 (93), 5467, 2024
14 examples of how LLMs can transform materials science and chemistry: a reflection on a large language model hackathon
A Imran, M Schwarting, KM Jablonka, Q Ai, A Al-Feghali, S Badhwar, ...
RSC, 2023
MatPropXtractor: Generate to Extract
A Ajith, M Schwarting, Z Hong, K Chard, I Foster
3D Convolutional Neural Networks for Dendrite Segmentation Using Fine-Tuning and Hyperparameter Optimization
J James, N Pruyne, T Stan, M Schwarting, J Yeom, S Hong, P Voorhees, ...
arXiv preprint arXiv:2205.01167, 2022
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