A mobile robotic chemist B Burger, PM Maffettone, VV Gusev, CM Aitchison, Y Bai, X Wang, X Li, ...
Nature 583 (7815), 237-241, 2020
1181 2020 On-demand hydrogen generation using nanosilicon: splitting water without light, heat, or electricity F Erogbogbo, T Lin, PM Tucciarone, KM LaJoie, L Lai, GD Patki, ...
Nano letters 13 (2), 451-456, 2013
214 2013 Accelerating Bayesian optimization for biological sequence design with denoising autoencoders S Stanton, W Maddox, N Gruver, P Maffettone, E Delaney, P Greenside, ...
International conference on machine learning, 20459-20478, 2022
103 2022 Combining machine learning and high-throughput experimentation to discover photocatalytically active organic molecules X Li, PM Maffettone, Y Che, T Liu, L Chen, AI Cooper
Chemical Science 12 (32), 10742-10754, 2021
80 2021 Crystallography companion agent for high-throughput materials discovery PM Maffettone, L Banko, P Cui, Y Lysogorskiy, MA Little, D Olds, A Ludwig, ...
Nature Computational Science 1 (4), 290-297, 2021
75 2021 Creating ligand-free silicon germanium alloy nanocrystal inks F Erogbogbo, T Liu, N Ramadurai, P Tuccarione, L Lai, MT Swihart, ...
ACS nano 5 (10), 7950-7959, 2011
53 2011 Deep learning for visualization and novelty detection in large X-ray diffraction datasets L Banko, PM Maffettone, D Naujoks, D Olds, A Ludwig
Npj Computational Materials 7 (1), 104, 2021
48 2021 Negative Hydration Expansion in M Baise, PM Maffettone, F Trousselet, NP Funnell, FX Coudert, ...
Physical Review Letters 120 (26), 265501, 2018
35 2018 Constrained non-negative matrix factorization enabling real-time insights of in situ and high-throughput experiments PM Maffettone, AC Daly, D Olds
Applied Physics Reviews 8 (4), 2021
26 2021 What is missing in autonomous discovery: open challenges for the community PM Maffettone, P Friederich, SG Baird, B Blaiszik, KA Brown, SI Campbell, ...
Digital Discovery 2 (6), 1644-1659, 2023
22 2023 Effective surrogate models for protein design with bayesian optimization N Gruver, S Stanton, P Kirichenko, M Finzi, P Maffettone, V Myers, ...
ICML Workshop on Computational Biology 198, 2021
22 2021 Gaming the beamlines—employing reinforcement learning to maximize scientific outcomes at large-scale user facilities PM Maffettone, JK Lynch, TA Caswell, CE Cook, SI Campbell, D Olds
Machine Learning: Science and Technology 2 (2), 025025, 2021
22 2021 Machine learning enabling high-throughput and remote operations at large-scale user facilities T Konstantinova, PM Maffettone, B Ravel, SI Campbell, AM Barbour, ...
Digital Discovery 1 (4), 413-426, 2022
15 2022 Ferromagnetic resonance in a topographically modulated permalloy film J Sklenar, P Tucciarone, RJ Lee, D Tice, RPH Chang, SJ Lee, ...
Physical Review B 91 (13), 134424, 2015
9 2015 Self-driving multimodal studies at user facilities PM Maffettone, DB Allan, SI Campbell, MR Carbone, TA Caswell, ...
arXiv preprint arXiv:2301.09177, 2023
8 2023 Machine-learning for designing nanoarchitectured materials by dealloying C Zhao, CC Chung, S Jiang, MM Noack, JH Chen, K Manandhar, J Lynch, ...
Communications Materials 3 (1), 86, 2022
8 2022 Advancing discovery with artificial intelligence and machine learning at NSLS-II A Barbour, S Campbell, T Caswell, M Fukuto, M Hanwell, A Kiss, ...
Synchrotron Radiation News 35 (4), 44-50, 2022
8 2022 Delivering real-time multi-modal materials analysis with enterprise beamlines PM Maffettone, S Campbell, MD Hanwell, S Wilkins, D Olds
Cell Reports Physical Science 3 (11), 2022
6 2022 Accurate, Uncertainty-Aware Classification of Molecular Chemical Motifs from Multimodal X-ray Absorption Spectroscopy MR Carbone, PM Maffettone, X Qu, S Yoo, D Lu
The Journal of Physical Chemistry A 128 (10), 1948-1957, 2024
4 2024 Inverse protein folding using deep bayesian optimization N Maus, Y Zeng, DA Anderson, P Maffettone, A Solomon, P Greenside, ...
arXiv preprint arXiv:2305.18089, 2023
4 2023