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Tom Arbaugh
Tom Arbaugh
Verified email at wesleyan.edu
Title
Cited by
Cited by
Year
Machine learning prediction on the fractional free volume of polymer membranes
L Tao, J He, T Arbaugh, JR McCutcheon, Y Li
Journal of Membrane Science 665, 121131, 2023
142023
Molecular mechanisms of thickness-dependent water desalination in polyamide reverse-osmosis membranes
J He, T Arbaugh, D Nguyen, W Xian, EMV Hoek, JR McCutcheon, Y Li
Journal of Membrane Science 674, 121498, 2023
62023
Unified machine learning protocol for copolymer structure-property predictions
L Tao, T Arbaugh, J Byrnes, V Varshney, Y Li
STAR protocols 3 (4), 101875, 2022
32022
Molecular self-assembled monolayers anomalously enhance thermal conductance across polymer–semiconductor interfaces
J He, L Tao, W Xian, T Arbaugh, Y Li
Nanoscale 14 (47), 17681-17693, 2022
32022
A machine learning interatomic potential for Ge-Te alloys
T Arbaugh, O Dunton, F Starr
Bulletin of the American Physical Society, 2024
2024
Efficient Modelling of Ge15Te85 using Active Learning Methods
T Arbaugh, F Starr
APS March Meeting Abstracts 2023, D02. 012, 2023
2023
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Articles 1–6