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Alpha Lee
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The electrostatic screening length in concentrated electrolytes increases with concentration
AM Smith, AA Lee, S Perkin
The journal of physical chemistry letters 7 (12), 2157-2163, 2016
3852016
Molecular transformer: a model for uncertainty-calibrated chemical reaction prediction
P Schwaller, T Laino, T Gaudin, P Bolgar, CA Hunter, C Bekas, AA Lee
ACS central science 5 (9), 1572-1583, 2019
3212019
Long range electrostatic forces in ionic liquids
MA Gebbie, AM Smith, HA Dobbs, GG Warr, X Banquy, M Valtiner, ...
Chemical communications 53 (7), 1214-1224, 2017
2712017
Identifying degradation patterns of lithium ion batteries from impedance spectroscopy using machine learning
Y Zhang, Q Tang, Y Zhang, J Wang, U Stimming, AA Lee
Nature Communications 11, 1706, 2020
1742020
Scaling analysis of the screening length in concentrated electrolytes
AA Lee, CS Perez-Martinez, AM Smith, S Perkin
Physical review letters 119 (2), 026002, 2017
1492017
Are room-temperature ionic liquids dilute electrolytes?
AA Lee, D Vella, S Perkin, A Goriely
The journal of physical chemistry letters 6 (1), 159-163, 2015
1272015
Alternative radical pairs for cryptochrome-based magnetoreception
AA Lee, JCS Lau, HJ Hogben, T Biskup, DR Kattnig, PJ Hore
Journal of The Royal Society Interface 11 (95), 20131063, 2014
1112014
Underscreening in concentrated electrolyes
AA Lee, C Perez-Martinez, AM Smith, S Perkin
107*2017
Underscreening in concentrated electrolytes
AA Lee, C Perez-Martinez, AM Smith, S Perkin
Faraday Discussions, 2017
1052017
Predicting materials properties without crystal structure: Deep representation learning from stoichiometry
REA Goodall, AA Lee
Nature communications 11 (1), 1-9, 2020
822020
Switching the structural force in ionic liquid-solvent mixtures by varying composition
AM Smith, AA Lee, S Perkin
Physical Review Letters 118 (9), 096002, 2017
772017
Crowdsourcing drug discovery for pandemics
J Chodera, AA Lee, N London, F von Delft
Nature Chemistry 12 (7), 581-581, 2020
692020
Bayesian semi-supervised learning for uncertainty-calibrated prediction of molecular properties and active learning
Y Zhang
Chemical science 10 (35), 8154-8163, 2019
602019
Molecular transformer unifies reaction prediction and retrosynthesis across pharma chemical space
AA Lee, Q Yang, V Sresht, P Bolgar, X Hou, JL Klug-McLeod, CR Butler
Chemical Communications 55 (81), 12152-12155, 2019
592019
Dynamics of Ion Transport in Ionic Liquids
AA Lee, S Kondrat, D Vella, A Goriely
Physical review letters 115 (10), 106101, 2015
59*2015
Single-file charge storage in conducting nanopores
AA Lee, S Kondrat, AA Kornyshev
Physical review letters 113 (4), 048701, 2014
592014
Energy–entropy competition and the effectiveness of stochastic gradient descent in machine learning
Y Zhang, AM Saxe, MS Advani, AA Lee
Molecular Physics 116 (21-22), 3214-3223, 2018
492018
Charging dynamics of supercapacitors with narrow cylindrical nanopores
AA Lee, S Kondrat, G Oshanin, AA Kornyshev
Nanotechnology 25 (31), 315401, 2014
452014
Interionic interactions in conducting nanoconfinement
CC Rochester, AA Lee, G Pruessner, AA Kornyshev
ChemPhysChem 14 (18), 4121-4125, 2013
372013
Interionic interactions in conducting nanoconfinement
CC Rochester, AA Lee, G Pruessner, AA Kornyshev
ChemPhysChem 14 (18), 4121-4125, 2013
372013
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