Accelerated discovery of CO2 electrocatalysts using active machine learning M Zhong, K Tran, Y Min, C Wang, Z Wang, CT Dinh, P De Luna, Z Yu, ... Nature 581 (7807), 178-183, 2020 | 1099 | 2020 |
Active learning across intermetallics to guide discovery of electrocatalysts for CO2 reduction and H2 evolution K Tran, ZW Ulissi Nature Catalysis 1 (9), 696-703, 2018 | 714 | 2018 |
Open catalyst 2020 (OC20) dataset and community challenges L Chanussot, A Das, S Goyal, T Lavril, M Shuaibi, M Riviere, K Tran, ... ACS Catalysis 11 (10), 6059-6072, 2021 | 527 | 2021 |
Convolutional neural network of atomic surface structures to predict binding energies for high-throughput screening of catalysts S Back, J Yoon, N Tian, W Zhong, K Tran, ZW Ulissi The journal of physical chemistry letters 10 (15), 4401-4408, 2019 | 215 | 2019 |
Methods for comparing uncertainty quantifications for material property predictions K Tran, W Neiswanger, J Yoon, Q Zhang, E Xing, ZW Ulissi Machine Learning: Science and Technology 1 (2), 025006, 2020 | 206 | 2020 |
Toward a design of active oxygen evolution catalysts: insights from automated density functional theory calculations and machine learning S Back, K Tran, ZW Ulissi Acs Catalysis 9 (9), 7651-7659, 2019 | 160 | 2019 |
An introduction to electrocatalyst design using machine learning for renewable energy storage CL Zitnick, L Chanussot, A Das, S Goyal, J Heras-Domingo, C Ho, W Hu, ... arXiv preprint arXiv:2010.09435, 2020 | 88 | 2020 |
Toward predicting intermetallics surface properties with high-throughput DFT and convolutional neural networks A Palizhati, W Zhong, K Tran, S Back, ZW Ulissi Journal of chemical information and modeling 59 (11), 4742-4749, 2019 | 64 | 2019 |
Discovery of acid-stable oxygen evolution catalysts: high-throughput computational screening of equimolar bimetallic oxides S Back, K Tran, ZW Ulissi ACS applied materials & interfaces 12 (34), 38256-38265, 2020 | 63 | 2020 |
Dynamic workflows for routine materials discovery in surface science K Tran, A Palizhati, S Back, ZW Ulissi Journal of chemical information and modeling 58 (12), 2392-2400, 2018 | 52 | 2018 |
Parallelized screening of characterized and DFT-modeled bimetallic colloidal cocatalysts for photocatalytic hydrogen evolution EM Lopato, EA Eikey, ZC Simon, S Back, K Tran, J Lewis, JF Kowalewski, ... ACS Catalysis 10 (7), 4244-4252, 2020 | 47 | 2020 |
Controllability analysis of protein glycosylation in CHO cells MM St. Amand, K Tran, D Radhakrishnan, AS Robinson, BA Ogunnaike PloS one 9 (2), e87973, 2014 | 47 | 2014 |
Computational catalyst discovery: Active classification through myopic multiscale sampling K Tran, W Neiswanger, K Broderick, E Xing, J Schneider, ZW Ulissi The Journal of Chemical Physics 154 (12), 2021 | 15 | 2021 |
In silico discovery of active, stable, CO-tolerant and cost-effective electrocatalysts for hydrogen evolution and oxidation S Back, J Na, K Tran, ZW Ulissi Physical Chemistry Chemical Physics 22 (35), 19454-19458, 2020 | 15 | 2020 |
Optimization-based design of active and stable nanostructured surfaces CL Hanselman, W Zhong, K Tran, ZW Ulissi, CE Gounaris The Journal of Physical Chemistry C 123 (48), 29209-29218, 2019 | 14 | 2019 |
Correction to “The Open Catalyst 2020 (OC20) Dataset and Community Challenges” L Chanussot, A Das, S Goyal, T Lavril, M Shuaibi, M Riviere, K Tran, ... ACS Catalysis 11 (21), 13062-13065, 2021 | 9 | 2021 |
Correction to “The Open Catalyst 2020 (OC20) Dataset and Community Challenges” L Chanussot, A Das, S Goyal, T Lavril, M Shuaibi, M Riviere, K Tran, ... ACS Catalysis 11 (21), 13062-13065, 2021 | 9 | 2021 |
The open catalyst 2020 (oc20) dataset and community challenges (vol 11, pg 6059, 2021) L Chanussot, A Das, S Goyal, T Lavril, M Shuaibi, M Riviere, K Tran, ... ACS CATALYSIS 11 (21), 13062-13065, 2021 | 3* | 2021 |
Advancing Insights into Electrochemical Pre‐Treatments of Supported Nanoparticle Electrocatalysts by Combining a Design of Experiments Strategy with In Situ Characterization AS Mule, K Tran, AM Aleman, YE Cornejo‐Carrillo, GA Kamat, ... Advanced Energy Materials 14 (41), 2401939, 2024 | 1 | 2024 |
Predicting Intermetallic Surface Energies with High-Throughput DFT and Convolutional Neural Networks A Palizhati, W Zhong, K Tran, Z Ulissi | 1 | 2019 |