| On the use of SRIM for computing radiation damage exposure RE Stoller, MB Toloczko, GS Was, AG Certain, S Dwaraknath, FA Garner Nuclear instruments and methods in physics research section B: beam …, 2013 | 1348 | 2013 |
| Accelerating the discovery of materials for clean energy in the era of smart automation DP Tabor, LM Roch, SK Saikin, C Kreisbeck, D Sheberla, JH Montoya, ... Nature reviews materials 3 (5), 5-20, 2018 | 584 | 2018 |
| Atomate: A high-level interface to generate, execute, and analyze computational materials science workflows K Mathew, JH Montoya, A Faghaninia, S Dwarakanath, M Aykol, H Tang, ... Computational Materials Science 139, 140-152, 2017 | 281 | 2017 |
| Thermodynamic limit for synthesis of metastable inorganic materials M Aykol, SS Dwaraknath, W Sun, KA Persson Science advances 4 (4), eaaq0148, 2018 | 250 | 2018 |
| High-throughput density-functional perturbation theory phonons for inorganic materials G Petretto, S Dwaraknath, H PC Miranda, D Winston, M Giantomassi, ... Scientific data 5 (1), 1-12, 2018 | 141 | 2018 |
| Computational approach for epitaxial polymorph stabilization through substrate selection H Ding, SS Dwaraknath, L Garten, P Ndione, D Ginley, KA Persson ACS applied materials & interfaces 8 (20), 13086-13093, 2016 | 89 | 2016 |
| The existence and impact of persistent ferroelectric domains in MAPbI3 LM Garten, DT Moore, SU Nanayakkara, S Dwaraknath, P Schulz, ... Science advances 5 (1), eaas9311, 2019 | 86 | 2019 |
| OPTIMADE, an API for exchanging materials data CW Andersen, R Armiento, E Blokhin, GJ Conduit, S Dwaraknath, ... Scientific data 8 (1), 217, 2021 | 68 | 2021 |
| A framework for quantifying uncertainty in DFT energy corrections A Wang, R Kingsbury, M McDermott, M Horton, A Jain, SP Ong, ... Scientific reports 11 (1), 15496, 2021 | 63 | 2021 |
| Assessing high-throughput descriptors for prediction of transparent conductors R Woods-Robinson, D Broberg, A Faghaninia, A Jain, SS Dwaraknath, ... Chemistry of Materials 30 (22), 8375-8389, 2018 | 62 | 2018 |
| Multiple ion beam irradiation for the study of radiation damage in materials S Taller, D Woodley, E Getto, AM Monterrosa, Z Jiao, O Toader, F Naab, ... Nuclear Instruments and Methods in Physics Research Section B: Beam …, 2017 | 55 | 2017 |
| A graph-based network for predicting chemical reaction pathways in solid-state materials synthesis MJ McDermott, SS Dwaraknath, KA Persson Nature communications 12 (1), 3097, 2021 | 54 | 2021 |
| BonDNet: a graph neural network for the prediction of bond dissociation energies for charged molecules M Wen, SM Blau, EWC Spotte-Smith, S Dwaraknath, KA Persson Chemical science 12 (5), 1858-1868, 2021 | 52 | 2021 |
| Propnet: a knowledge graph for materials science D Mrdjenovich, MK Horton, JH Montoya, CM Legaspi, S Dwaraknath, ... Matter 2 (2), 464-480, 2020 | 46 | 2020 |
| Toward a mechanistic model of solid–electrolyte interphase formation and evolution in lithium-ion batteries EWC Spotte-Smith, RL Kam, D Barter, X Xie, T Hou, S Dwaraknath, ... ACS Energy Letters 7 (4), 1446-1453, 2022 | 42 | 2022 |
| A chemically consistent graph architecture for massive reaction networks applied to solid-electrolyte interphase formation SM Blau, HD Patel, EWC Spotte-Smith, X Xie, S Dwaraknath, KA Persson Chemical science 12 (13), 4931-4939, 2021 | 41 | 2021 |
| The materials project: Accelerating materials design through theory-driven data and tools A Jain, J Montoya, S Dwaraknath, NER Zimmermann, J Dagdelen, ... Handbook of Materials Modeling: Methods: Theory and Modeling, 1751-1784, 2020 | 41 | 2020 |
| Performance comparison of and SCAN metaGGA density functionals for solid materials via an automated, high-throughput computational workflow R Kingsbury, AS Gupta, CJ Bartel, JM Munro, S Dwaraknath, M Horton, ... Physical Review Materials 6 (1), 013801, 2022 | 37 | 2022 |
| Evaluation of thermodynamic equations of state across chemistry and structure in the materials project K Latimer, S Dwaraknath, K Mathew, D Winston, KA Persson npj Computational Materials 4 (1), 40, 2018 | 30 | 2018 |
| Harnessing the Materials Project for machine-learning and accelerated discovery W Ye, C Chen, S Dwaraknath, A Jain, SP Ong, KA Persson MRS Bulletin 43 (9), 664-669, 2018 | 28 | 2018 |
Kristin Aslaug Persson (nee Einarsdott...Department of Materials Science and Engineering, UC BerkeleyVerified email at berkeley.edu
