| AiiDA 1.0, a scalable computational infrastructure for automated reproducible workflows and data provenance SP Huber, S Zoupanos, M Uhrin, L Talirz, L Kahle, R Häuselmann, ... Scientific data 7 (1), 300, 2020 | 218 | 2020 |
| High-throughput computational screening for solid-state Li-ion conductors L Kahle, A Marcolongo, N Marzari Energy & Environmental Science 13 (3), 928-948, 2020 | 101 | 2020 |
| Modeling lithium-ion solid-state electrolytes with a pinball model L Kahle, A Marcolongo, N Marzari Physical Review Materials 2 (6), 065405, 2018 | 39 | 2018 |
| Unsupervised landmark analysis for jump detection in molecular dynamics simulations L Kahle, A Musaelian, N Marzari, B Kozinsky Physical Review Materials 3 (5), 055404, 2019 | 37 | 2019 |
| Workflow Engineering in Materials Design within the BATTERY 2030+ Project J Schaarschmidt, J Yuan, T Strunk, I Kondov, SP Huber, G Pizzi, L Kahle, ... Advanced Energy Materials 12 (17), 2102638, 2022 | 32 | 2022 |
| Quality of uncertainty estimates from neural network potential ensembles L Kahle, F Zipoli Physical Review E 105 (1), 015311, 2022 | 23 | 2022 |
| Li4–xGe1–xPxO4, a Potential Solid-State Electrolyte for All-Oxide Microbatteries E Gilardi, G Materzanini, L Kahle, M Dobeli, S Lacey, X Cheng, N Marzari, ... ACS Applied Energy Materials 3 (10), 9910-9917, 2020 | 11 | 2020 |
| High Li-ion conductivity in tetragonal LGPO: A comparative first-principles study against known LISICON and LGPS phases G Materzanini, L Kahle, A Marcolongo, N Marzari Physical Review Materials 5 (3), 035408, 2021 | 10 | 2021 |
| The solid-state Li-ion conductor Li7TaO6: A combined computational and experimental study L Kahle, X Cheng, T Binninger, SD Lacey, A Marcolongo, F Zipoli, ... Solid State Ionics 347, 115226, 2020 | 7 | 2020 |
| AiiDA 1.0, a scalable computational infrastructure for automated reproducible workflows and data provenance. Sci Data 7: 300 SP Huber, S Zoupanos, M Uhrin, L Talirz, L Kahle, R Häuselmann, ... | 6 | 2020 |
| Prediction of phase diagrams and associated phase structural properties F Zipoli, V Viterbo, O Schilter, L Kahle, T Laino Industrial & Engineering Chemistry Research 61 (24), 8378-8389, 2022 | 5 | 2022 |
| Learning a reactive potential for silica-water through uncertainty attribution S Roy, JP Dürholt, TS Asche, F Zipoli, R Gómez-Bombarelli arXiv preprint arXiv:2307.01705, 2023 | 1 | 2023 |
| Conductivity, elastic moduli and phase transitions in the Li10GeP2O12 solid-state electrolyte from first-principles molecular dynamics G Materzanini, L Kahle, A Marcolongo, N Marzari APS March Meeting Abstracts 2021, J56. 009, 2021 | | 2021 |
| Electrolytes for Li-ion all-solid-state batteries: a first-principles comparative study of Li10GeP2O12 and Li10GeP2S12 in the LISICON and LGPS phases G Materzanini, L Kahle, A Marcolongo, N Marzari arXiv preprint arXiv:2010.08068, 2020 | | 2020 |
| Comparison of Correlated Li+ Diffusion from Molecular Dynamics of Promising Solid Electrolytes N Adelstein, VYZ Wei, Z Mehmedović, A Grieder, N Leclerc, A Musaelian, ... Electrochemical Society Meeting Abstracts 236, 701-701, 2019 | | 2019 |
| Modeling, understanding, and screening fast lithium-ion conductors for solid-state electrolytes L Kahle EPFL, 2019 | | 2019 |
| Computational screening of experimental structural repositories for novel Li-ion conductors L Kahle, A Marcolongo, N Marzari APS March Meeting Abstracts 2019, K18. 007, 2019 | | 2019 |
| Fast screening of solid-state lithium-ion conductors L Kahle, A Marcolongo, N Marzari APS March Meeting Abstracts 2018, K12. 003, 2018 | | 2018 |
Nicola MarzariÉcole Polytechnique Fédérale de Lausanne (EPFL), and Paul Scherrer Institut (PSI)Adresse e-mail validée de epfl.ch
