Fatih Sen
Affiliations: | 2014-2017 | Argonne National Laboratory, Lemont, IL, United States |
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| Mannodi-Kanakkithodi A, Toriyama MY, Sen FG, et al. (2020) Machine-learned impurity level prediction for semiconductors: the example of Cd-based chalcogenides Npj Computational Materials. 6 |
| Paulauskas T, Sen FG, Sun C, et al. (2019) Stabilization of a monolayer tellurene phase at CdTe interfaces. Nanoscale |
| Guo J, Mannodi-Kanakkithodi A, Sen FG, et al. (2019) Effect of selenium and chlorine co-passivation in polycrystalline CdSeTe devices Applied Physics Letters. 115: 153901 |
| Chan H, Narayanan B, Cherukara MJ, et al. (2019) Machine Learning Classical Interatomic Potentials for Molecular Dynamics from First-Principles Training Data The Journal of Physical Chemistry C. 123: 6941-6957 |
| Guo J, Sen FG, Mannodi-Kannakithodi A, et al. (2019) Study of Effects of Cl and Se in CdSeTe Solar Cells Using Scanning Transmission Electron Microscopy Microscopy and Microanalysis. 25: 2150-2151 |
| Chong L, Wen J, Kubal J, et al. (2018) Ultralow-loading platinum-cobalt fuel cell catalysts derived from imidazolate frameworks. Science (New York, N.Y.) |
| Schwenker E, Sen F, Ophus C, et al. (2018) An Autonomous Microscopy Workflow for Structure Determination from Atomic-Resolution Images Microscopy and Microanalysis. 24: 510-511 |
| Guo J, Sen FG, Wang L, et al. (2018) Atomic-Resolution Study of Grain Boundaries in CdTe Using Scanning Transmission Electron Microscopy Microscopy and Microanalysis. 24: 102-103 |
| Narayanan B, Chan H, Kinaci A, et al. (2017) Machine learnt bond order potential to model metal-organic (Co-C) heterostructures. Nanoscale |
| Li Y, Li H, Pickard FC, et al. (2017) Machine Learning Force Field Parameters from Ab Initio Data. Journal of Chemical Theory and Computation |