Spin–phonon couplings in transition metal complexes with slow magnetic relaxation DH Moseley, SE Stavretis, K Thirunavukkuarasu, M Ozerov, Y Cheng, ... Nature communications 9 (1), 2572, 2018 | 112 | 2018 |
Evolution of amorphous carbon across densities: An inferential study B Bhattarai, A Pandey, DA Drabold Carbon 131, 168-174, 2018 | 71 | 2018 |
Inversion of diffraction data for amorphous materials A Pandey, P Biswas, DA Drabold Scientific Reports 6 (1), 33731, 2016 | 71 | 2016 |
Machine learning based surrogate modeling approach for mapping crystal deformation in three dimensions A Pandey, R Pokharel Scripta Materialia 193, 1-5, 2021 | 56 | 2021 |
Force-enhanced atomic refinement: Structural modeling with interatomic forces in a reverse Monte Carlo approach applied to amorphous Si and A Pandey, P Biswas, DA Drabold Physical Review B 92 (15), 155205, 2015 | 54 | 2015 |
Inelastic neutron scattering evidence for anomalous H–H distances in metal hydrides A Borgschulte, J Terreni, E Billeter, L Daemen, Y Cheng, A Pandey, ... Proceedings of the National Academy of Sciences 117 (8), 4021-4026, 2020 | 36 | 2020 |
The effect of porosity and microcracking on the thermomechanical properties of cordierite A Shyam, G Bruno, TR Watkins, A Pandey, E Lara-Curzio, CM Parish, ... Journal of the European Ceramic Society 35 (16), 4557-4566, 2015 | 34 | 2015 |
Realistic inversion of diffraction data for an amorphous solid: The case of amorphous silicon A Pandey, P Biswas, B Bhattarai, DA Drabold Physical Review B 94 (23), 235208, 2016 | 33 | 2016 |
Electrical activity of boron and phosphorus in hydrogenated amorphous silicon A Pandey, B Cai, N Podraza, DA Drabold Physical Review Applied 2 (5), 054005, 2014 | 22 | 2014 |
Physics-informed data-driven surrogate modeling for full-field 3D microstructure and micromechanical field evolution of polycrystalline materials R Pokharel, A Pandey, A Scheinker JOM 73 (11), 3371-3382, 2021 | 13 | 2021 |
Machine learning enabled surrogate crystal plasticity model for spatially resolved 3d orientation evolution under uniaxial tension A Pandey, R Pokharel arXiv preprint arXiv:2005.00951, 2020 | 13 | 2020 |
Density functional theory model of amorphous zinc oxide (a-ZnO) and a-X0. 375Z0. 625O (X= Al, Ga and In) A Pandey, H Scherich, DA Drabold Journal of Non-Crystalline Solids 455, 98-101, 2017 | 12 | 2017 |
Exposing Key Vibrational Contributions to Properties of Organic Molecular Solids with High Signal, Low Frequency Neutron Spectroscopy and Ab Initio Simulations A Pandey, A Sedova, LL Daemen, Y Cheng, AJ Ramirez-Cuesta Crystal Growth & Design 18 (9), 4815-4821, 2018 | 6 | 2018 |
Molecular Dynamics Study of Diffusion of Different Inert Gases Like Neon and Argon in Water at Different Temperatures HB Moktan, A Panday, NP Adhikari International Journal of Modern Physics B 26 (03), 1250016, 2012 | 6 | 2012 |
Machine learning interatomic potential for high-throughput screening of high-entropy alloys A Pandey, J Gigax, R Pokharel JOM 74 (8), 2908-2920, 2022 | 5 | 2022 |
Theoretical study of alkali-metal hydrides at high pressures: a case of NaH supported by inelastic neutron scattering (INS) experiments at 1 and 2 GPa A Pandey, J Zhang, Y Cheng, L Daemen, AJ Ramirez-Cuesta The Journal of Physical Chemistry A 123 (46), 10079-10085, 2019 | 2 | 2019 |
Machine learning interatomic potential for high throughput screening and optimization of high-entropy alloys A Pandey, J Gigax, R Pokharel arXiv preprint arXiv:2201.08906, 2022 | 1 | 2022 |
Periodic DFT calculations of vibrational and molecular dynamics on large organic molecular systems using olcf computers A Sedova, A Pandey, MD Smith | 1 | 2018 |
Best of Both Worlds: Enforcing Detailed Balance in Machine Learning Models of Transition Rates AA Talapatra, A Pandey, MS Wilson, YW Li, G Pilania, BP Uberuaga, ... arXiv preprint arXiv:2409.12284, 2024 | | 2024 |
Capabilities and Advantages of the GasModels Package S Srinivasan, K Sundar, SKK Hari, A Zlotnik, A Pandey, M Ewers, D Fobes, ... PSIG Annual Meeting, PSIG-2414, 2024 | | 2024 |