| Simulated annealing with adaptive cooling rates M Karabin, SJ Stuart The Journal of Chemical Physics 153 (11), 2020 | 25 | 2020 |
| An entropy-maximization approach to automated training set generation for interatomic potentials M Karabin, D Perez The Journal of Chemical Physics 153 (9), 2020 | 22 | 2020 |
| Ab initio approaches to high-entropy alloys: a comparison of CPA, SQS, and supercell methods M Karabin, WR Mondal, A Östlin, WGD Ho, V Dobrosavljevic, KM Tam, ... Journal of Materials Science 57 (23), 10677-10690, 2022 | 10 | 2022 |
| ORNL_AISD_NiPt M Karabin, M Lupo Pasini, M Eisenbach Oak Ridge National Lab.(ORNL), Oak Ridge, TN (United States). Oak Ridge …, 2023 | 1 | 2023 |
| Machine learning for first principles calculations of material properties for ferromagnetic materials M Eisenbach, M Karabin, M Lupo Pasini, J Yin Smoky Mountains Computational Sciences and Engineering Conference, 75-86, 2022 | 1 | 2022 |
| Transferring predictions of formation energy across lattices of increasing size ML Pasini, M Karabin, M Eisenbach Machine Learning: Science and Technology 5 (2), 025015, 2024 | | 2024 |
| A deconstructive analysis of charge-transfer and electrostatic field fluctuations to supplement first-principles modeling of disordered metals WG Ho, W Mondal, H Terletska, KM Tam, M Karabin, M Eisenbach, ... Bulletin of the American Physical Society, 2024 | | 2024 |
| Simulation of the homogeneous electron gas on quantum computers J Lietz, A Baroni, P Groszkowski, E Coello Perez, M Karabin, T Morris, ... Bulletin of the American Physical Society, 2024 | | 2024 |
| Mechanism of charge transfer and electrostatic field fluctuations in high entropy metallic alloys WGD Ho, WR Mondal, H Terletska, KM Tam, M Karabin, M Eisenbach, ... arXiv preprint arXiv:2311.14463, 2023 | | 2023 |
| Mechanism governing electronic charge rearrangements in random alloys WG Ho, M Karabin, Y Wang, M Eisenbach, G Stocks, X Liu, W Mondal, ... APS March Meeting Abstracts 2023, D44. 006, 2023 | | 2023 |
| Material properties prediction using machine learning-based ab initio calculations M Karabin, M Eisenbach, M Lupo Pasini, J Yin APS March Meeting Abstracts 2023, T62. 002, 2023 | | 2023 |
| Investigating the properties of the Homogeneous Electron Gas on small-scale quantum computers J Lietz, P Groszkowski, E Coello Perez, M Eisenbach, A Baroni, ... APS March Meeting Abstracts 2023, W64. 008, 2023 | | 2023 |
| A first principles investigation of electronic charge distribution in random alloys Y Wang, M Karabin, M Eisenbach, G Stocks, X Liu, W Mondal, H Terletska, ... APS March Meeting Abstracts 2022, F46. 009, 2022 | | 2022 |
| MuST: A high performance ab initio framework for the study of disordered structures Y Wang, M Eisenbach, X Liu, M Karabin, S Ghosh, H Terletska, W Mondal, ... APS March Meeting Abstracts 2021, F22. 006, 2021 | | 2021 |
| From LSMS to MuST: Large scale first principles materials calculations at the exascale M Eisenbach, X Liu, M Karabin, S Ghosh, Y Wang, H Terletska, W Mondal, ... APS March Meeting Abstracts 2021, S19. 002, 2021 | | 2021 |
| Applying Statistical Mechanics to Improve Computational Sampling Algorithms and Interatomic Potentials M Karabin Clemson University, 2020 | | 2020 |
| Using Thrill to Process Scientific Data on HPC M Karabin, S Suresh, X Chen, I Jimenez, LT Lo, P Grosset | | 2018 |
| Термочутливі полімери блочної та гребенеподібної будови на основі олігопероксидних прекурсорів-макроініціаторів О М’ягкота, А Рябцева, Н Мітіна, М Карабін, Н Кречик, О Заіченко Вісник Національного університету Львівська політехніка. Хімія, технологія …, 2015 | | 2015 |
| NM 87545 USA M Karabin, D Perez | | |
