| Rapid discovery of stable materials by coordinate-free coarse graining REA Goodall, AS Parackal, FA Faber, R Armiento, AA Lee Science advances 8 (30), eabn4117, 2022 | 34 | 2022 |
| Wyckoff Set Regression for Materials Discovery REA Goodall, AS Parackal, FA Faber, R Armiento Neural Information Processing Systems 7, 2020 | 3 | 2020 |
| Na in diamond: High spin defects revealed by the ADAQ high-throughput computational database J Davidsson, W Stenlund, AS Parackal, R Armiento, IA Abrikosov npj Computational Materials 10 (1), 109, 2024 | 1 | 2024 |
| Evaluating and improving the predictive accuracy of mixing enthalpies and volumes in disordered alloys from universal pre-trained machine learning potentials L Casillas-Trujillo, AS Parackal, R Armiento, B Alling arXiv preprint arXiv:2406.17499, 2024 | | 2024 |
| Inverting unidentified X-ray Powder Diffraction Spectra through Machine Learning-Driven Prototype enumeration AS Parackal | | 2024 |
| Identifying Crystal Structures Beyond Known Prototypes from X-ray Powder Diffraction Spectra AS Parackal, REA Goodall, FA Faber, R Armiento arXiv e-prints, arXiv: 2309.16454, 2023 | | 2023 |
| Screening the unexplored crystal prototype space and inverting XRD patterns with the WREN machine-learning model R Armiento, A Parackal, R Goodall, F Faber APS March Meeting Abstracts 2023, A53. 001, 2023 | | 2023 |
| Coordinate-free representation of crystals for accelerated materials discovery using machine learning. R Goodall, A Parackal, F Faber, R Armiento APS March Meeting Abstracts 2022, M47. 008, 2022 | | 2022 |
Rickard ArmientoLinköping UniversityVerified email at liu.se
