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Abhijith Parackal
Abhijith Parackal
在 liu.se 的电子邮件经过验证 - 首页
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引用次数
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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
382022
Wyckoff Set Regression for Materials Discovery
REA Goodall, AS Parackal, FA Faber, R Armiento
Neural Information Processing Systems 7, 2020
32020
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
22024
Identifying crystal structures beyond known prototypes from x-ray powder diffraction spectra
AS Parackal, REA Goodall, FA Faber, R Armiento
Physical Review Materials 8 (10), 103801, 2024
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
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
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