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Stephen Raymond Xie
Stephen Raymond Xie
Postdoctoral Researcher, KBR at NASA Ames Research Center
Email verificata su nasa.gov - Home page
Titolo
Citata da
Citata da
Anno
The 2021 Room-Temperature Superconductivity Roadmap
L Boeri, RG Hennig, PJ Hirschfeld, G Profeta, A Sanna, E Zurek, ...
Journal of Physics: Condensed Matter, 2021
146*2021
Fast nastic motion of plants and bioinspired structures
Q Guo, E Dai, X Han, S Xie, E Chao, Z Chen
Journal of the Royal Society Interface 12 (110), 20150598, 2015
1282015
Functional form of the superconducting critical temperature from machine learning
SR Xie, GR Stewart, JJ Hamlin, PJ Hirschfeld, RG Hennig
Physical Review B 100 (17), 174513, 2019
472019
Machine learning of superconducting critical temperature from Eliashberg theory
SR Xie, Y Quan, AC Hire, B Deng, JM DeStefano, I Salinas, US Shah, ...
npj Computational Materials 8 (1), 14, 2022
362022
Machine learning of octahedral tilting in oxide perovskites by symbolic classification with compressed sensing
SR Xie, P Kotlarz, RG Hennig, JC Nino
Computational Materials Science 180, 109690, 2020
232020
Creating superconductivity in WB2 through pressure-induced metastable planar defects
J Lim, AC Hire, Y Quan, JS Kim, SR Xie, S Sinha, RS Kumar, D Popov, ...
Nature communications 13 (1), 7901, 2022
222022
Augmenting machine learning of energy landscapes with local structural information
SJ Honrao, SR Xie, RG Hennig
Journal of Applied Physics 128 (8), 2020
162020
Ultra-fast interpretable machine-learning potentials
SR Xie, M Rupp, RG Hennig
npj Computational Materials 9 (1), 162, 2023
152023
Candidate replacements for lead in CH3NH3PbI3 from first principles calculations
JJ Gabriel, S Xie, K Choudhary, M Sexton, SR Phillpot, J Xue, RG Hennig
Computational Materials Science 155, 69-73, 2018
122018
High-pressure study of the low- rich superconductor
J Lim, AC Hire, Y Quan, J Kim, L Fanfarillo, SR Xie, RS Kumar, C Park, ...
Physical Review B 104 (6), 064505, 2021
42021
Ultra-Fast Force Fields (UF3) framework for machine-learning interatomic potentials
S Xie, R Schmid, M Rupp, R Hennig
APS March Meeting Abstracts 2022, G13. 004, 2022
22022
Computational Design of Low Melting Eutectics of Molten Salts: A Combined Machine Learning and Thermodynamic Modeling Approach
A Ravichandran, S Honrao, S Xie, E Fonseca, JW Lawson
The Journal of Physical Chemistry Letters 15 (1), 121-126, 2023
12023
Stability and magnetic behavior of exfoliable nanowire one-dimensional materials
JT Paul, J Lu, S Shah, SR Xie, RG Hennig
Physical Review Materials 7 (7), 076002, 2023
12023
18. Towards high-throughput superconductor discovery via machine learning
SR Xie, Y Quan, AC Hire, L Fanfarillo, GR Stewart, JJ Hamlin, RG Hennig, ...
The 2021 Room-Temperature Superconductivity Roadmap, 2021
12021
Remarkable low-energy properties of the pseudogapped semimetal
L Fanfarillo, JJ Hamlin, RG Hennig, AC Hire, PJ Hirschfeld, J Kim, J Lim, ...
Physical Review B 102 (15), 155206, 2020
12020
Ultra-fast machine-learning potentials to simulate spin-lattice dynamics of magnetism in iron
M Li, A Hire, S Xie, R Hennig
Bulletin of the American Physical Society, 2024
2024
High-Throughput Screening of Li Solid-State Electrolytes With Bond Valence Methods and Graph Neural Networks
SR Xie, SJ Honrao, JW Lawson
TMS 153rd Annual Meeting & Exhibition, 2024
2024
A Combined Machine Learning and Thermodynamic Modeling Approach for Designing Low Melting Molten Salt Eutectics
A Ravichandran, S Honrao, S Xie, E Fonseca, JW Lawson
2023 AIChE Annual Meeting, 2023
2023
Hierarchical screening for Li-based solid electrolytes using fast, interpretable machine-learned potentials
SR Xie, SJ Honrao, JW Lawson
62nd Sanibel Symposium, 2023
2023
Machine learning and Monte Carlo simulations of the Gibbs free energy of the Fe-C system in a magnetic field
M Li, R Hennig, L Wirth, D Trinkle, A Hire, S Xie, M Campbell
APS March Meeting Abstracts 2023, D44. 002, 2023
2023
Il sistema al momento non può eseguire l'operazione. Riprova più tardi.
Articoli 1–20