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pro vyhledávání: '"Thorn, Aidan"'
Publikováno v:
Phys. Chem. Chem. Phys., 2023, 25, 22415-22436
We present our findings of a large-scale screening for new synthesizable materials in five M-Sn binaries, M = Na, Ca, Cu, Pd, and Ag. The focus on these systems was motivated by the known richness of M-Sn properties with potential applications in ene
Externí odkaz:
http://arxiv.org/abs/2306.10223
Publikováno v:
npj Computational Materials volume 8, Article number: 136 (2022)
The Li-Sn binary system has been the focus of extensive research because it features Li-rich alloys with potential applications as battery anodes. Our present re-examination of the binary system with a combination of machine learning and ab initio me
Externí odkaz:
http://arxiv.org/abs/2203.06283
Autor:
Hajinazar, Samad, Thorn, Aidan, Sandoval, Ernesto D., Kharabadze, Saba, Kolmogorov, Aleksey N.
Module for ab initio structure evolution (MAISE) is an open-source package for materials modeling and prediction. The code's main feature is an automated generation of neural network (NN) interatomic potentials for use in global structure searches. T
Externí odkaz:
http://arxiv.org/abs/2005.12131
Autor:
Hajinazar, Samad, Thorn, Aidan, Sandoval, Ernesto D., Kharabadze, Saba, Kolmogorov, Aleksey N.
Publikováno v:
In Computer Physics Communications February 2021 259
Akademický článek
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Autor:
Thorn, Aidan, Rojas-Nunez, Javier, Hajinazar, Samad, Baltazar, Samuel E., Kolmogorov, Aleksey N.
Publikováno v:
The Journal of Physical Chemistry - Part C; December 2019, Vol. 123 Issue: 50 p30088-30098, 11p