Zobrazeno 1 - 10
of 110
pro vyhledávání: '"Aidan A. Thompson"'
Autor:
Lenz Fiedler, Normand A. Modine, Steve Schmerler, Dayton J. Vogel, Gabriel A. Popoola, Aidan P. Thompson, Sivasankaran Rajamanickam, Attila Cangi
Publikováno v:
npj Computational Materials, Vol 9, Iss 1, Pp 1-10 (2023)
Abstract The properties of electrons in matter are of fundamental importance. They give rise to virtually all material properties and determine the physics at play in objects ranging from semiconductor devices to the interior of giant gas planets. Mo
Externí odkaz:
https://doaj.org/article/f472e14ee9f14f318128eada67a6336e
Autor:
David Montes de Oca Zapiain, Mitchell A. Wood, Nicholas Lubbers, Carlos Z. Pereyra, Aidan P. Thompson, Danny Perez
Publikováno v:
npj Computational Materials, Vol 8, Iss 1, Pp 1-9 (2022)
Abstract Advances in machine learning (ML) have enabled the development of interatomic potentials that promise the accuracy of first principles methods and the low-cost, parallel efficiency of empirical potentials. However, ML-based potentials strugg
Externí odkaz:
https://doaj.org/article/2298f107774b44dc8696a59a82489bca
Autor:
Svetoslav Nikolov, Mitchell A. Wood, Attila Cangi, Jean-Bernard Maillet, Mihai-Cosmin Marinica, Aidan P. Thompson, Michael P. Desjarlais, Julien Tranchida
Publikováno v:
npj Computational Materials, Vol 7, Iss 1, Pp 1-12 (2021)
Abstract A data-driven framework is presented for building magneto-elastic machine-learning interatomic potentials (ML-IAPs) for large-scale spin-lattice dynamics simulations. The magneto-elastic ML-IAPs are constructed by coupling a collective atomi
Externí odkaz:
https://doaj.org/article/d348af2bd3da41768c9cb3ef7706b759
Autor:
Jonathan T. Willman, Kien Nguyen-Cong, Ashley S. Williams, Anatoly B. Belonoshko, Stan G. Moore, Aidan P. Thompson, Mitchell A. Wood, Ivan I. Oleynik
Publikováno v:
Physical Review B. 106
A Spectral Neighbor Analysis (SNAP) machine learning interatomic potential (MLIP) has been developed for simulations of carbon at extreme pressures (up to 5 TPa) and temperatures (up to 20,000 K). This was achieved using a large database of experimen
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::51acfff55e3987eb4e17d95882ad2f71
https://doi.org/10.1103/physrevb.106.l180101
https://doi.org/10.1103/physrevb.106.l180101
Autor:
Mitchell Wood, Mihai-Cosmin Marinica, Jean-Bernard Maillet, Michael P. Desjarlais, Aidan P. Thompson, Attila Cangi, Svetoslav Nikolov, Julien Tranchida
Publikováno v:
npj Computational Materials, Vol 7, Iss 1, Pp 1-12 (2021)
A data-driven framework is presented for building magneto-elastic machine-learning interatomic potentials (ML-IAPs) for large-scale spin-lattice dynamics simulations. The magneto-elastic ML-IAPs are constructed by coupling a collective atomic spin mo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b6f6c7a1bbc6d26efbd6e73e8b4d6ff8
https://doaj.org/article/d348af2bd3da41768c9cb3ef7706b759
https://doaj.org/article/d348af2bd3da41768c9cb3ef7706b759
Publikováno v:
Educating Character Through the Arts ISBN: 9781003148852
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7745a575aae7459da72cddb66768a904
https://doi.org/10.4324/9781003148852-1
https://doi.org/10.4324/9781003148852-1
Autor:
John A Mitchell, Fadi Abdeljawad, Corbett Battaile, Cristina Garcia-Cardona, Elizabeth A Holm, Eric R Homer, Jon Madison, Theron M Rodgers, Aidan P Thompson, Veena Tikare, Ed Webb, Steven J Plimpton
Publikováno v:
Modelling and Simulation in Materials Science and Engineering. 31:055001
SPPARKS is an open-source parallel simulation code for developing and running various kinds of on-lattice Monte Carlo models at the atomic or meso scales. It can be used to study the properties of solid-state materials as well as model their dynamic
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6b22d68f48e1635f3d00ac9a35237469
https://doi.org/10.1088/1361-651x/accc4b
https://doi.org/10.1088/1361-651x/accc4b
Autor:
Germain Clavier, Aidan P. Thompson
Publikováno v:
Computer Physics Communications. 286:108674
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ecd46baced61d9f9c112221090240255
https://doi.org/10.1016/j.cpc.2023.108674
https://doi.org/10.1016/j.cpc.2023.108674
Autor:
Aidan P. Thompson
Publikováno v:
SSRN Electronic Journal.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6b53b861ffbc2f64faea5b1911372f5b
https://doi.org/10.2139/ssrn.4207813
https://doi.org/10.2139/ssrn.4207813