Zobrazeno 1 - 10
of 104
pro vyhledávání: '"Eric R Homer"'
Publikováno v:
Nova Religio: The Journal of Alternative and Emergent Religions, 2017 Aug 01. 21(1), 130-131.
Externí odkaz:
https://www.jstor.org/stable/26417777
Autor:
Eric R. Homer, Oliver K. Johnson, Darcey Britton, James E. Patterson, Eric T. Sevy, Gregory B. Thompson
Publikováno v:
npj Computational Materials, Vol 8, Iss 1, Pp 1-9 (2022)
Abstract Observations of microstructural coarsening at cryogenic temperatures, as well as numerous simulations of grain boundary motion that show faster migration at low temperature than at high temperature, have been troubling because they do not fo
Externí odkaz:
https://doaj.org/article/81fa27cdc68942a58943d66f2bb22b5a
Autor:
Olivia P. Pfeiffer, Haihao Liu, Luca Montanelli, Marat I. Latypov, Fatih G. Sen, Vishwanath Hegadekatte, Elsa A. Olivetti, Eric R. Homer
Publikováno v:
Scientific Data, Vol 9, Iss 1, Pp 1-9 (2022)
Measurement(s) chemical composition of aluminum alloys • mechanical properties of aluminum alloys Technology Type(s) natural language processing
Externí odkaz:
https://doaj.org/article/aca5179ed8e0439f92045164a0dd2a7d
Publikováno v:
MethodsX, Vol 9, Iss , Pp 101731- (2022)
We present a method for performing efficient barycentric interpolation for large grain boundary octonion point sets which reside on the surface of a hypersphere. This method includes removal of degenerate dimensions via singular value decomposition (
Externí odkaz:
https://doaj.org/article/556843885b2043c98df56e7aa70275f4
Publikováno v:
MethodsX, Vol 5, Iss , Pp 1187-1203 (2018)
One of the limitations of atomistic simulations is that many of the computational tools used to extract structural information from atomic trajectories provide metrics that are not directly compatible with experiments for validation. In this work, to
Externí odkaz:
https://doaj.org/article/7327db15855e49adbf5129363e146fbd
Autor:
Landon T Hansen, Jay D Carroll, Eric R Homer, Robert H Wagoner, Guowei Zhou, David T Fullwood
Publikováno v:
Microscopy and Microanalysis.
Geometrically necessary dislocations (GNDs) play a key role in accommodating strain incompatibility between neighboring grains in polycrystalline materials. One critical step toward accurately capturing GNDs in deformation models involves studying th
Publikováno v:
npj Computational Materials, Vol 3, Iss 1, Pp 1-7 (2017)
Machine learning: Modelling atomic systems to make property predictions A method for representing atomic systems for machine learning is shown that can provide access to the physical properties of these systems. Machine learning is a powerful tool fo
Externí odkaz:
https://doaj.org/article/b71a7a9a5df64438a53ef378aa2fd64e
Publikováno v:
Frontiers in Materials, Vol 6 (2019)
The atomic structure of grain boundaries plays a defining but poorly understood role in the properties they exhibit. Due to the complex nature of these structures, machine learning is a natural tool for extracting meaningful relationships and new phy
Externí odkaz:
https://doaj.org/article/aa1baa2249494bd5bcd04b69b1242cd8
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
Nanotwin stability in alloyed copper under ambient and cryo-temperature dependent deformation states
Publikováno v:
Materials Science and Engineering: A. 871:144866