Zobrazeno 1 - 10
of 596
pro vyhledávání: '"P. Daymond"'
Autor:
Luo, Yu, Meziere, Jason A., Samolyuk, German D., Hart, Gus L. W., Daymond, Mark R, Béland, Laurent Karim
Machine learning force fields (MLFFs) are an increasingly popular choice for atomistic simulations due to their high fidelity and improvable nature. Here, we propose a hybrid small-cell approach that combines attributes of both offline and active lea
Externí odkaz:
http://arxiv.org/abs/2306.00128
While machine-learned interatomic potentials have become a mainstay for modeling materials, designing training sets that lead to robust potentials is challenging. Automated methods, such as active learning and on-the-fly learning, construct reliable
Externí odkaz:
http://arxiv.org/abs/2304.01314
Autor:
D. C. Williams, A. Riahi, A. Carcea, J. D. Giallonardo, P. Keech, S. Y. Persaud, M. R. Daymond, R. C. Newman
Publikováno v:
npj Materials Degradation, Vol 8, Iss 1, Pp 1-9 (2024)
Abstract Slow strain rate tensile testing was conducted on electrodeposited copper, which is a candidate coating material for used nuclear fuel containers. Embrittlement was observed in electrodeposited copper containing 26.4 ± 1.0 ppm hydrogen, wit
Externí odkaz:
https://doaj.org/article/0f0bc89a4b164b32a220ac6177aa322b
Unlike the vast amount of irradiated material data that exists for stainless steel internals from LWRs, with high fast neutron flux and an irradiation temperature of~330oC, the CANDU reactor is unique with a high thermal spectrum stainless steel comp
Externí odkaz:
http://arxiv.org/abs/2203.02403
Autor:
Saidi, Peyman, Pirgazi, Hadi, Sanjari, Mehdi, Tamimi, Saeed, Mohammadi, Mohsen, Beland, Laurent K., Daymond, Mark R., Tamblyn, Isaac
Efficient and precise prediction of plasticity by data-driven models relies on appropriate data preparation and a well-designed model. Here we introduce an unsupervised machine learning-based data preparation method to maximize the trainability of cr
Externí odkaz:
http://arxiv.org/abs/2106.12730
Autor:
Ferasat, Keyvan, Swinburne, Thomas D., Saidi, Peyman, Daymond, Mark R., Yao, Zhongwen, Béland, Laurent Karim
Publikováno v:
Materialia. 19 (2021) 101180
Neutron irradiation tends to promote disorder in ordered alloys through the action of the thermal spikes that it generates, while simultaneously introducing point defects and defect clusters. As they migrate, these point defects will promote reorderi
Externí odkaz:
http://arxiv.org/abs/2104.11658
Autor:
Tuomas Komulainen, Patrik Daymond, Kristiina E. Hietanen, Ilkka S. Kaartinen, Tero A. H. Järvinen
Publikováno v:
Frontiers in Medicine, Vol 11 (2024)
IntroductionKeloids form as a pathological response to skin wound healing, and their etiopathology is poorly understood. Myofibroblasts, which are cells transformed from normal fibroblasts, are believed to contribute to pathological scar formation in
Externí odkaz:
https://doaj.org/article/78c2083641ed4a5d94a1923c4686c8eb
Autor:
Saidi, Peyman, Changizian, Pooyan, Nicholson, Eric, Zhang, He Ken, Luo, Yu, Yao, Zhongwen, Singh, Chandra Veer, Daymond, Mark R., Beland, Laurent Karim
The order-disorder transition in Ni-Al alloys under irradiation represents an interplay between various re-ordering processes and disordering due to thermal spikes generated by incident high energy particles. Typically, ordering in enabled by diffusi
Externí odkaz:
http://arxiv.org/abs/2002.11659
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