Machine learning-driven atomistic analysis of mechanical behavior in silicon nanowires

Zare Pakzad, Sina, Nasr Esfahani, Mohammad orcid.org/0000-0002-6973-2205, Canadinc, Demircan et al. (1 more author) (2025) Machine learning-driven atomistic analysis of mechanical behavior in silicon nanowires. Computational Materials Science. 113446. ISSN 0927-0256

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Item Type: Article
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Keywords: Machine learning,Modulus of elasticity,Molecular dynamics,Silicon nanowire,Tensile behavior
Dates:
  • Published: 1 January 2025
  • Published (online): 23 October 2024
  • Accepted: 9 October 2024
Institution: The University of York
Academic Units: The University of York > Faculty of Sciences (York) > Electronic Engineering (York)
Depositing User: Pure (York)
Date Deposited: 03 Jan 2025 13:00
Last Modified: 03 Jan 2025 13:00
Published Version: https://doi.org/10.1016/j.commatsci.2024.113446
Status: Published
Refereed: Yes
Identification Number: 10.1016/j.commatsci.2024.113446
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Licence: CC-BY 2.5

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