Mo–Si Alloys Studied by Atomistic Computer Simulations Using a Novel Machine‐Learning Interatomic Potential: Thermodynamics and Interface Phenomena

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Location: Deutsche Nationalbibliothek Frankfurt am Main

Extent: Online-Ressource

Language: Englisch

Bibliographic citation: In: Advanced Engineering Materials, 26, (17), Wiley-VCH, ISSN 1438-1656

Event: Veröffentlichung

(where): Darmstadt

(who): Universitäts- und Landesbibliothek

(when): 2024

Creator: Lenchuk, Olena
Rohrer, Jochen
Albe, Karsten

DOI: 10.26083/tuprints-00028276

URN: urn:nbn:de:tuda-tuprints-282760

Rights: Der Zugriff auf das Objekt ist unbeschränkt möglich.

Last update: 15.08.2025, 7:37 AM CEST

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Lenchuk, Olena
Rohrer, Jochen
Albe, Karsten
Universitäts- und Landesbibliothek

Time of origin

2024

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Mo–Si Alloys Studied by Atomistic Computer Simulations Using a Novel Machine‐Learning Interatomic Potential: Thermodynamics and Interface Phenomena

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Other Objects (12)

Mo–Si Alloys Studied by Atomistic Computer Simulations Using a Novel Machine‐Learning Interatomic Potential: Thermodynamics and Interface Phenomena

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Mo–Si Alloys Studied by Atomistic Computer Simulations Using a Novel Machine‐Learning Interatomic Potential: Thermodynamics and Interface Phenomena

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First-Principles Multiscale Modeling of Mechanical Properties in Graphene/Borophene Heterostructures Empowered by Machine-Learning Interatomic Potentials

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Atomistic simulations of Ag–Cu–Sn alloys based on a new modified embedded-atom method interatomic potential

Atomistic insights into adhesion characteristics of tungsten on titanium nitride using steered molecular dynamics with machine learning interatomic potential

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