Lenchuk, Olena ; Rohrer, Jochen ; Albe, Karsten (2024)
Mo–Si Alloys Studied by Atomistic Computer Simulations Using a Novel Machine‐Learning Interatomic Potential: Thermodynamics and Interface Phenomena.
In: Advanced Engineering Materials, 2024, 26 (17)
doi: 10.26083/tuprints-00028276
Article, Secondary publication, Publisher's Version
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Item Type: | Article |
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Type of entry: | Secondary publication |
Title: | Mo–Si Alloys Studied by Atomistic Computer Simulations Using a Novel Machine‐Learning Interatomic Potential: Thermodynamics and Interface Phenomena |
Language: | English |
Date: | 19 November 2024 |
Place of Publication: | Darmstadt |
Year of primary publication: | September 2024 |
Place of primary publication: | Weinheim |
Publisher: | Wiley-VCH |
Journal or Publication Title: | Advanced Engineering Materials |
Volume of the journal: | 26 |
Issue Number: | 17 |
Collation: | 12 Seiten |
DOI: | 10.26083/tuprints-00028276 |
Corresponding Links: | |
Origin: | Secondary publication DeepGreen |
Abstract: | A machine‐learning interatomic potential for Mo–Si alloys based on the atomic cluster expansion formalism is presented, its performance is validated, and it is applied for studying interface phenomena. Structural parameters, elastic constants, and melting temperatures of the crystalline body‐centered cubic Mo, diamond Si, and stable Mo–Si alloys (Mo₃Si, Mo₅Si₃, and MoSi₂) are calculated and compared to experimental values. Using the trained potential defect, formation energies are calculated and the thermodynamic stability of various MoxSiy alloys is discussed with focus on Mo₃Si. Finally, the intermixing between Mo and Si phases is studied by performing interface simulations of Mo|Si. The crystallization behavior of the Mo₃Si phase provides additional evidence for the off‐stoichiometric composition of this intermetallic phase. |
Uncontrolled Keywords: | machine‐learning interatomic potentials, molecular dynamics, Mo–Si alloys, refractory alloys |
Identification Number: | Artikel-ID: 2302043 |
Status: | Publisher's Version |
URN: | urn:nbn:de:tuda-tuprints-282760 |
Additional Information: | Special Issue: Materials Compounds from Composite Materials for Applications in Extreme Conditions |
Classification DDC: | 500 Science and mathematics > 540 Chemistry 600 Technology, medicine, applied sciences > 620 Engineering and machine engineering 600 Technology, medicine, applied sciences > 660 Chemical engineering |
Divisions: | 11 Department of Materials and Earth Sciences > Material Science > Materials Modelling |
Date Deposited: | 19 Nov 2024 12:26 |
Last Modified: | 05 Dec 2024 12:02 |
SWORD Depositor: | Deep Green |
URI: | https://tuprints.ulb.tu-darmstadt.de/id/eprint/28276 |
PPN: | 524314462 |
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