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General purpose potential for glassy and crystalline phases of Cu-Zr alloys based on the ACE formalism

Leimeroth, Niklas ; Rohrer, Jochen ; Albe, Karsten (2024)
General purpose potential for glassy and crystalline phases of Cu-Zr alloys based on the ACE formalism.
In: Physical Review Materials, 8 (4)
doi: 10.1103/PhysRevMaterials.8.043602
Artikel, Bibliographie

Kurzbeschreibung (Abstract)

A general purpose machine-learning interatomic potential (MLIP) for the Cu-Zr system is presented based on the atomic cluster expansion formalism [R. Drautz, Phys. Rev. B 99, 014104 (2019)]. By using an extensive set of Cu-Zr training data generated withdensity functional theory, this potential describes a wide range of properties of crystalline as well as amorphous phases within the whole compositional range. Therefore, the machine learning interatomic potential (MLIP) can reproduce the experimental phase diagram and amorphous structure with considerably improved accuracy. A massively different short-range order compared to classica interatomic potentials is found in glassy Cu-Zr samples, shedding light on the role of the full icosahedral motif in the material. Tensile tests of B2-CuZr inclusions in an Cu50⁢Zr50 amorphous matrix reveal the occurrence of martensitic phase transformations in this crystal-glass nanocomposite.

Typ des Eintrags: Artikel
Erschienen: 2024
Autor(en): Leimeroth, Niklas ; Rohrer, Jochen ; Albe, Karsten
Art des Eintrags: Bibliographie
Titel: General purpose potential for glassy and crystalline phases of Cu-Zr alloys based on the ACE formalism
Sprache: Englisch
Publikationsjahr: 16 April 2024
Verlag: American Physical Society
Titel der Zeitschrift, Zeitung oder Schriftenreihe: Physical Review Materials
Jahrgang/Volume einer Zeitschrift: 8
(Heft-)Nummer: 4
DOI: 10.1103/PhysRevMaterials.8.043602
Kurzbeschreibung (Abstract):

A general purpose machine-learning interatomic potential (MLIP) for the Cu-Zr system is presented based on the atomic cluster expansion formalism [R. Drautz, Phys. Rev. B 99, 014104 (2019)]. By using an extensive set of Cu-Zr training data generated withdensity functional theory, this potential describes a wide range of properties of crystalline as well as amorphous phases within the whole compositional range. Therefore, the machine learning interatomic potential (MLIP) can reproduce the experimental phase diagram and amorphous structure with considerably improved accuracy. A massively different short-range order compared to classica interatomic potentials is found in glassy Cu-Zr samples, shedding light on the role of the full icosahedral motif in the material. Tensile tests of B2-CuZr inclusions in an Cu50⁢Zr50 amorphous matrix reveal the occurrence of martensitic phase transformations in this crystal-glass nanocomposite.

ID-Nummer: Artikel-ID: 043602
Fachbereich(e)/-gebiet(e): 11 Fachbereich Material- und Geowissenschaften
11 Fachbereich Material- und Geowissenschaften > Materialwissenschaft
11 Fachbereich Material- und Geowissenschaften > Materialwissenschaft > Fachgebiet Materialmodellierung
Zentrale Einrichtungen
Zentrale Einrichtungen > Hochschulrechenzentrum (HRZ)
TU-Projekte: DFG|RO4542/4-1|Interatomare Potenti
DFG|STU611/5-1|Von interatomaren Po
Hinterlegungsdatum: 27 Mai 2024 06:24
Letzte Änderung: 27 Mai 2024 11:41
PPN: 518631079
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