Hard antiphase domain boundaries in strontium titanate unravelled using machine-learned force fields

A. Tröster; C. Verdi; C. Dellago; I. Rychetsky; G. Kresse; W. Schranz

doi:10.1103/PhysRevMaterials.6.094408

Hard antiphase domain boundaries in strontium titanate unravelled using machine-learned force fields

A. Tröster (Corresponding author), C. Verdi, C. Dellago, I. Rychetsky, G. Kresse, W. Schranz

Publications: Contribution to journal › Article › Peer Reviewed

Original language	English
Article number	094408
Number of pages	8
Journal	Physical Review Materials
Volume	6
Issue number	9
DOIs	https://doi.org/10.1103/PhysRevMaterials.6.094408
Publication status	Published - 16 Sept 2022

Funding

A.T. acknowledges support by the Austrian Science Fund (FWF) Project No. P27738-N28, and C.V., C.D., and G.K. by FWF Project No. F81-08 (SFB TACO).

Austrian Fields of Science 2012

102019 Machine learning
103018 Materials physics

Keywords

INSTABILITIES

Access to Document

10.1103/PhysRevMaterials.6.094408

Cite this

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AU - Tröster, A.

AU - Verdi, C.

AU - Dellago, C.

AU - Rychetsky, I.

AU - Kresse, G.

AU - Schranz, W.

PY - 2022/9/16

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Hard antiphase domain boundaries in strontium titanate unravelled using machine-learned force fields

Funding

Austrian Fields of Science 2012

Keywords

Access to Document

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TACO: Taming Complexity in Materials Modeling

Cite this

Hard antiphase domain boundaries in strontium titanate unravelled using machine-learned force fields

Funding

Austrian Fields of Science 2012

Keywords

Access to Document

Other files and links

Fingerprint

Projects

TACO: Taming Complexity in Materials Modeling

Cite this