Abstract
Originalsprache | englisch |
---|---|
Seiten (von - bis) | 043803 |
Fachzeitschrift | Physical Review Materials |
Jahrgang | 2 |
Ausgabenummer | 4 |
DOIs | |
Publikationsstatus | Veröffentlicht - 17 Apr 2018 |
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Fields of Expertise
- Advanced Materials Science
Dies zitieren
Charting the energy landscape of metal/organic interfaces via machine learning. / Scherbela, Michael; Hörmann, Lukas; Jeindl, Andreas; Obersteiner, Veronika; Hofmann, Oliver.
in: Physical Review Materials, Jahrgang 2, Nr. 4, 17.04.2018, S. 043803.Publikation: Beitrag in einer Fachzeitschrift › Artikel › Forschung › Begutachtung
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TY - JOUR
T1 - Charting the energy landscape of metal/organic interfaces via machine learning
AU - Scherbela, Michael
AU - Hörmann, Lukas
AU - Jeindl, Andreas
AU - Obersteiner, Veronika
AU - Hofmann, Oliver
PY - 2018/4/17
Y1 - 2018/4/17
N2 - The rich polymorphism exhibited by inorganic/organic interfaces is a major challenge for materials design. In this work, we present a method to efficiently explore the potential energy surface and predict the formation energies of polymorphs and defects. This is achieved by training a machine learning model on a list of only 100 candidate structures that are evaluated via dispersion-corrected density functional theory (DFT) calculations. We demonstrate the power of this approach for tetracyanoethylene on Ag(100) and explain the anisotropic ordering that is observed experimentally.
AB - The rich polymorphism exhibited by inorganic/organic interfaces is a major challenge for materials design. In this work, we present a method to efficiently explore the potential energy surface and predict the formation energies of polymorphs and defects. This is achieved by training a machine learning model on a list of only 100 candidate structures that are evaluated via dispersion-corrected density functional theory (DFT) calculations. We demonstrate the power of this approach for tetracyanoethylene on Ag(100) and explain the anisotropic ordering that is observed experimentally.
U2 - 10.1103/PhysRevMaterials.2.043803
DO - 10.1103/PhysRevMaterials.2.043803
M3 - Article
VL - 2
SP - 043803
JO - Physical Review Materials
JF - Physical Review Materials
SN - 2475-9953
IS - 4
ER -