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Structure and dynamics of materials based on advanced electronic structure calculations

Applicant Goedecker Stefan
Number 165554
Funding scheme Project funding
Research institution Departement Physik Universität Basel
Institution of higher education University of Basel - BS
Main discipline Physical Chemistry
Start/End 01.05.2016 - 30.04.2019
Approved amount 400'000.00
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All Disciplines (2)

Discipline
Physical Chemistry
Material Sciences

Keywords (2)

electronic structure calculations; structure prediction

Lay Summary (German)

Lead
.In diesem Projekt werden neue und verbesserte Methioden fuer atomistische Simulationen entwickelt werden. Es werden sowohl klassische Ansaetze wie beispielsweise die Dicjhtefunktionalstheorie verbesster werden als auch neue Ansaetzte entwickelt werden, die zum Beispiel auf Maschinen Lernen beruhen. Bei den Anwendungen wird der Schwerpunkt bei Materialien liegen, die fuer erneuerbare Energieerzeugung und Speicherung von Interesse sind
Lay summary
Atomistische Simulationen erlauben ein tiefgreifendes Verstaendnis sowohl von der Struktur als auch von dynamischen Prozessen in kondensierter Materie. In diesem Projekt werden verbesserte Methoden fuer die Simulation von solchen atomistischen Prozessen entwickelt werden. Eine zentrale Groesse auf der fast alle atomistischen Simulationen basieren ist die Potentialenergieoberflaeche. Diese kann mit verschiedenen Methoden berechnet werden, die sich in ihrer Genauigkeit und in ihren  numeroschen Anforderungen unterscheiden. Ein klassischer guter Kompromiss ist in vielen Faellen die sogenannte Dichtefunktionalstheorie. Sie liefert fuer die meisten physikalischen Observablen ausreichende Genauigkeit und kann auf modernen Parallelrechner trotzdem noch fuer relatiiv grosse Syetem von eingen hundert Atomen angewendet werden. Eine neuer Ansatz sind Kraftfelder, die auf Maschinen Lernen beruhen. Damit koennte es in Zukunft moeglich sein auesserst genaue atomistische Simulationen durchzufuehren, die nur einen Bruchteil der Computerleistung verlangen die fuer Dichtefunktionalsrechnungen notwendig sind. In diesem Projekt an einem weiten Spektrum von verbesserten Methoden zur Berechnung von Potentialenergieoberflaechen gearbeitet werden.
Was Anwendeuneg anbelangt, werden atomistische Simulationen vorallem dazu verwendet werden  Materialien zu studieren, die fuer die nachhaltige Energieerzeugung und Speicherung von Interesse sind.
Direct link to Lay Summary Last update: 30.03.2016

Responsible applicant and co-applicants

Employees

Publications

Publication
Finding Reaction Pathways with Optimal Atomic Index Mappings
De Deb Sankar, Krummenacher Marco, Schaefer Bastian, Goedecker Stefan (2019), Finding Reaction Pathways with Optimal Atomic Index Mappings, in Physical Review Letters, 123(20), 206102-206102.
Evidence for carbon clusters present near thermal gate oxides affecting the electronic band structure in SiC-MOSFET
Dutta D., De D. S., Fan D., Roy S., Alfieri G., Camarda M., Amsler M., Lehmann J., Bartolf H., Goedecker S., Jung T. A. (2019), Evidence for carbon clusters present near thermal gate oxides affecting the electronic band structure in SiC-MOSFET, in Applied Physics Letters, 115(10), 101601-101601.
Divalent Path to Enhance p-Type Conductivity in a SnO Transparent Semiconductor
Graužinytė Miglė, Tomerini Daniele, Goedecker Stefan, Flores-Livas José A. (2019), Divalent Path to Enhance p-Type Conductivity in a SnO Transparent Semiconductor, in The Journal of Physical Chemistry C, 123(24), 14909-14913.
Emergence of superconductivity in doped H2O ice at high pressure
Flores-Livas José A., Sanna Antonio, Graužinytė Miglė, Davydov Arkadiy, Goedecker Stefan, Marques Miguel A. L. (2017), Emergence of superconductivity in doped H2O ice at high pressure, in Scientific Reports, 7(1), 6825-6825.
Surface reconstruction of fluorites in vacuum and aqueous environment
Fisicaro Giuseppe, Sicher Michael, Amsler Maximilian, Saha Santanu, Genovese Luigi, Goedecker Stefan (2017), Surface reconstruction of fluorites in vacuum and aqueous environment, in Physical Review Materials, 1(3), 033609-033609.
Interplay between structure and superconductivity: Metastable phases of phosphorus under pressure
Flores-Livas José A., Sanna Antonio, Drozdov Alexander P., Boeri Lilia, Profeta Gianni, Eremets Mikhail, Goedecker Stefan (2017), Interplay between structure and superconductivity: Metastable phases of phosphorus under pressure, in Physical Review Materials, 1(2), 024802-024802.
The Elephant in the Room of Density Functional Theory Calculations
Jensen Stig Rune, Saha Santanu, Flores-Livas José A., Huhn William, Blum Volker, Goedecker Stefan, Frediani Luca (2017), The Elephant in the Room of Density Functional Theory Calculations, in The Journal of Physical Chemistry Letters, 8(7), 1449-1457.

Collaboration

Group / person Country
Types of collaboration
Luigi Genovese France (Europe)
- Publication

Associated projects

Number Title Start Funding scheme
182877 Development of a Neural Network Potential with Accurate Electrostatic Interactions 01.04.2019 Project funding
144278 High accuracy electronic structure calculations for large systems 01.05.2013 Project funding
153658 Predicting cluster assembled materials 01.04.2014 Project funding

Abstract

In atomistic simulations the positions of all the involved atoms are individually known. In this way the structure as well as the dynamics of molecular systems can be studied and understood in depth. A prerequisite for such atomistic simulations is the availability of a high quality potential energy surface and methods to explore it efficiently. Potential energy surfaces calculated on the density functional levelare usually considered to be state of the art, even though their accuracy is not sufficient in numerous cases. In this project several key aspects of atomistic simulations will be addressed. Based on our recently developed methods to navigate in the configurational space, the efficiency of our structure prediction schemes will be further improved and its applicability enlarged. In addition we will deducefrom our exploration of the potential energy surface not only structural but also dynamic properties. Improved density functional methods will be implemented to give higher accuracy potential energy surfaces and consequently improved predictability for atomistic simulations. We will work both on the validation of methods within mainstream density functional schemes as well as on some non-standard approaches inspired by quantum chemistry methods. For some specific systems, machine learning based force fields will be constructed that are not only highly accurate but also orders of magnitude faster to evaluate than potential energy surfaces resulting from density functional calculations. All these developments will allow to find new materials with useful properties faster and to predict their properties with higher reliability. In particular we will apply these methods to study molecular crystals and cluster assembled materials.
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