Bayesian regression for
multi-level machine-learned potentials

Subproject P03

The first-principles description of the properties of multi-component metal oxides is an exceedingly challenging problem. The reasons are that the configurational space grows exponentially with the number of species and standard Density Functional Theory (DFT) is often not accurate enough. The long-term objective of P03 is to accelerate first-principles calculations by developing machine-learning approaches for the description of the interatomic forces, Born effective charges, and other tensorial properties of multivalent oxides. The project will rely on kernel-based methods and Bayesian inference to implement fully automatic “on-the-fly” learning.

In the first project period, we will develop machine-learned force fields (MLFF) for DFT and DFT+U, whereby the number of components in the FF will be gradually increased. A concise framework for learning tensorial properties will be implemented. We will use this to simulate infrared spectra of oxide materials, which can be readily compared to the finite-temperature spectra measured by the experimental groups.

The difference between DFT and hybrid functionals will be machine-learned to go beyond semi-local functionals (Delta-learning). The long-term perspective is to extend this approach to highly accurate beyond-DFT methods, such as the random phase approximation and quantum chemistry (coupled cluster) methods. Although kernel-based methods are exceedingly accurate, they are often less efficient than NN. We will collaborate with other projects to recast the on-the-fly trained FF into NN potentials to address this issue.

Georg Kresse
PI

Expertise

The main research efforts of the group are directed towards the development of quantum-mechanical tools for atomic-scale simulations of properties and processes in materials and the application of these methodologies to key areas of condensed matter physics and materials research. An important pillar of the research is the Vienna Ab initio Simulation Package (VASP), a general-purpose ab initio code for solving the many-electron Schrödinger equation. The code is among the world leaders in its field, with more than 3500 licensees worldwide. We have expertise with simulations for a vast number of properties using many different techniques:

  • Density functional theory (DFT), including spin and non-collinear DFT
  • Linear response theory to calculate phonons and dielectric properties
  • Hartree-Fock techniques and many flavors of hybrid functionals
  • Many-body perturbation theory, including GW and Bethe-Salpeter
  • Wavefunction-based correlated methods (Møller-Plesset perturbation theory)
  • Surface science, including growth and oxide formation
  • Simulation of nanostructures
  • Semiconductor physics: charge trapping, polarons
  • Electronic excitations
  • Defect energies in extended systems

For TACO, we will adapt our machine-learning techniques to tensorial properties and correlated wavefunction techniques. These techniques are directly integrated into VASP and allow to accelerate finite-temperature simulations by many orders of magnitudes.

Team

Georg Kresse
PI

Carla Verdi
co-PI

Peitao Liu
PostDoc

Bernhard Schmiedmayer
PhD Student

Publications

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43 entries « 1 of 5 »

2021

Ni-modified Fe3O4(001) surface as a simple model system for understanding the oxygen evolution reaction

Mirabella, Francesca; Müllner, Matthias; Touzalin, Thomas; Riva, Michele; Jakub, Zdenek; Kraushofer, Florian; Schmid, Michael; Koper, Marc T M; Parkinson, Gareth S; Diebold, Ulrike

Ni-modified Fe3O4(001) surface as a simple model system for understanding the oxygen evolution reaction Journal Article

In: Electrochimica Acta, 389 , pp. 138638, 2021.

Abstract | Links | BibTeX | Tags: P02, P04, pre-TACO

Emerging applications of MXene materials in CO2 photocatalysis

Shen, Jiahui; Wu, Zhiyi; Li, Chaoran; Zhang, Chengcheng; Genest, Alexander; Rupprechter, Günther; He, Le

Emerging applications of MXene materials in CO2 photocatalysis Journal Article

In: FlatChem, 28 , pp. 100252, 2021.

Abstract | Links | BibTeX | Tags: P08, pre-TACO

Resolving multifrequential oscillations and nanoscale interfacet communication in single-particle catalysis

Suchorski, Yuri; Zeininger, Johannes; Buhr, Sebastian; Raab, Maximilian; Stöger-Pollach, Michael; Bernardi, Johannes; Grönbeck, Henrik; Rupprechter, Günther

Resolving multifrequential oscillations and nanoscale interfacet communication in single-particle catalysis Journal Article

In: Science, 372 (6548), pp. 1314–1318, 2021.

Links | BibTeX | Tags: P08, pre-TACO

Improved description of atomic environments using low-cost polynomial functions with compact support

Bircher, Martin P; Singraber, Andreas; Dellago, Christoph

Improved description of atomic environments using low-cost polynomial functions with compact support Journal Article

In: Machine Learning: Science and Technology, 2 (3), pp. 035026, 2021.

Abstract | Links | BibTeX | Tags: P12, pre-TACO

α-β phase transition of zirconium predicted by on-the-fly machine-learned force field

Liu, Peitao; Verdi, Carla; Karsai, Ferenc; Kresse, Georg

α-β phase transition of zirconium predicted by on-the-fly machine-learned force field Journal Article

In: Physical Review Materials, 5 (5), pp. 053804, 2021.

Abstract | Links | BibTeX | Tags: P03, pre-TACO

Evolutionary computing and machine learning for discovering of low-energy defect configurations

Arrigoni, Marco; Madsen, Georg K H

Evolutionary computing and machine learning for discovering of low-energy defect configurations Journal Article

In: npj Computational Materials, 7 (1), 2021.

Abstract | Links | BibTeX | Tags: P09, pre-TACO

Co3O4-CeO2 Nanocomposites for Low-Temperature CO Oxidation

Yang, Jingxia; Yigit, Nevzat; Möller, Jury; Rupprechter, Günther

Co3O4-CeO2 Nanocomposites for Low-Temperature CO Oxidation Journal Article

In: Chemistry A European Journal, 2021.

Abstract | Links | BibTeX | Tags: P08, pre-TACO

Direct CO2 capture and conversion to fuels on magnesium nanoparticles under ambient conditions simply using water

Rawool, Sushma A; Belgamwar, Rajesh; Jana, Rajkumar; Maity, Ayan; Bhumla, Ankit; Yigit, Nevzat; Datta, Ayan; Rupprechter, Günther; Polshettiwar, Vivek

Direct CO2 capture and conversion to fuels on magnesium nanoparticles under ambient conditions simply using water Journal Article

In: Chemical Science, 12 (16), pp. 5774–5786, 2021.

Abstract | Links | BibTeX | Tags: P08, pre-TACO

Polarons in materials

Franchini, Cesare; Reticcioli, Michele; Setvin, Martin; Diebold, Ulrike

Polarons in materials Journal Article

In: Nature Reviews Materials, 2021.

Abstract | Links | BibTeX | Tags: P02, P07, pre-TACO

Operando Surface Spectroscopy and Microscopy during Catalytic Reactions: From Clusters via Nanoparticles to Meso-Scale Aggregates

Rupprechter, Günther

Operando Surface Spectroscopy and Microscopy during Catalytic Reactions: From Clusters via Nanoparticles to Meso-Scale Aggregates Journal Article

In: Small, 2021.

Abstract | Links | BibTeX | Tags: P08, pre-TACO

43 entries « 1 of 5 »