Polaron pattern recognition
in correlated oxide surfaces
The formation of polarons by charge trapping is pervasive in transition metal oxides. Polarons have been widely studied in binary compounds but comparatively much less so in perovskites.
In P07, we aim to combine advanced first-principles approaches with computer-vision and machine-learning techniques to accelerate and automatize the study of polarons and novel polaron effects in perovskites.
The project has three main pillars: (i) artificial intelligence-aided analysis of experimental ncAFM/STM results (from P02 Diebold, P04 Parkinson) to extract lattice symmetry, surface structure, and chemical composition; (ii) calculation of polaronic configurational energies at different concentrations and temperature using NN; and (iii) identification of unusual types of polarons and polaron-defect complexes in doped perovskites such as spin-, ferroelectric-, Jahn-Teller-, small polarons, and bipolarons.
In the long-term, we plan to establish a fully automatic diagnosis of ncAFM/STM (symmetry, defects, domains) and LEED (diffraction, surface reconstruction) and the construction of a combined experiment & theory database. The research will benefit from two external collaborators and synergy with several experimental (P02, P04) and computational (P03 Kresse, P09 Madsen) TACO partners.
Theoretical and computational modeling of quantum materials, in particular transition metal oxides in bulk phases and surfaces, to predict and interpret novel physical effects and states of matter arising from fundamental quantum interactions: electron-electron correlation, electron-phonon coupling, spin-spin exchange, spin-orbit coupling, to name the most relevant ones. The theoretical research is conducted in strong synergy and cooperation with experimental groups.
- Density functional theory, hybrid functionals, GW, BSE
- First principles molecular dynamics
- Effective Hamiltonian
- Diagrammatic quantum Monte Carlo
- Dynamical mean-field theory
- Machine learning and computer vision
- Polarons: formation, dynamics, polaron-mediated effects, many-body properties
- Computational surface science: energetics, reconstructions, surface polarons, polarity effects, adsorption and chemical reactions
- Quantum magnetism: all-rank multipolar spin-spin interactions beyond Heisenberg exchange
- Electronic and magnetic phase transitions
Our goals in TACO:
- Accelerated study of polaron properties by integrating molecular dynamics and machine learning methods (kernel-ridge regression, standard and convolutional neural-networks
- Implementation of automated identification of local structures in atomically resolved images using computer vision methods
- Complementing the experimental measurements with extensive first principles modeling of perovskite surfaces.
Oxygen-Terminated (1 × 1) Reconstruction of Reduced Magnetite Fe3O4(111)Journal ArticleOpen Access
In: vol. 14, no. 13, pp. 3258–3265, 2023.
Quantum paraelectricity and structural phase transitions in strontium titanate beyond density functional theoryJournal Article
In: Physical Review Materials, vol. 7, no. 3, pp. l030801, 2023.
Temperature-dependent anharmonic phonons in quantum paraelectric KTaO3 by first principles and machine-learned force fieldsJournal ArticleOpen Access
In: Advanced Quantum Technology, vol. 6, iss. 4, 2023.
Automated Real-Space Lattice Extraction for Atomic Force Microscopy ImagesJournal ArticleOpen Access
In: Machine Learning: Science and Technology, vol. 4, pp. 015015, 2023.
Surface chemistry on a polarizable surface: Coupling of CO with KTaO 3(001)Journal ArticleOpen Access
In: Science Advances, vol. 8, iss. 33, 2022.
Competing electronic states emerging on polar surfacesJournal ArticleOpen Access
In: Nature Communications, vol. 13, no. 4311, 2022.
Role of Polarons in Single-Atom Catalysts: Case Study of Me1[Au1,Pt1 and Rh1] on TiO2(110)Journal ArticleOpen Access
In: Topics in Catalysis, vol. 65, pp. 1620–1630, 2022.
Machine learning for exploring small polaron configurational spaceJournal ArticleOpen Access
In: npj Computational Materials, vol. 8, no. 125, 2022.
CO oxidation by Pt2/Fe3O4: Metastable dimer and support configurations facilitate lattice oxygen extractionJournal ArticleOpen Access
In: ScienceAdvances, vol. 8, iss. 13, pp. eabn4580, 2022.
Modeling polarons in density functional theory: lessons learned from TiO2Journal ArticleOpen Access
In: Journal of Physics: Condensed Matter, vol. 34, no. 20, pp. 204006, 2022.