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.
Polarons in materials Journal Article
Nature Reviews Materials, 2021.
Unraveling CO adsorption on model single-atom catalysts Journal Article
Science, 371 (6527), pp. 375–379, 2021.
Angewandte Chemie - International Edition, 58 (39), pp. 13961–13968, 2019.
Physical Review Letters, 122 (1), pp. 016805, 2019.
Polaron-Driven Surface Reconstructions Journal Article
Physical Review X, 7 (3), pp. 031053, 2017.