Polaron pattern recognition
in correlated oxide surfaces

Subproject P07

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 transition metal oxides.

We address and provide solutions for static and dynamical polaron properties by implementing ML and computer vision approaches to accelerate the exploration of the multi-polaron configurational space and to extend small polaron dynamics to the nanoscale. We integrate charge state encoding into the atomic features and forecast the dynamic evolution by predicting the occupation matrix. These methodological developments will be integrated in our software Leopolad (Learning of polaron dynamics) based on an equivariant graph neural network framework.

Addressing ML-augmented charge (polaron) dynamics is essential for advancing our understanding of complex materials and phenomena, and for fully leveraging ML-assisted MD. By expanding DFT capabilities with ML algorithms, we aim to extend the simulation of polaron dynamics to the nanoscale. This advancement will enable us to uncover novel effects, such as the dynamical interaction of surface polaron with adsorbates.

The advancement of ML-assisted polaron-MD will significantly contribute to the key methodological developments of the SFB, particularly in predicting multivalence states in oxides.

Cesare Franchini
PI

Expertise

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.

Methods:

  • 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

Applications:

  • 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:

  1. Accelerated study of polaron properties by integrating molecular dynamics and machine learning methods (kernel-ridge regression, standard and convolutional neural-networks
  2. Implementation of automated identification of local structures in atomically resolved images using computer vision methods
  3. Complementing the experimental measurements with extensive first principles modeling of perovskite surfaces.

Team

Cesare Franchini
PI

Johanna Paulina Carbone
Co-PI

Daniela Mangano
PhD Student

Associates

Matthias Meier
Postdoc

Luca Leoni
PhD Student

Darin Joseph
PhD Student

Former Members

Michele Reticcioli
Co-PI

Viktor Birschitzky
PhD Student

Marco Corrias
PhD Student

Florian Ellinger
PhD Student

Publications

29 entries « 2 of 3 »

2024

Digging Its Own Site: Linear Coordination Stabilizes a Pt1/Fe2O3 Single-Atom Catalyst

Rafsanjani-Abbasi, Ali; Buchner, Florian; Lewis, Faith J.; Puntscher, Lena; Kraushofer, Florian; Sombut, Panukorn; Eder, Moritz; Pavelec, Jiří; Rheinfrank, Erik; Franceschi, Giada; Birschitzky, Viktor; Riva, Michele; Franchini, Cesare; Schmid, Michael; Diebold, Ulrike; Meier, Matthias; Madsen, Georg K. H.; Parkinson, Gareth S.

Digging Its Own Site: Linear Coordination Stabilizes a Pt1/Fe2O3 Single-Atom Catalyst

Journal ArticleOpen Access

In: ACS Nano, vol. 18, iss. 39, pp. 26920–26927, 2024.

Abstract | Links | BibTeX | Tags: P02, P04, P07, P09

A Multitechnique Study of C2H4 Adsorption on a Model Single-Atom Rh1 Catalyst

Wang, Chunlei; Sombut, Panukorn; Puntscher, Lena; Ulreich, Manuel; Pavelec, Jiri; Rath, David; Balajka, Jan; Meier, Matthias; Schmid, Michael; Diebold, Ulrike; Franchini, Cesare; Parkinson, Gareth S.

A Multitechnique Study of C2H4 Adsorption on a Model Single-Atom Rh1 Catalyst

Journal ArticleOpen Access

In: The Journal of Physical Chemistry C, vol. 128, iss. 37, pp. 15404–15411, 2024.

Abstract | Links | BibTeX | Tags: P02, P04, P07

Molecular hydrogen in the N-doped LuH3 system as a possible path to superconductivity

Tresca, Cesare; Forcella, Pietro Maria; Angeletti, Andrea; Ranalli, Luigi; Franchini, Cesare; Reticcioli, Michele; Profeta, Gianni

Molecular hydrogen in the N-doped LuH3 system as a possible path to superconductivity

Journal ArticleOpen Access

In: Nature Communications, vol. 15, pp. 7283, 2024.

Abstract | Links | BibTeX | Tags: P07

Global sampling of Feynman's diagrams through normalizing flow

Leoni, Luca; Franchini, Cesare

Global sampling of Feynman's diagrams through normalizing flow

Journal ArticleOpen Access

In: Physical Review Research, vol. 6, iss. 3, pp. 033041, 2024.

Abstract | Links | BibTeX | Tags: P07

Machine learning-based prediction of polaron-vacancy patterns on the TiO2(110) surface

Birschitzky, Viktor; Sokolovic, Igor; Prezzi, Michael; Palotas, Krisztian; Setvin, Martin; Diebold, Ulrike; Reticcioli, Michele; Franchini, Cesare

Machine learning-based prediction of polaron-vacancy patterns on the TiO2(110) surface

Journal ArticleOpen Access

In: npj Computational Materials, vol. 10, no. 89, 2024.

Abstract | Links | BibTeX | Tags: P02, P07

Spin-orbital Jahn-Teller bipolarons

Celiberti, Lorenzo; Mosca, Dario Fiore; Allodi, Giuseppe; Pourovskii, Leonid V.; Tassetti, Anna; Forino, Paola Caterina; Cong, Rong; Garcia, Erick; Tran, Phuong M.; Renzi, Roberto De; Woodward, Patrick M.; Mitrović, Vesna F.; Sanna, Samuele; Franchini, Cesare

Spin-orbital Jahn-Teller bipolarons

Journal ArticleOpen Access

In: Nature Communications, vol. 15, no. 2429, 2024.

Abstract | Links | BibTeX | Tags: P07

CO‐Induced Dimer Decay Responsible for Gem‐Dicarbonyl Formation on a Model Single‐Atom Catalyst

Wang, Chunlei; Sombut, Panukorn; Puntscher, Lena; Jakub, Zdenek; Meier, Matthias; Pavelec, Jiri; Bliem, Roland; Schmid, Michael; Diebold, Ulrike; Franchini, Cesare; Parkinson, Gareth S.

CO‐Induced Dimer Decay Responsible for Gem‐Dicarbonyl Formation on a Model Single‐Atom Catalyst

Journal ArticleOpen AccessIn Press

In: Angewandte Chemie - International Edition, no. e202317347, 2024, ISSN: 1521-3773.

Abstract | Links | BibTeX | Tags: P02, P04, P07

2023

A Multitechnique Study of C2H4 Adsorption on Fe3O4(001)

Puntscher, Lena; Sombut, Panukorn; Wang, Chunlei; Ulreich, Manuel; Pavelec, Jiri; Rafsanjani-Abbasi, Ali; Meier, Matthias; Lagin, Adam; Setvin, Martin; Diebold, Ulrike; Franchini, Cesare; Schmid, Michael; Parkinson, Gareth S.

A Multitechnique Study of C2H4 Adsorption on Fe3O4(001)

Journal ArticleOpen Access

In: Journal of Physical Chemistry C, vol. 127, iss. 37, pp. 18378–18388, 2023.

Abstract | Links | BibTeX | Tags: P02, P04, P07

Oxygen-Terminated (1 × 1) Reconstruction of Reduced Magnetite Fe3O4(111)

Kraushofer, Florian; Meier, Matthias; Jakub, Zdeněk; Hütner, Johanna; Balajka, Jan; Hulva, Jan; Schmid, Michael; Franchini, Cesare; Diebold, Ulrike; Parkinson, Gareth S.

Oxygen-Terminated (1 × 1) Reconstruction of Reduced Magnetite Fe3O4(111)

Journal ArticleOpen Access

In: The Journal of Physical Chemistry Letters, vol. 14, no. 13, pp. 3258–3265, 2023.

Abstract | Links | BibTeX | Tags: P02, P04, P07

Quantum paraelectricity and structural phase transitions in strontium titanate beyond density functional theory

Verdi, Carla; Ranalli, Luigi; Franchini, Cesare; Kresse, Georg

Quantum paraelectricity and structural phase transitions in strontium titanate beyond density functional theory

Journal Article

In: Physical Review Materials, vol. 7, no. 3, pp. l030801, 2023.

Abstract | Links | BibTeX | Tags: P03, P07

29 entries « 2 of 3 »