Publications

@article{Troester2022,

title = {Hard antiphase domain boundaries in strontium titanate unravelled using machine-learned force fields},

author = {Andreas Tröster and Carla Verdi and Christoph Dellago and Ivan Rychetsky and Georg Kresse and Wilfried Schranz},

doi = {10.1103/physrevmaterials.6.094408},

year  = {2022},

date = {2022-09-16},

urldate = {2022-09-16},

journal = {Physical Review Materials},

volume = {6},

number = {9},

pages = {094408},

publisher = {American Physical Society (APS)},

abstract = {We investigate the properties of hard antiphase boundaries in SrTiO_{3} using machine-learned force fields. In contrast to earlier findings based on standard \textit{ab initio} methods, for all pressures up to 120kbar the observed domain wall pattern maintains an almost perfect Néel character in quantitative agreement with Landau-Ginzburg-Devonshire theory, and the in-plane polarization P_{3} shows no tendency to decay to zero. Together with the switching properties of P_{3} under reversal of the Néel order parameter component, this provides hard evidence for the presence of rotopolar couplings. The present approach overcomes the severe limitations of \textit{ab initio} simulations of wide domain walls and opens avenues toward concise atomistic predictions of domain-wall properties even at finite temperatures.},

keywords = {P03, P12},

pubstate = {published},

tppubtype = {article}

}

@article{Wanzenboeck2022,

title = {Neural-network-backed evolutionary search for SrTiO_{3}(110) surface reconstructions},

author = {Ralf Wanzenböck and Marco Arrigoni and Sebastian Bichelmaier and Florian Buchner and Jesús Carrete and Georg K. H. Madsen},

doi = {10.1039/d2dd00072e},

year  = {2022},

date = {2022-08-26},

journal = {Digital Discovery},

volume = {1},

number = {5},

pages = {703--710},

publisher = {Royal Society of Chemistry (RSC)},

abstract = {The determination of atomic structures in surface reconstructions has typically relied on structural models derived from intuition and domain knowledge. Evolutionary algorithms have emerged as powerful tools for such structure searches. However, when density functional theory is used to evaluate the energy the computational cost of a thorough exploration of the potential energy landscape is prohibitive. Here, we drive the exploration of the rich phase diagram of TiO_{x} overlayer structures on SrTiO_{3}(110) by combining the covariance matrix adaptation evolution strategy (CMA-ES) and a neural-network force field (NNFF) as a surrogate energy model. By training solely on SrTiO_{3}(110) 4×1 overlayer structures and performing CMA-ES runs on 3×1, 4×1 and 5×1 overlayers, we verify the transferability of the NNFF. The speedup due to the surrogate model allows taking advantage of the stochastic nature of the CMA-ES to perform exhaustive sets of explorations and identify both known and new low-energy reconstructions.},

keywords = {P09},

pubstate = {published},

tppubtype = {article}

}

@article{Coretti2022,

title = {Learning Mappings between Equilibrium States of Liquid Systems Using Normalizing Flows},

author = {Alessandro Coretti and Sebastian Falkner and Phillip Geissler and Christoph Dellago},

url = {https://arxiv.org/abs/2208.10420},

year  = {2022},

date = {2022-08-22},

urldate = {2022-08-22},

journal = {arXiv},

abstract = {     Generative models are a promising tool to address the sampling problem in multi-body and condensed-matter systems in the framework of statistical mechanics. In this work, we show that normalizing flows can be used to learn a transformation to map different liquid systems into each other allowing at the same time to obtain an unbiased equilibrium distribution through a reweighting process. Two proof-of-principles calculations are presented for the transformation between Lennard-Jones systems of particles with different depths of the potential well and for the transformation between a Lennard-Jones and a system of repulsive particles. In both numerical experiments, systems are in the liquid state. In future applications, this approach could lead to efficient methods to simulate liquid systems at ab-initio accuracy with the computational cost of less accurate models, such as force field or coarse-grained simulations.},

keywords = {P12},

pubstate = {published},

tppubtype = {article}

}

@article{Wang2022,

title = {Surface chemistry on a polarizable surface: Coupling of CO with KTaO _{3}(001)},

author = {Zhichang Wang and Michele Reticcioli and Zdenek Jakub and Igor Sokolović and Matthias Meier and Lynn A Boatner and Michael Schmid and Gareth S. Parkinson and Ulrike Diebold and Cesare Franchini and Martin Setvin},

url = {https://www.science.org/doi/10.1126/sciadv.abq1433},

doi = {10.1126/sciadv.abq1433},

year  = {2022},

date = {2022-08-19},

urldate = {2022-08-19},

journal = {Science Advances},

volume = {8},

issue = {33},

publisher = {American Association for the Advancement of Science (AAAS)},

abstract = {Polarizable materials attract attention in catalysis because they have a free parameter for tuning chemical reactivity. Their surfaces entangle the dielectric polarization with surface polarity, excess charge, and orbital hybridization. How this affects individual adsorbed molecules is shown for the incipient ferroelectric perovskite KTaO_{3}. This intrinsically polar material cleaves along (001) into KO- and TaO_{2}-terminated surface domains. At TaO_{2} terraces, the polarity-compensating excess electrons form a two-dimensional electron gas and can also localize by coupling to ferroelectric distortions. TaO_{2} terraces host two distinct types of CO molecules, adsorbed at equivalent lattice sites but charged differently as seen in atomic force microscopy/scanning tunneling microscopy. Temperature-programmed desorption shows substantially stronger binding of the charged CO; in density functional theory calculations, the excess charge favors a bipolaronic configuration coupled to the CO. These results pinpoint how adsorption states couple to ferroelectric polarization.},

keywords = {P02, P04, P07},

pubstate = {published},

tppubtype = {article}

}

@article{Sombut2022,

title = {Role of Polarons in Single-Atom Catalysts: Case Study of Me_{1}[Au_{1},Pt_{1} and Rh_{1}] on TiO_{2}(110)},

author = {Panukorn Sombut and Lena Puntscher and Marlene Atzmüller and Zdenek Jakub and Michele Reticcioli and Matthias Meier and Gareth S. Parkinson and Cesare Franchini},

doi = {10.1007/s11244-022-01651-0},

year  = {2022},

date = {2022-07-25},

journal = {Topics in Catalysis},

volume = {65},

pages = {1620--1630},

abstract = {The local environment of metal-oxide supported single-atom catalysts plays a decisive role in the surface reactivity and related catalytic properties. The study of such systems is complicated by the presence of point defects on the surface, which are often associated with the localization of excess charge in the form of polarons. This can affect the stability, the electronic configuration, and the local geometry of the adsorbed adatoms. In this work, through the use of density functional theory and surface-sensitive experiments, we study the adsorption of Rh_{1}, Pt_{1}, and Au_{1} metals on the reduced TiO_{2}(110) surface, a prototypical polaronic material. A systematic analysis of the adsorption configurations and oxidation states of the adsorbed metals reveals different types of couplings between adsorbates and polarons. As confirmed by scanning tunneling microscopy measurements, the favored Pt_{1} and Au_{1} adsorption at oxygen vacancy sites is associated with a strong electronic charge transfer from polaronic states to adatom orbitals, which results in a reduction of the adsorbed metal. In contrast, the Rh_{1} adatoms interact weakly with the excess charge, which leaves the polarons largely unaffected. Our results show that an accurate understanding of the properties of single-atom catalysts on oxide surfaces requires a careful account of the interplay between adatoms, vacancy sites, and polarons.},

keywords = {P04, P07},

pubstate = {published},

tppubtype = {article}

}

@article{Reticcioli2022,

title = {Competing electronic states emerging on polar surfaces},

author = {Michele Reticcioli and Zhichang Wang and Michael Schmid and Dominik Wrana and Lynn A. Boatner and Ulrike Diebold and Martin Setvin and Cesare Franchini},

url = {https://www.nature.com/articles/s41467-022-31953-6},

doi = {10.1038/s41467-022-31953-6},

year  = {2022},

date = {2022-07-25},

urldate = {2022-07-25},

journal = {Nature Communications},

volume = {13},

number = {4311},

publisher = {Springer Science and Business Media LLC},

abstract = {Excess charge on polar surfaces of ionic compounds is commonly described by the two-dimensional electron gas (2DEG) model, a homogeneous distribution of charge, spatially-confined in a few atomic layers. Here, by combining scanning probe microscopy with density functional theory calculations, we show that excess charge on the polar TaO_{2} termination of KTaO_{3}(001) forms more complex electronic states with different degrees of spatial and electronic localization: charge density waves (CDW) coexist with strongly-localized electron polarons and bipolarons. These surface electronic reconstructions, originating from the combined action of electron-lattice interaction and electronic correlation, are energetically more favorable than the 2DEG solution. They exhibit distinct spectroscopy signals and impact on the surface properties, as manifested by a local suppression of ferroelectric distortions.},

keywords = {P02, P07},

pubstate = {published},

tppubtype = {article}

}

@article{Yigit2022,

title = {Active sites and deactivation of room temperature CO oxidation on Co_{3}O_{4} catalysts: combined experimental and computational investigations},

author = {Nevzat Yigit and Alexander Genest and Schamil Terloev and Jury Möller and Günther Rupprechter},

doi = {10.1088/1361-648x/ac718b},

year  = {2022},

date = {2022-06-29},

urldate = {2022-06-29},

journal = {Journal of Physics: Condensed Matter},

volume = {34},

number = {35},

pages = {354001},

publisher = {IOP Publishing},

abstract = {Co_{3}O_{4} is a well-known low temperature CO oxidation catalyst, but it often suffers from deactivation. We have thus examined room temperature (RT) CO oxidation on Co_{3}O_{4} catalysts by operando DSC, TGA and MS measurements, as well as by pulsed chemisorption to differentiate the contributions of CO adsorption and reaction to CO_{2}. Catalysts pretreated in oxygen at 400 °C are most active, with the initial interaction of CO and Co_{3}O_{4} being strongly exothermic and with maximum amounts of CO adsorption and reaction. The initially high RT activity then levels-off, suggesting that the oxidative pretreatment creates an oxygen-rich reactive Co_{3}O_{4} surface that upon reaction onset loses its most active oxygen. This specific active oxygen is not reestablished by gas phase O_{2} during the RT reaction. When the reaction temperature is increased to 150 °C, full conversion can be maintained for 100 h, and even after cooling back to RT. Apparently, deactivating species are avoided this way, whereas exposing the active surface even briefly to pure CO leads to immediate deactivation. Computational modeling using DFT helped to identify the CO adsorption sites, determine oxygen vacancy formation energies and the origin of deactivation. A new species of CO bonded to oxygen vacancies at RT was identified, which may block a vacancy site from further reaction unless CO is removed at higher temperature. The interaction between oxygen vacancies was found to be small, so that in the active state several lattice oxygen species are available for reaction in parallel.},

keywords = {P08},

pubstate = {published},

tppubtype = {article}

}

@article{Birschitzky2022,

title = {Machine learning for exploring small polaron configurational space},

author = {Viktor C Birschitzky and Florian Ellinger and Ulrike Diebold and Michele Reticcioli and Cesare Franchini},

url = {https://www.nature.com/articles/s41524-022-00805-8},

doi = {10.1038/s41524-022-00805-8},

year  = {2022},

date = {2022-06-06},

urldate = {2022-06-06},

journal = {npj Computational Materials},

volume = {8},

number = {125},

publisher = {Springer Science and Business Media LLC},

abstract = {Polaron defects are ubiquitous in materials and play an important role in many processes involving carrier mobility, charge transfer and surface reactivity. Determining small polarons’ spatial distributions is essential to understand materials properties and functionalities. However, the required exploration of the configurational space is computationally demanding when using first principles methods. Here, we propose a machine-learning (ML) accelerated search that determines the ground state polaronic configuration. The ML model is trained on databases of polaron configurations generated by density functional theory (DFT) via molecular dynamics or random sampling. To establish a mapping between configurations and their stability, we designed descriptors modelling the interactions among polarons and charged point defects. We used the DFT+ML protocol to explore the polaron configurational space for two surface-systems, reduced rutile TiO_{2}(110) and Nb-doped SrTiO_{3}(001). The ML-aided search proposes additional polaronic configurations and can be utilized to determine optimal polaron distributions at any charge concentration.},

keywords = {P02, P07},

pubstate = {published},

tppubtype = {article}

}

@article{ANGEWANDTE2022,

title = {Structure of an Ultrathin Oxide on Pt_{3}Sn(111) Solved by Machine Learning Enhanced Global Optimization},

author = {Lindsay R Merte and Malthe Kjær Bisbo and Igor Sokolović and Martin Setvín and Benjamin Hagman and Mikhail Shipilin and Michael Schmid and Ulrike Diebold and Edvin Lundgren and Bjørk Hammer},

url = {https://onlinelibrary.wiley.com/doi/10.1002/anie.202204244},

doi = {10.1002/anie.202204244},

year  = {2022},

date = {2022-04-05},

urldate = {2022-04-05},

journal = {Angewandte Chemie - International Edition},

volume = {61},

issue = {25},

pages = {e202204244},

abstract = {Determination of the atomic structure of solid surfaces typically depends on comparison of measured properties with simulations based on hypothesized structural models. For simple structures, the models may be guessed, but for more complex structures there is a need for reliable theory-based search algorithms. So far, such methods have been limited by the combinatorial complexity and computational expense of sufficiently accurate energy estimation for surfaces. However, the introduction of machine learning methods has the potential to change this radically. Here, we demonstrate how an evolutionary algorithm, utilizing machine learning for accelerated energy estimation and diverse population generation, can be used to solve an unknown surface structure—the (4×4) surface oxide on Pt_{3}Sn(111)–based on limited experimental input. The algorithm is efficient and robust, and should be broadly applicable in surface studies, where it can replace manual, intuition based model generation.},

keywords = {P02},

pubstate = {published},

tppubtype = {article}

}

@article{SCIADV2022,

title = {CO oxidation by Pt_{2}/Fe_{3}O_{4}: Metastable dimer and support configurations facilitate lattice oxygen extraction},

author = {Matthias Meier and Jan Hulva and Zdenek Jakub and Florian Kraushofer and Mislav Bobić and Roland Bliem and Martin Setvin and Michael Schmid and Ulrike Diebold and Cesare Franchini and Gareth S. Parkinson},

url = {https://www.science.org/doi/10.1126/sciadv.abn4580},

doi = {10.1126/sciadv.abn4580},

year  = {2022},

date = {2022-04-01},

urldate = {2022-04-01},

journal = {ScienceAdvances},

volume = {8},

issue = {13},

pages = {eabn4580},

abstract = {Heterogeneous catalysts based on subnanometer metal clusters often exhibit strongly size-dependent properties, and the addition or removal of a single atom can make all the difference. Identifying the most active species and deciphering the reaction mechanism is extremely difficult, however, because it is often not clear how the catalyst evolves in operando. Here, we use a combination of atomically resolved scanning probe microscopies, spectroscopic techniques, and density functional theory (DFT)–based calculations to study CO oxidation by a model Pt/Fe_{3}O_{4}(001) “single-atom” catalyst. We demonstrate that (PtCO)_{2} dimers, formed dynamically through the agglomeration of mobile Pt-carbonyl species, catalyze a reaction involving the oxide support to form CO_{2}. Pt_{2} dimers produce one CO_{2} molecule before falling apart into two adatoms, releasing the second CO. Olattice extraction only becomes facile when both the Pt-dimer and the Fe_{3}O_{4} support can access metastable configurations, suggesting that substantial, concerted rearrangements of both cluster and support must be considered for reactions occurring at elevated temperature.},

keywords = {P02, P04, P07},

pubstate = {published},

tppubtype = {article}

}