Publications

@article{Verdi2023,

title = {Quantum paraelectricity and structural phase transitions in strontium titanate beyond density functional theory},

author = {Carla Verdi and Luigi Ranalli and Cesare Franchini and Georg Kresse},

doi = {10.1103/physrevmaterials.7.l030801},

year  = {2023},

date = {2023-03-16},

journal = {Physical Review Materials},

volume = {7},

number = {3},

pages = {l030801},

publisher = {American Physical Society (APS)},

abstract = {We demonstrate an approach for calculating temperature-dependent quantum and anharmonic effects with beyond density-functional theory accuracy. By combining machine-learned potentials and the stochastic self-consistent harmonic approximation, we investigate the cubic to tetragonal transition in strontium titanate and show that the paraelectric phase is stabilized by anharmonic quantum fluctuations. We find that a quantitative understanding of the quantum paraelectric behavior requires a higher-level treatment of electronic correlation effects via the random phase approximation. This approach enables detailed studies of emergent properties in strongly anharmonic materials beyond density-functional theory.},

keywords = {P03, P07},

pubstate = {published},

tppubtype = {article}

}

@article{Pramhaas2023,

title = {Polarization-Dependent Sum-Frequency-Generation Spectroscopy for In Situ Tracking of Nanoparticle Morphology},

author = {Verena Pramhaas and Holger Unterhalt and Hans-Joachim Freund and Günther Rupprechter},

doi = {10.1002/anie.202300230},

year  = {2023},

date = {2023-03-08},

journal = {Angewandte Chemie - International Edition},

volume = {62},

number = {19},

publisher = {Wiley},

abstract = {The surface structure of oxide-supported metal nanoparticles can be determined via characteristic vibrations of adsorbed probe molecules such as CO. Usually, spectroscopic studies focus on peak position and intensity, which are related to binding geometries and number of adsorption sites, respectively. Employing two differently prepared model catalysts, it is demonstrated that polarization-dependent sum-frequency-generation (SFG) spectroscopy reveals the average surface structure and shape of the nanoparticles. SFG results for different particle sizes and morphologies are compared to direct real-space structure analysis by TEM and STM. The described feature of SFG could be used to monitor particle restructuring in situ and may be a valuable tool for operando catalysis.},

keywords = {P08},

pubstate = {published},

tppubtype = {article}

}

@article{Ranalli2023,

title = {Temperature-dependent anharmonic phonons in quantum paraelectric KTaO_{3} by first principles and machine-learned force fields},

author = {Luigi Ranalli and Carla Verdi and Lorenzo Monacelli and Georg Kresse and Matteo Calandra and Cesare Franchini},

doi = {10.1002/qute.202200131},

year  = {2023},

date = {2023-02-22},

urldate = {2023-02-22},

journal = {Advanced Quantum Technology},

volume = {6},

issue = {4},

abstract = {Understanding collective phenomena in quantum materials from first principles is a promising route toward engineering materials properties and designing new functionalities. This work examines the quantum paraelectric state, an elusive state of matter characterized by the smooth saturation of the ferroelectric instability at low temperature due to quantum fluctuations associated with anharmonic phonon effects. The temperature-dependent evolution of the soft ferroelectric phonon mode in the quantum paraelectric KTaO_{3} in the range 0–300 K is modeled by combining density functional theory (DFT) calculations with the stochastic self-consistent harmonic approximation assisted by an on-the-fly machine-learned force field. The calculated data show that including anharmonic terms is essential to stabilize the spurious imaginary ferroelectric phonon predicted by DFT in the harmonic approximation, in agreement with experiments. Augmenting the DFT workflow with machine-learned force fields allows for efficient stochastic sampling of the configuration space using large supercells in a wide temperature range, inaccessible to conventional ab initio protocols. This work proposes a robust computational workflow capable of accounting for collective behaviors involving different degrees of freedom and occurring at large time/length scales, paving the way for precise modeling and control of quantum effects in materials.},

keywords = {P03, P07},

pubstate = {published},

tppubtype = {article}

}

@article{Liu2023,

title = {Combining Machine Learning and Many-Body Calculations: Coverage-Dependent Adsorption of CO on Rh(111)},

author = {Peitao Liu and Jiantao Wang and Noah Avargues and Carla Verdi and Andreas Singraber and Ferenc Karsai and Xing-Qiu Chen and Georg Kresse},

doi = {10.1103/physrevlett.130.078001},

year  = {2023},

date = {2023-02-17},

urldate = {2023-02-01},

journal = {Physical Review Letters},

volume = {130},

number = {7},

pages = {078001},

publisher = {American Physical Society (APS)},

abstract = {Adsorption of carbon monoxide (CO) on transition-metal surfaces is a prototypical process in surface sciences and catalysis. Despite its simplicity, it has posed great challenges to theoretical modeling. Pretty much all existing density functionals fail to accurately describe surface energies and CO adsorption site preference as well as adsorption energies simultaneously. Although the random phase approximation (RPA) cures these density functional theory failures, its large computational cost makes it prohibitive to study the CO adsorption for any but the simplest ordered cases. Here, we address these challenges by developing a machine-learned force field (MLFF) with near RPA accuracy for the prediction of coverage-dependent adsorption of CO on the Rh(111) surface through an efficient on-the-fly active learning procedure and a Δ-machine learning approach. We show that the RPA-derived MLFF is capable to accurately predict the Rh(111) surface energy and CO adsorption site preference as well as adsorption energies at different coverages that are all in good agreement with experiments. Moreover, the coverage-dependent ground-state adsorption patterns and adsorption saturation coverage are identified.},

keywords = {P03},

pubstate = {published},

tppubtype = {article}

}

@article{Raab2023,

title = {Emergence of chaos in a compartmentalized catalytic reaction nanosystem},

author = {Maximilian Raab and Johannes Zeininger and Yuri Suchorski and Keita Tokuda and Günther Rupprechter},

doi = {10.1038/s41467-023-36434-y},

year  = {2023},

date = {2023-02-10},

urldate = {2023-02-01},

journal = {Nature Communications},

volume = {14},

pages = {736--745},

publisher = {Springer Science and Business Media LLC},

abstract = {In compartmentalized systems, chemical reactions may proceed in differing ways even in adjacent compartments. In compartmentalized nanosystems, the reaction behaviour may deviate from that observed on the macro- or mesoscale. In situ studies of processes in such nanosystems meet severe experimental challenges, often leaving the field to theoretical simulations. Here, a rhodium nanocrystal surface consisting of different nm-sized nanofacets is used as a model of a compartmentalized reaction nanosystem. Using field emission microscopy, different reaction modes are observed, including a transition to spatio-temporal chaos. The transitions between different modes are caused by variations of the hydrogen pressure modifying the strength of diffusive coupling between individual nanofacets. Microkinetic simulations, performed for a network of 52 coupled oscillators, reveal the origins of the different reaction modes. Since diffusive coupling is characteristic for many living and non-living compartmentalized systems, the current findings may be relevant for a wide class of reaction systems.},

keywords = {P08},

pubstate = {published},

tppubtype = {article}

}

@article{Maqbool2023,

title = {\textit{Operando} monitoring of a room temperature nanocomposite methanol sensor},

author = {Qaisar Maqbool and Nevzat Yigit and Michael Stöger-Pollach and Maria Letizia Ruello and Francesca Tittarelli and Günther Rupprechter},

doi = {10.1039/d2cy01395a},

year  = {2023},

date = {2023-02-07},

urldate = {2023-02-07},

journal = {Catalysis Science & Technology},

volume = {13},

issue = {3},

pages = {624--636},

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

abstract = {The sensing of volatile organic compounds by composites containing metal oxide semiconductors is typically explained via adsorption–desorption and surface electrochemical reactions changing the sensor's resistance. The analysis of molecular processes on chemiresistive gas sensors is often based on indirect evidence, whereas \textit{in situ} or \textit{operando} studies monitoring the gas/surface interactions enable a direct insight. Here we report a cross-disciplinary approach employing spectroscopy of working sensors to investigate room temperature methanol detection, contrasting well-characterized nanocomposite (TiO_{2}@rGO-NC) and reduced-graphene oxide (rGO) sensors. Methanol interactions with the sensors were examined by (quasi) \textit{operando}-DRIFTS and \textit{in situ}-ATR-FTIR spectroscopy, the first paralleled by simultaneous measurements of resistance. The sensing mechanism was also studied by mass spectroscopy (MS), revealing the surface electrochemical reactions. The \textit{operando} and \textit{in situ} spectroscopy techniques demonstrated that the sensing mechanism on the nanocomposite relies on the combined effect of methanol reversible physisorption and irreversible chemisorption, sensor modification over time, and electron/O_{2} depletion–restoration due to a surface electrochemical reaction forming CO_{2} and H_{2}O.},

keywords = {P08},

pubstate = {published},

tppubtype = {article}

}

@article{Corrias2023,

title = {Automated Real-Space Lattice Extraction for Atomic Force Microscopy Images},

author = {Marco Corrias and Lorenzo Papa and Igor Sokolovíc and Viktor Birschitzky and Alexander Gorfer and Martin Setvin and Michael Schmid and Ulrike Diebold and Michele Reticcioli and Cesare Franchini},

doi = {10.1088/2632-2153/acb5e0},

year  = {2023},

date = {2023-01-24},

urldate = {2023-01-24},

journal = {Machine Learning: Science and Technology},

volume = {4},

pages = {015015},

abstract = {Analyzing atomically resolved images is a time-consuming process requiring solid experience and substantial human intervention. In addition, the acquired images contain a large amount of information such as crystal structure, presence and distribution of defects, and formation of domains, which need to be resolved to understand a material's surface structure. Therefore, machine learning techniques have been applied in scanning probe and electron microscopies during the last years, aiming for automatized and efficient image analysis. This work introduces a free and open source tool (AiSurf: Automated Identification of Surface Images) developed to inspect atomically resolved images via Scale-Invariant Feature Transform (SIFT) and Clustering Algorithms (CA). AiSurf extracts primitive lattice vectors, unit cells, and structural distortions from the original image, with no pre-assumption on the lattice and minimal user intervention. The method is applied to various atomically resolved non-contact atomic force microscopy (AFM) images of selected surfaces with different levels of complexity: anatase TiO_{2}(101), oxygen deficient rutile TiO_{2}(110) with and without CO adsorbates, SrTiO_{3}(001) with Sr vacancies and graphene with C vacancies. The code delivers excellent results and is tested against atom misclassification and artifacts, thereby facilitating the interpretation of scanning probe microscopy images.},

keywords = {P02, P07},

pubstate = {published},

tppubtype = {article}

}

@article{Schmid2022,

title = {Analysis of Temperature-Programmed Desorption via Equilibrium Thermodynamics},

author = {Michael Schmid and Gareth S. Parkinson and Ulrike Diebold},

doi = {10.1021/acsphyschemau.2c00031},

year  = {2022},

date = {2022-11-15},

journal = {ACS Physical Chemistry Au},

volume = {3},

issue = {1},

pages = {44--62},

publisher = {American Chemical Society (ACS)},

abstract = {Temperature-programmed desorption (TPD) experiments in surface science are usually analyzed using the Polanyi–Wigner equation and/or transition-state theory. These methods are far from straightforward, and the determination of the pre-exponential factor is often problematic. We present a different method based on equilibrium thermodynamics, which builds on an approach previously used for TPD by Kreuzer et al. (\textit{Surf. Sci.}\textbf{1988}). Equations for the desorption rate are presented for three different types of surface–adsorbate interactions: (i) a 2D ideal hard-sphere gas with a negligible diffusion barrier, (ii) an ideal lattice gas, that is, fixed adsorption sites without interaction between the adsorbates, and (iii) a lattice gas with a distribution of (site-dependent) adsorption energies. We show that the coverage dependence of the sticking coefficient for adsorption at the desorption temperature determines whether the desorption process can be described by first- or second-order kinetics. The sticking coefficient at the desorption temperature must also be known for a quantitative determination of the adsorption energy, but it has a rather weak influence (like the pre-exponential factor in a traditional TPD analysis). Quantitative analysis is also influenced by the vibrational contributions to the energy and entropy. For the case of a single adsorption energy, we provide equations to directly convert peak temperatures into adsorption energies. These equations also provide an approximation of the desorption energy in cases that cannot be described by a fixed pre-exponential factor. For the case of a distribution of adsorption energies, the desorption spectra cannot be considered a superposition of desorption spectra corresponding to the different energies. Nevertheless, we present a method to extract the distribution of adsorption energies from TPD spectra, and we rationalize the energy resolution of TPD experiments. The analytical results are complemented by a program for simulation and analysis of TPD data.},

keywords = {P02, P04},

pubstate = {published},

tppubtype = {article}

}

@article{Zeininger2022,

title = {Reaction Modes on a Single Catalytic Particle: Nanoscale Imaging and Micro-Kinetic Modeling},

author = {Johannes Zeininger and Maximilian Raab and Yuri Suchorski and Sebastian Buhr and Michael Stöger-Pollach and Johannes Bernardi and Günther Rupprechter},

doi = {10.1021/acscatal.2c02901},

year  = {2022},

date = {2022-10-07},

journal = {ACS Catalysis},

volume = {12},

number = {20},

pages = {12774--12785},

publisher = {American Chemical Society (ACS)},

abstract = {The kinetic behavior of individual Rh(\textit{hkl}) nanofacets coupled in a common reaction system was studied using the apex of a curved rhodium microcrystal (radius of 0.65 μm) as a model of a single catalytic particle and field electron microscopy for in situ imaging of catalytic hydrogen oxidation. Depending on the extent of interfacet coupling via hydrogen diffusion, different oscillating reaction modes were observed including highly unusual multifrequential oscillations: differently oriented nanofacets oscillated with differing frequencies despite their immediate neighborhood. The transitions between different modes were induced by variations in the particle temperature, causing local surface reconstructions, which create locally protruding atomic rows. These atomic rows modified the coupling strength between individual nanofacets and caused the transitions between different oscillating modes. Effects such as entrainment, frequency locking, and reconstruction-induced collapse of spatial coupling were observed. To reveal the origin of the different experimentally observed effects, microkinetic simulations were performed for a network of 105 coupled oscillators, modeling the individual nanofacets communicating via hydrogen surface diffusion. The calculated behavior of the oscillators, the local frequencies, and the varying degree of spatial synchronization describe the experimental observations well.},

keywords = {P08},

pubstate = {published},

tppubtype = {article}

}

@article{Zeininger2022a,

title = {Pattern Formation in Catalytic H_{2} Oxidation on Rh: Zooming in by Correlative Microscopy},

author = {Johannes Zeininger and Philipp Winkler and Maximilian Raab and Yuri Suchorski and Mauricio J. Prieto and Liviu C. Tănase and Lucas Souza Caldas and Aarti Tiwari and Thomas Schmidt and Michael Stöger-Pollach and Andreas Steiger-Thirsfeld and Beatriz Roldan Cuenya and Günther Rupprechter},

doi = {10.1021/acscatal.2c03692},

year  = {2022},

date = {2022-09-19},

urldate = {2022-09-19},

journal = {ACS Catalysis},

volume = {12},

number = {19},

pages = {11974--11983},

publisher = {American Chemical Society (ACS)},

abstract = {Spatio-temporal nonuniformities in H_{2} oxidation on individual Rh(\textit{h k l}) domains of a polycrystalline Rh foil were studied in the 10^{–6} mbar pressure range by photoemission electron microscopy (PEEM), X-ray photoemission electron microscopy (XPEEM), and low-energy electron microscopy (LEEM). The latter two were used for in situ correlative microscopy to zoom in with significantly higher lateral resolution, allowing detection of an unusual island-mediated oxygen front propagation during kinetic transitions. The origin of the island-mediated front propagation was rationalized by model calculations based on a hybrid approach of microkinetic modeling and Monte Carlo simulations.},

keywords = {P08},

pubstate = {published},

tppubtype = {article}

}