Publications

@article{Redondo2023,

title = {Hematite α-Fe_{2}O_{3}(0001) in Top and Side View: Resolving Long-Standing Controversies about Its Surface Structure},

author = {Jesús Redondo and Jan Michalička and Florian Kraushofer and Giada Franceschi and Břetislav Šmid and Nishant Kumar and Ondřej Man and Matthias Blatnik and Dominik Wrana and Benjamin Mallada and Martin Švec and Gareth S. Parkinson and Martin Setvin and Michele Riva and Ulrike Diebold and Jan Čechal},

doi = {10.1002/admi.202300602},

year  = {2023},

date = {2023-08-18},

urldate = {2023-08-18},

journal = {Advanced Materials Interfaces},

number = {2300602},

publisher = {Wiley},

abstract = {Hematite is a common iron oxide found in nature, and the α-Fe_{2}O_{3}(0001) plane is prevalent on the nanomaterial utilized in photo- and electrocatalytic applications. The atomic-scale structure of the surface remains controversial despite decades of study, partly because it depends on sample history as well as the preparation conditions. Here, a comprehensive study is performed using an arsenal of surface techniques (non-contact atomic force microscopy, scanning tunneling microscopy, low-energy electron diffraction, and X-ray photoemission spectroscopy) complemented by analyses of the near surface region by high-resolution transmission electron microscopy and electron energy loss spectroscopy. The results show that the so-called “bi-phase” termination forms even under highly oxidizing conditions; a (1 × 1) surface is only observed in the presence of impurities. Furthermore, it is shown that the biphase is actually a continuous layer distorted due to a mismatch with the subsurface layers, and thus not the proposed mixture of FeO(111) and α-Fe_{2}O_{3}(0001) phases. Overall, the results show how combining surface and cross-sectional imaging provides a full view that can be essential for understanding the role of the near-surface region on oxide surface properties.},

keywords = {P02, P04},

pubstate = {published},

tppubtype = {article}

}

@article{Tangpakonsab2023,

title = {Kinetic and Computational Studies of CO Oxidation and PROX on Cu/CeO_{2} Nanospheres},

author = {Parinya Tangpakonsab and Alexander Genest and Jingxia Yang and Ali Meral and Bingjie Zou and Nevzat Yigit and Sabine Schwarz and Günther Rupprechter},

doi = {10.1007/s11244-023-01848-x},

year  = {2023},

date = {2023-07-31},

journal = {Topics in Catalysis},

volume = {66},

pages = {1129--1142},

publisher = {Springer Science and Business Media LLC},

abstract = {As supported CuO is well-known for low temperature activity, CuO/CeO_{2} nanosphere catalysts were synthesized and tested for CO oxidation and preferential oxidation of CO (PROX) in excess H_{2}. For the first reaction, ignition was observed at 95 °C, whereas selective PROX occurred in a temperature window from 50 to 100 °C. The catalytic performance was independent of the initial oxidation state of the catalyst (CuO vs. Cu^{0}), suggesting that the same active phase is formed under reaction conditions. Density functional modeling was applied to elucidate the intermediate steps of CO oxidation, as well as those of the comparably less feasible H_{2} transformation. In the simulations, various Cu and vacancy sites were probed as reactive centers enabling specific pathways.},

keywords = {P08},

pubstate = {published},

tppubtype = {article}

}

@article{Asencios2023,

title = {Partial Oxidation of Bio-methane over Nickel Supported on MgO–ZrO_{2} Solid Solutions},

author = {Yvan J. O. Asencios and Nevzat Yigit and Thomas Wicht and Michael Stöger-Pollach and Alessandra F. Lucrédio and Francielle C. F. Marcos and Elisabete M. Assaf and Günther Rupprechter},

doi = {10.1007/s11244-023-01822-7},

year  = {2023},

date = {2023-05-24},

journal = {Topics in Catalysis},

publisher = {Springer Science and Business Media LLC},

abstract = {Syngas can be produced from biomethane via Partial Oxidation of Methane (POM), being an attractive route since it is ecofriendly and sustainable. In this work, catalysts of Ni supported on MgO–ZrO_{2} solid solutions, prepared by a one-step polymerization method, were characterized by HRTEM/EDX, XRD, XPS, H_{2}-TPR, and in situ XRD. All catalysts, including Ni/ZrO_{2} and Ni/MgO as reference, were tested for POM (CH_{4}:O_{2} molar ratio 2, 750 ºC, 1 atm). NiO/MgO/ZrO_{2} contained two solid-solutions, MgO–ZrO2 and NiO-MgO, as revealed by XRD and XPS. Ni (30 wt%) supported on MgO–ZrO_{2} solid solution exhibited high methane conversion and hydrogen selectivity. However, depending on the MgO amount (0, 4, 20, 40, 100 molar percent) major differences in NiO reducibility, growth of Ni^{0} crystallite size during H_{2} reduction and POM, and in carbon deposition rates were observed. Interestingly, catalysts with lower MgO content achieved the highest CH_{4} conversion (~ 95%), high selectivity to H_{2} (1.7) and CO (0.8), and low carbon deposition rates (0.024 g_{carbon} g_{cat}^{−1} h^{−1}) with Ni_{4}MgZr (4 mol% MgO) turning out to be the best catalyst. In situ XRD during POM indicated metallic Ni nanoparticles (average crystallite size of 31 nm), supported by MgO–ZrO_{2} solid solution, with small amounts of NiO–MgO being present as well. The presence of MgO also influenced the morphology of the carbon deposits, leading to filaments instead of amorphous carbon. A combustion-reforming mechanism is suggested and using a MgO–ZrO_{2} solid solution support strongly improves catalytic performance, which is attributed to effective O_{2}, CO_{2} and H_{2}O activation at the Ni/MgO–ZrO_{2} interface.},

keywords = {P08},

pubstate = {published},

tppubtype = {article}

}

@article{doi:10.1021/acscatal.3c00060,

title = {Imaging Interface and Particle Size Effects by In Situ Correlative Microscopy of a Catalytic Reaction},

author = {Philipp Winkler and Maximilian Raab and Johannes Zeininger and Lea M. Rois and Yuri Suchorski and Michael Stöger-Pollach and Matteo Amati and Rahul Parmar and Luca Gregoratti and Günther Rupprechter},

doi = {10.1021/acscatal.3c00060},

year  = {2023},

date = {2023-05-23},

urldate = {2023-01-01},

journal = {ACS Catalysis},

volume = {13},

number = {11},

pages = {7650--7660},

abstract = {The catalytic behavior of Rh particles supported by three different materials (Rh, Au, and ZrO_{2_{) in H_{2_{ oxidation has been studied in situ by correlative photoemission electron microscopy (PEEM) and scanning photoemission electron microscopy (SPEM). Kinetic transitions between the inactive and active steady states were monitored, and self-sustaining oscillations on supported Rh particles were observed. Catalytic performance differed depending on the support and Rh particle size. Oscillations varied from particle size-independent (Rh/Rh) via size-dependent (Rh/ZrO_{2_{) to fully inhibited (Rh/Au). For Rh/Au, the formation of a surface alloy induced such effects, whereas for Rh/ZrO_{2_{, the formation of substoichiometric Zr oxides on the Rh surface, enhanced oxygen bonding, Rh-oxidation, and hydrogen spillover onto the ZrO_{2_{ support were held responsible. The experimental observations were complemented by micro-kinetic simulations, based on variations of hydrogen adsorption and oxygen binding. The results demonstrate how correlative in situ surface microscopy enables linking of the local structure, composition, and catalytic performance.},

keywords = {P08},

pubstate = {published},

tppubtype = {article}

}

@article{Carrete2023,

title = {Deep ensembles vs committees for uncertainty estimation in neural-network force fields: Comparison and application to active learning},

author = {Jesús Carrete and Hadrián Montes-Campos and Ralf Wanzenböck and Esther Heid and Georg K. H. Madsen},

doi = {10.1063/5.0146905},

year  = {2023},

date = {2023-05-22},

journal = {The Journal of Chemical Physics},

volume = {158},

number = {20},

pages = {204801-1--204801-18},

publisher = {AIP Publishing},

abstract = {A reliable uncertainty estimator is a key ingredient in the successful use of machine-learning force fields for predictive calculations. Important considerations are correlation with error, overhead during training and inference, and efficient workflows to systematically improve the force field. However, in the case of neural-network force fields, simple committees are often the only option considered due to their easy implementation. Here, we present a generalization of the deep-ensemble design based on multiheaded neural networks and a heteroscedastic loss. It can efficiently deal with uncertainties in both energy and forces and take sources of aleatoric uncertainty affecting the training data into account. We compare uncertainty metrics based on deep ensembles, committees, and bootstrap-aggregation ensembles using data for an ionic liquid and a perovskite surface. We demonstrate an adversarial approach to active learning to efficiently and progressively refine the force fields. That active learning workflow is realistically possible thanks to exceptionally fast training enabled by residual learning and a nonlinear learned optimizer.},

keywords = {P09},

pubstate = {published},

tppubtype = {article}

}

@article{Jung2023,

title = {Machine-guided path sampling to discover mechanisms of molecular self-organization},

author = {Hendrik Jung and Roberto Covino and A. Arjun and Christian Leitold and Christoph Dellago and Peter G. Bolhuis and Gerhard Hummer},

doi = {10.1038/s43588-023-00428-z},

year  = {2023},

date = {2023-04-24},

journal = {Nature Computational Science},

volume = {3},

number = {4},

pages = {334--345},

publisher = {Springer Science and Business Media LLC},

abstract = {Molecular self-organization driven by concerted many-body interactions produces the ordered structures that define both inanimate and living matter. Here we present an autonomous path sampling algorithm that integrates deep learning and transition path theory to discover the mechanism of molecular self-organization phenomena. The algorithm uses the outcome of newly initiated trajectories to construct, validate and—if needed—update quantitative mechanistic models. Closing the learning cycle, the models guide the sampling to enhance the sampling of rare assembly events. Symbolic regression condenses the learned mechanism into a human-interpretable form in terms of relevant physical observables. Applied to ion association in solution, gas-hydrate crystal formation, polymer folding and membrane-protein assembly, we capture the many-body solvent motions governing the assembly process, identify the variables of classical nucleation theory, uncover the folding mechanism at different levels of resolution and reveal competing assembly pathways. The mechanistic descriptions are transferable across thermodynamic states and chemical space.},

keywords = {P12},

pubstate = {published},

tppubtype = {article}

}

@article{Kraushofer2023,

title = {Oxygen-Terminated (1 × 1) Reconstruction of Reduced Magnetite Fe_{3}O_{4}(111)},

author = {Florian Kraushofer and Matthias Meier and Zdeněk Jakub and Johanna Hütner and Jan Balajka and Jan Hulva and Michael Schmid and Cesare Franchini and Ulrike Diebold and Gareth S. Parkinson},

doi = {10.1021/acs.jpclett.3c00281},

year  = {2023},

date = {2023-03-28},

urldate = {2023-03-28},

volume = {14},

number = {13},

pages = {3258--3265},

publisher = {American Chemical Society (ACS)},

abstract = {The (111) facet of magnetite (Fe_{3}O_{4}) has been studied extensively by experimental and theoretical methods, but controversy remains regarding the structure of its low-energy surface terminations. Using density functional theory (DFT) computations, we demonstrate three reconstructions that are more favorable than the accepted Feoct2 termination under reducing conditions. All three structures change the coordination of iron in the kagome Feoct1 layer to be tetrahedral. With atomically resolved microscopy techniques, we show that the termination that coexists with the Fetet1 termination consists of tetrahedral iron capped by 3-fold coordinated oxygen atoms. This structure explains the inert nature of the reduced patches.},

keywords = {P02, P04, P07},

pubstate = {published},

tppubtype = {article}

}

@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}

}