The carbonation of silicate minerals is a key process in the Earth's carbon cycle and offers a promising avenue for long-term CO2 sequestration. However, the atomistic mechanisms by which CO2 is activated at silicate surfaces remain poorly understood, largely due to the intrinsic complexity and insulating nature of these materials. To close this gap, wollastonite (CaSiO3) is used as a model system. Noncontact atomic force microscopy (nc-AFM) with functionalized tips is combined with density functional theory (DFT) to investigate its lowest-energy (100) surface under ultrahigh vacuum (UHV). Upon cleaving the mineral in UHV, water vapor is released from the sample and spontaneously readsorbs into a previously unreported, exceptionally stable configuration. The resulting surface hydration layer promotes spontaneous CO2 chemisorption and the formation of surface carbonates with negligible kinetic barriers. Our results offer atomic-scale evidence of gas-phase carbonation on a silicate mineral, revealing a water-assisted pathway for CO2 capture that bypasses aqueous mineral dissolution.

Heating a long-range ordered adsorbate phase beyond its stability temperature does not necessarily result in a disordered phase; it can also break up into heavily fluctuating ordered domains. Temporal and/or spatial averaging over these fluctuations may give the impression of both a wrong periodicity and false symmetry elements such as nonexisting glide planes or rotational axes of incorrect order. This can happen in real space and reciprocal space, and also below liquid-nitrogen temperature, so that the true nature of the phase might remain undetected. We demonstrate this scenario at the catalytically active Rh(100) surface covered by 1/2 monolayer of oxygen, using quantitative low-energy electron diffraction, variable-temperature scanning tunneling microscopy, and density functional theory. Using the example of CO adsorption, we show that local symmetry can have a decisive influence on the binding energy and thus the chemical reactivity.

Quantitative low-energy electron diffraction (LEEDI(V) or LEEDI(E)), which evaluates the diffraction intensitiesIas a function of the electron energy, is a versatile technique for the study of surface structures. The technique is based on optimizing the agreement between experimental and calculated intensities. Today, the most commonly used measure of agreement is Pendry'sRfactorRP. WhileRPhas many advantages it also has severe shortcomings, as it is a noisy target function for optimization and very sensitive to small offsets of the intensity. Furthermore,RP=0, which is meant to imply perfect agreement between twoI(E)curves, can also be achieved by qualitatively very different curves. We present a modifiedRfactorRS, which can be used as a direct replacement forRP, but avoids these shortcomings. We also demonstrate thatRSis as good asRPor better in steering the optimization to the correct result in the case of imperfections in the experimental data, while another commonRfactor,RZJ(suggested by Zanazzi and Jona) is worse in this respect.

Infrared reflection absorption spectroscopy (IRAS) offers a powerful route to bridging the materials and pressure gaps between surface science and powder catalysis. Using a newly developed IRAS setup optimised for dielectric single crystals, we investigate CO adsorption on the model single-atom catalyst Rh/Fe3O4(001). IRAS resolves three species: monocarbonyls at isolated, twofold-coordinated Rh adatoms, monocarbonyls at fivefold-coordinated Rh atoms embedded in the surface, and gem-dicarbonyls at isolated, twofold-coordinated Rh adatoms. Under ultra-high vacuum (UHV) conditions, RhCO monocarbonyl species at adatom sites dominate. Rh(CO)(2)gem-dicarbonyl formation is kinetically hindered and occurs predominantly through CO-induced dissociation of Rh dimers rather than sequential adsorption of two CO molecules at an isolated, twofold Rh adatom. The sequential-adsorption pathway to Rh(CO)(2) becomes accessible at millibar CO pressures as evidenced by near-ambient-pressure scanning tunnelling microscopy (NAP-STM). These findings link the UHV behaviour to that expected under realistic reaction conditions. Assignments of the vibrational frequencies to individual species rely on isotopic labelling, thermal treatments, and a review of previous SPM, XPS, and TPD data, supported by density functional theory (DFT)-based calculations. While theory provides qualitative insight, such as the instability of dicarbonyls on fivefold-coordinated Rh atoms, it does not yet reproduce experimental frequencies quantitatively and is sensitive to the computational parameters, highlighting the need for robust experimental benchmarks. The spectroscopic fingerprints established here provide a reliable foundation for identifying Rh coordination environments in oxide-supported single-atom catalysts.

The behaviour of excess charges in ionic lattices, such as the formation of polarons and charge trapping at defect sites, influences the physical and chemical properties of materials and translates into applications in electronics, optics, photovoltaics, and catalysis. Here we show that the bulk-terminated SrTiO3(001) surface accumulates photoexcited charges and keeps the associated photovoltage for many days at cryogenic temperatures. A combination of scanning tunneling microscopy, atomic force microscopy (STM/AFM) and Kelvin probe force microscopy (KPFM) was used to measure this photovoltage and to localize the photoexcited charges with atomic precision down to the single-quasiparticle limit. Density functional theory (DFT) shows that holes favor localization at oxygen 2p orbitals adjacent to Sr vacancies, creating long-lived trapped states. The methodology presented here provides guidelines for imaging of charges trapped in the crystal lattice using noncontact AFM.

Water adsorption on silicate surfaces is a critical yet poorly understood process relevant to, e.g., mineral weathering and cement hydration. This study investigates the structure of water overlayers on a model calcium silicate, the lowest-energy (100) surface of wollastonite (CaSiO3). It combines atomically resolved non-contact atomic force microscopy (nc-AFM), acquired with qPlus sensors and functionalized tips in ultrahigh vacuum (UHV), with density functional theory (DFT) calculations employing the metaGGA r2SCAN+rVV10 functional. Adding incremental doses of water to the sample at cryogenic temperatures produces distinct structures governed by the competition between water-surface and water-water interactions. With two water molecules per surface unit cell, water-surface interactions dominate: In line with previous theoretical predictions, adsorbates follow the surface lattice. As the coverage increases, intermolecular hydrogen bonding competes with bonding to the surface, leading to the emergence of complex, coexisting patterns. While their small energy differences prevent an unambiguous identification of the most stable structure by DFT, the experimentally observed symmetries help constrain plausible structural models. Above a critical density of four water molecules per unit cell, water-water interactions prevail, and water clusters are formed. The results provide an atomic-scale framework for understanding water interactions with calcium silicate surfaces.

Abstract Alumina (Al2O3) is a key material for thin-film growth and heterogeneous catalysis, where the atomic surface structure critically impacts performance. Using noncontact atomic force microscopy (nc-AFM) combined with density functional theory (DFT) calculations, we challenge the common assumption that the unreconstructed α-Al2O3(0001) surface is atomically flat and uniformly Al-terminated. This widely accepted bulk termination satisfies polarity compensation requirements but results in highly undercoordinated Al cations at the surface. Despite substantial inward relaxation of these Al cations, we find that the (1 × 1) surface remains inherently metastable, relative to the thermodynamically stable $$(\sqrt{31} \times \sqrt{31}) $$ ( 31 × 31 ) R ± 9° surface reconstruction that forms at high temperatures above 1000 °C. Nc-AFM imaging of the unreconstructed surface reveals a rough and disordered morphology, with only nanometer-scale regions exhibiting the ordered Al-terminated (1 × 1) structure. Our results show that the unreconstructed Al2O3(0001) surface is intrinsically inhomogeneous, reconciling conflicting experimental observations and challenging the validity of commonly used atomistic models.

Alumina (Al_2O_3) is a key material for thin-film growth and heterogeneous catalysis, where the atomic surface structure critically impacts performance. Using noncontact atomic force microscopy (nc-AFM) combined with density functional theory (DFT) calculations, we challenge the common assumption that the unreconstructed α-Al_2O_3(0001) surface is atomically flat and uniformly Al-terminated. This widely accepted bulk termination satisfies polarity compensation requirements but results in highly undercoordinated surface Al cations at the surface. Despite substantial inward relaxation of these Al cations, we find that the (1 × 1) surface remains inherently metastable, relative to the thermodynamically stable (√(31)×√(31))R±9° surface reconstruction that forms at high temperatures above 1000 °C. Nc-AFM imaging of the unreconstructed surface reveals a rough and disordered morphology, with only nanometer-scale regions exhibiting the ordered Al-terminated (1 × 1) structure. Our results show that the unreconstructed Al_2O_3(0001) surface is intrinsically inhomogeneous, reconciling conflicting experimental observations and challenging the validity of commonly used atomistic models.

Hydrogen activation is a key elementary step in catalytic hydrogenation. In heterogeneous catalysis, it usually proceeds through dissociative adsorption on metal nanoparticles followed by surface diffusion or spillover, whereas homogeneous catalysts activate H2 through dihydride or dihydrogen intermediates at a single metal center. Here, we show that isolated Rh adatoms supported on Fe3O4(001) activate hydrogen through formation of a stable dihydride species without atomic H spillover. Temperature-programmed desorption, x-ray photoelectron spectroscopy, and scanning tunneling microscopy collectively reveal strong (≈1 eV) hydrogen adsorption exclusively at isolated Rh1 sites, while isotope-exchange experiments further demonstrate that hydrogen remains localized. Density-functional theory-based calculations indicate a barrierless conversion from molecular H2 to the dihydride, and random-phase approximation calculations further confirm the relative stability of the dihydride. Together, these results show that single-atom Rh sites cleave hydrogen through a dihydride pathway analogous to homogeneous complexes, establishing a mechanistic bridge between homogeneous and heterogeneous catalysis.

Hydrogen activation is a key elementary step in catalytic hydrogenation. In heterogeneous catalysis, it usually proceeds through dissociative adsorption on metal nanoparticles followed by surface diffusion or spillover, whereas homogeneous catalysts activate H 2 through dihydride or dihydrogen intermediates at a single metal center. Here, we show that isolated Rh adatoms supported on Fe 3 O 4 (001) activate hydrogen through formation of a stable dihydride species without atomic H spillover. Temperature‐programmed desorption, x‐ray photoelectron spectroscopy, and scanning tunneling microscopy collectively reveal strong (≈1 eV) hydrogen adsorption exclusively at isolated Rh 1 sites, while isotope‐exchange experiments further demonstrate that hydrogen remains localized. Density‐functional theory‐based calculations indicate a barrierless conversion from molecular H 2 to the dihydride, and random‐phase approximation calculations further confirm the relative stability of the dihydride. Together, these results show that single‐atom Rh sites cleave hydrogen through a dihydride pathway analogous to homogeneous complexes, establishing a mechanistic bridge between homogeneous and heterogeneous catalysis.

Research on sustainable energy has intensified to reduce greenhouse gas emissions, especially CO2. One promising strategy is the catalytic reduction of CO2 to methanol, and indium oxide (In2O3) has emerged as a highly efficient catalyst, with high turnover rates and selectivity. This work investigates methanol, the end product of CO2 reduction, and its interaction with the In2O3(111) surface. Utilizing an ultrahigh vacuum (UHV) environment, this study combines temperature-programmed desorption (TPD), X-ray photoelectron spectroscopy (XPS), noncontact atomic force microscopy (nc-AFM), scanning tunneling microscopy (STM), and density functional theory (DFT) calculations. The coverages investigated range from 1 to 12 methanol molecules per unit cell. The results are compared to water adsorption on In2O3(111), as the chemical behavior of both molecules is similar in many respects. At low coverage, the adsorption patterns and interactions with the In2O3(111) surface mirror those seen with water, including dissociative and molecular adsorption. The first three methanol molecules dissociate at specific sites within the surface unit cell, while molecular adsorption becomes favored for subsequent molecules at temperatures below 300 K. At the highest coverage (before multilayer adsorption) methanol and water exhibit distinct structures due to their differing hydrogen bonding capabilities.

Gem-dicarbonyls of transition metals supported on metal (oxide) surfaces are common intermediates in heterogeneous catalysis. While infrared (IR) spectroscopy is a standard tool for detecting these species on powder catalysts, the ill-defined crystallographic environment renders data interpretation challenging. In this work, we apply a multi-technique surface science approach to investigate rhodium gem-dicarbonyls on a single-crystalline rutile TiO2(110) surface. We combine spectroscopy, scanning probe microscopy, and density functional theory (DFT) to determine their location and coordination on the surface. IR spectroscopy shows the successful creation of gem-dicarbonyls on a titania single crystal by exposing deposited Rh atoms to CO gas, followed by annealing to 200-250 K. Low-temperature scanning tunneling microscopy (STM) and non-contact atomic force microscopy (nc-AFM) data reveal that these complexes are mostly aligned along the [001] crystallographic direction, corroborating theoretical predictions. Notably, X-ray photoelectron spectroscopy (XPS) data reveal multiple rhodium species on the surface, even when the IR spectra show only the signature of rhodium gem-dicarbonyls. As such, our results highlight the complex behavior of carbonyls on metal oxide surfaces, and demonstrate the necessity of multi-technique approaches for the adequate characterization of single-atom catalysts.

Two-dimensional electron liquids (2DELs) have increasing technological relevance for ultrafast electronics and spintronics, yet significant gaps in their fundamental understanding are exemplified on the prototypical SrTiO3. We correlate the exact SrTiO3(001) surface structure with distinct 2DELs through combined microscopic angle-resolved photoemission spectroscopy and non-contact atomic force microscopy on truly bulk-terminated surfaces that alleviate structural uncertainties inherent to this long-studied system. The SrO termination is shown to develop a 2DEL following the creation of oxygen vacancies, unlike the intrinsically metallic TiO2 termination. Differences in degeneracy of the 2DELs, with nearly the same band filling and identical band bending, are assigned to polar distortions of the Ti atoms in combination with spin order, supported with the extraction of fundamental electron-phonon coupling strength. These results not only resolve the ambiguities regarding 2DELs on SrTiO3 thus far, but also pave the way to manipulating band filling and spin order in oxide 2DELs in general.

Understanding how the physical and electronic structures of metal-oxide surfaces evolve under varying conditions is crucial for optimizing their performance in applications such as catalysis. In this study, we compute the surface phase diagram of the Fe3O4(001) facet using density functional theory (DFT)-based calculations, with an emphasis on understanding the terminations observed in surface science experiments. Our results reveal two stable terminations in addition to the subsurface cation vacancy (SCV) structure, which dominates under oxidizing conditions. The commonly reported octahedral Fe pair, also known as the Fe-dimer termination, is stable within an oxygen chemical potential range of -3.1 eV < μ O < -2.3 eV. We identify the lowest-energy structure of this surface as the one proposed by J. R. Rustad, E. Wasserman and A. R. Felmy, A Molecular Dynamics Investigation of Surface Reconstruction on Magnetite (001), Surf. Sci., 1999, 432, 1-2, where a tetrahedrally coordinated FeA atom is replaced by two octahedrally coordinated FeB atoms in the surface layer. This transformation serves as a precursor to the emergence of an FeO-like termination under highly reducing conditions. A key insight from our study is the importance of thoroughly sampling different charge-order configurations to identify the global minima across varying stoichiometries.

Surfaces of cubic perovskite oxides attract significant attention for their physical tunability and high potential for technical applications. Bulk-terminated surfaces are desirable for theoretical modeling and experimental reproducibility, yet there is a lack of methods for preparing such well-defined surfaces. We discuss a method for strain-assisted cleaving of perovskite single crystals, using a setup easily transferable between different experimental systems. The details of the cleaving device and the procedure were optimized in a systematic study on the model cubic perovskite oxide SrTiO3. The large-area morphology and typical distribution of surface terminations on cleaved SrTiO3(001) are presented, with specific guidelines on how to distinguish well-cleaved surfaces from conchoidally fractured ones. The cleaving is applicable to other cubic perovskites, as demonstrated on KTaO3(001) and BaTiO3(001). This approach opens up a pathway for obtaining high-quality surfaces of this promising class of materials.

As part of the Vienna package for Erlangen LEED, low-energy electron diffraction (ViPErLEED) project, computer programs have been developed for facile and user-friendly data extraction from movies of LEED images. The programs make use of some concepts from astronomical image processing and analysis. As a first step, flat-field and dark-frame corrections reduce the effects of inhomogeneities of the camera and screen. In a second step, for identifying all diffraction maxima ("spots"), it is sufficient to manually mark and label a single spot or very few spots. Then the program can automatically identify all other spots and determine the distortions of the image. This forms the basis for automatic spot tracking (i.e., following the spots as they move across the LEED screen) and intensity measurement. Even for complex structures with hundreds to a few thousand diffraction beams, this step takes less than a minute. The package also includes a program for further processing of these I(V ) curves (averaging of equivalent beams, manual and/or automatic selection, smoothing) as well as several utilities. The software is implemented as a set of plugins for the public-domain image processing program IMAGEJ and provided as an open-source package.

Quantitative low-energy electron diffraction [LEED I(V)] is a powerful method for surface-structure determination, based on a direct comparison of experimentally observed I(V) data with computations for a structure model. As the diffraction intensities I are highly sensitive to subtle structural changes, local structure optimization is essential for assessing the validity of a structure model and finding the best-fit structure. The calculation of diffraction intensities is well established, but the large number of evaluations required for reliable structural optimization renders it computationally demanding. The computational effort is mitigated by the tensor-LEED approximation, which accelerates optimization by applying a perturbative treatment of small deviations from a reference structure. Nevertheless, optimization of complex structures is a tedious process. Here, the problem of surface-structure optimization is reformulated using a tree-based data structure, which helps to avoid redundant function evaluations. In the new tensor-LEED implementation presented in this work, intensities are computed on the fly, eliminating limitations of previous algorithms that are limited to precomputed values at a grid of search parameters. It also enables the use of state-of-the-art optimization algorithms. Implemented in Python with the JAX library, the method provides access to gradients of the R factor and supports execution on graphics processing units (GPUs). Based on these developments, the computing time can be reduced by more than an order of magnitude.