Origin of the surface-orientation dependence of the reduction kinetics of ultrathin ceria

Performance of catalytic redox reactions depends crucially on the oxygen storage and release capability of the catalyst and with that the catalyst’s defect chemistry. Here, we show that the surface defect chemistry of cerium oxide, a prototypical reducible oxide, differs markedly between two surface terminations. The results are in good agreement with density functional theory calculations and provide important guiding factors for rational design of industrially relevant catalysts. The study is conducted by preparing (100) and (111) terminated nanoislands of cerium oxide next to each other on Cu(111). Leveraging the benefits of full-field imaging capability of photoemission electron microscopy (PEEM), we follow the structural and chemical properties of the nanoislands under reducing hydrogen atmosphere simultaneously and in situ. The results, summarized in Figure 1, directly reveal different overall reducibility that can be traced to equilibrium oxygen vacancy concentrations via a kinetic model. The density functional theory calculations provide further details regarding the equilibrium co-ordination of oxygen vacancies for both surface planes. Conjoining the two, the unique simultaneous nature of the PEEM-facilitated structure–activity relationship study allows us to separate the thermodynamics of reduction from the kinetics of oxygen exchange, revealing the fact that the difference in reducibility of the two surfaces of ceria is not determined by the kinetic rate constants of the reduction reaction, but rather by the equilibrium concentration of oxygen vacancies, an information that has not been provided by the isolated model system approach to date. Surprisingly, the reason for the different reducibilities is a purely geometric one: the creation of nearest neighbor oxygen vacancies. Please click Additional Files below to see the full abstract

Oxygen Vacancy Chemistry in Ceria

Cerium(IV) oxide (CeO2), ceria, is an active metal oxide used in solid oxide fuel cells and for the purification of exhaust gases in vehicle emissions control. Behind these technically important applications of ceria lies one overriding feature, namely ceria's exceptional reduction-oxidation properties. These are enabled by the duality of the cerium ion which easily toggles between Ce4+ and Ce3+. Here the cerium 4f electrons and oxygen vacancies (missing oxygen ions in the structure) are key players. In this thesis, the nature of ceria's f electrons and oxygen vacancies are in focus, and examined with theoretical calculations. It is shown that for single oxygen vacancies at ceria surfaces, the intimate coupling between geometrical structure and electron localisation gives a multitude of almost degenerate local energy mimima. With many vacancies, the situation becomes even more complex, and not even state-of-the-art quantum-mechanical calculations manage to predict the experimentally observed phenomenon of vacancy clustering. Instead, an alternative set of computer experiments managed to produce stable vacancy chains and trimers consistent with experimental findings from the literature and revealed a new general principle for surface vacancy clustering. The rich surface chemistry of ceria involves not only oxygen vacancies but also other active oxygen species such as superoxide ions (O2−). Experiments have shown that nanocrystalline ceria demonstrates an unusually large oxygen storage capacity (OSC) and an appreciable low-temperature redox activity, which have been ascribed to superoxide species. A mechanism explaining these phenomena is presented. The ceria surface is also known to interact with SOx molecules, which is relevant both in the context of sulfur poisoning of ceria-based catalysts and sulfur recovery from them. In this thesis, the sulfur species and key mechanisms involved are identified

Oxygen Vacancy Chemistry in Ceria

Cerium(IV) oxide (CeO2), ceria, is an active metal oxide used in solid oxide fuel cells and for the purification of exhaust gases in vehicle emissions control. Behind these technically important applications of ceria lies one overriding feature, namely ceria's exceptional reduction-oxidation properties. These are enabled by the duality of the cerium ion which easily toggles between Ce4+ and Ce3+. Here the cerium 4f electrons and oxygen vacancies (missing oxygen ions in the structure) are key players. In this thesis, the nature of ceria's f electrons and oxygen vacancies are in focus, and examined with theoretical calculations. It is shown that for single oxygen vacancies at ceria surfaces, the intimate coupling between geometrical structure and electron localisation gives a multitude of almost degenerate local energy mimima. With many vacancies, the situation becomes even more complex, and not even state-of-the-art quantum-mechanical calculations manage to predict the experimentally observed phenomenon of vacancy clustering. Instead, an alternative set of computer experiments managed to produce stable vacancy chains and trimers consistent with experimental findings from the literature and revealed a new general principle for surface vacancy clustering. The rich surface chemistry of ceria involves not only oxygen vacancies but also other active oxygen species such as superoxide ions (O2−). Experiments have shown that nanocrystalline ceria demonstrates an unusually large oxygen storage capacity (OSC) and an appreciable low-temperature redox activity, which have been ascribed to superoxide species. A mechanism explaining these phenomena is presented. The ceria surface is also known to interact with SOx molecules, which is relevant both in the context of sulfur poisoning of ceria-based catalysts and sulfur recovery from them. In this thesis, the sulfur species and key mechanisms involved are identified

Oxygen Vacancy Chemistry in Ceria

Cerium(IV) oxide (CeO2), ceria, is an active metal oxide used in solid oxide fuel cells and for the purification of exhaust gases in vehicle emissions control. Behind these technically important applications of ceria lies one overriding feature, namely ceria's exceptional reduction-oxidation properties. These are enabled by the duality of the cerium ion which easily toggles between Ce4+ and Ce3+. Here the cerium 4f electrons and oxygen vacancies (missing oxygen ions in the structure) are key players. In this thesis, the nature of ceria's f electrons and oxygen vacancies are in focus, and examined with theoretical calculations. It is shown that for single oxygen vacancies at ceria surfaces, the intimate coupling between geometrical structure and electron localisation gives a multitude of almost degenerate local energy mimima. With many vacancies, the situation becomes even more complex, and not even state-of-the-art quantum-mechanical calculations manage to predict the experimentally observed phenomenon of vacancy clustering. Instead, an alternative set of computer experiments managed to produce stable vacancy chains and trimers consistent with experimental findings from the literature and revealed a new general principle for surface vacancy clustering. The rich surface chemistry of ceria involves not only oxygen vacancies but also other active oxygen species such as superoxide ions (O2−). Experiments have shown that nanocrystalline ceria demonstrates an unusually large oxygen storage capacity (OSC) and an appreciable low-temperature redox activity, which have been ascribed to superoxide species. A mechanism explaining these phenomena is presented. The ceria surface is also known to interact with SOx molecules, which is relevant both in the context of sulfur poisoning of ceria-based catalysts and sulfur recovery from them. In this thesis, the sulfur species and key mechanisms involved are identified

Photoinduced Adsorption and Oxidation of SO2 on Anatase TiO2(101)

Adsorption of molecules is a fundamental step in all heterogeneous catalytic reactions. Nevertheless, the basic mechanism by which photon-mediated adsorption processes occur on solid surfaces is poorly understood, mainly because they involve excited catalyst states that complicate the analysis. Here we demonstrate a method by which density functional theory (DFT) can be used to quantify photoinduced adsorption processes on transition metal oxides and reveal the fundamental nature of these reactions. Specifically, the photoadsorption of SO2 on TiO2(101) has been investigated by using a combination of DFT and in situ diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS). The combined experimental and theoretical approach gives a detailed description of the photocatalytic desulfurization process on TiO2, in which sulfate forms as a stable surface product that is known to poison the catalytic surface. This work identifies surface-SO42– as the sulfate species responsible for the surface poisoning and shows how this product can be obtained from a stepwise oxidation of SO2 on TiO2(101). Initially, the molecule binds to a lattice O2– ion through a photomediated adsorption process and forms surface sulfite, which is subsequently oxidized into surface-SO42– by transfer of a neutral oxygen from an adsorbed O2 molecule. The work further explains how the infrared spectra associated with this oxidation product change during interactions with water and surface hydroxyl groups, which can be used as fingerprints for the surface reactions. The approach outlined here can be generalized to other photo- and electrocatalytic transition metal oxide systems

Adsorption and Catalytic Oxidation of NO2 on Anatase TiO2 : Concerted Nitrate Interaction and Photon-Stimulated Reaction

The catalytic and photon-induced oxidation of NO2 on anatase TiO2 has been studied and compared with the surface nitrate species obtained after adsorption of HNO3. Using a combination of in situ diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS), density functional theory (DFT), and temperature-programmed desorption (TPD), it is shown that identical products are obtained in all reaction systems but that their formation rates differ significantly. The surface reaction products are identified as combinations of surface–NO3– species, where NO2 bonds to the lattice oxygen, and freely adsorbed NO3– ions. These products can be obtained either by dissociative adsorption of HNO3 or by catalytic/photocatalytic oxidation of NO2, which is facilitated by UV light. A concerted reaction mechanism is unraveled that involves reorientation of bidentate nitrate that pushes out a neighboring protonated lattice oxygen to form a surface–NO3– species and a terminal OH group. The thermal stability of these surface species has been studied by means of TPD and simultaneous in situ DRIFTS measurements that reveal a main desorption peak (m/z = 46) at around 430 °C, which is attributed to concerted nitrate desorption through pentoxide (N2O5) formation. A weaker and broader TPD peak is found at about 185 °C and is attributed to desorption of nitrate species bonded in a compressed configuration. The experimental results can be explained by the changing stability of the identified nitrate products, which depends strongly on the surface chemical environment and the surface coverage. The DFT results show that the stabilization of intermediate NO2 adsorbates and the final nitrate reaction products occurs through a bifunctional charge exchange mechanism that is mediated by the TiO2 crystal. In particular, a stable surface–NO3– and NO3– ion pair configuration has been identified. This mechanism explains both the thermal and photoinduced oxidation of NO2 and their thermal stability and different formation rates, yielding high photoinduced oxidation reaction rates. Our results provide insights into the structure and chemical stability of nitrate surface products on TiO2 particles and their formation mechanism, which is important for understanding their catalyzed transformation into the harmful compounds HONO and N2O during continued UV light illumination.Title of manuscript version in list of papers for David Langhammer: Adsorption and Catalytic Oxidation of NO2 on Anatase TiO2: A Combined DFT and Operando DRIFT Spectroscopy StudyAuthors of manuscript version in list of papers for David Langhammer: David Langhammar, Lars Österlund</p

Water in Crystals : A Database for ML and a Knowledge Base for Vibrational Prediction

Hydrate crystals are excellent reference systems to learnaboutaqueous systems. We have created a database of density functionaltheory (DFT)-optimized (optPBE-vdW) structures and vibrational frequenciesfor 101 crystalline hydrate and hydroxide bulk systems and over 300unique oscillators and use it to explore and discuss the tradeoffbetween prediction accuracy and insight. Starting from a machine-learninggeometrical descriptor, we gradually include more physics/chemistryflavor in the descriptor and examine how the frequency predictionpower varies. The most accurate models are the machine-learned model(of modest insight) and a physically motivated model containing theelectric field and field gradient. Furthermore, detailed comparisonswith experimental correlations show that, where available data exists,our DFT results largely overlap with the experiment. A small blind-testshowed that our machine-learned (ML) descriptor model can be usedto predict experimental vibrational frequencies based only on theexperimental structures and our best-regressed model, with encouragingresults

Density Functional Tight Binding Theory Approach for the CO2 Reduction Reaction Paths on Anatase TiO2 Surfaces

Herein, we have investigated the CO2 reduction paths on the (101) anatase TiO2 surface using an approach based on the density functional tight binding (DFTB) theory. We analyzed the reaction paths for the conversion of carbon dioxide to methane by performing a large number of calculations with intermediates placed in various orientations and locations at the surface. Our results show that the least stable intermediate is CO2 H and therefore a key bottleneck is the reduction of CO2 to formic acid. Hydrogen adsorption is also weak and would also be a limiting factor, unless very high pressures of hydrogen are used. The results from our DFTB approach are in good agreement with the hybrid functional based density functional theory calculations presented in the literature

Controlling the metal work function through atomic-scale surface engineering

Adsorbate induced work function modification of Ni have been investigated by means of first-principles calculations. More specifically, the adsorption of Li, Na, Si, Zr, Pd, Pt, or Sn at various coverages on Ni low-index surface models have been considered. In the case of Sn, a more thorough investigation was performed comparing the adsorption as an overlayer structure with the case of surface alloy formation. Our calculations suggest that the most stable Sn@Ni configuration corresponds to a surface alloy, and here the Ni(100)c(2 × 2)-Sn, Ni(110)c(2 × 2)-Sn, and Ni(111)()R30-Sn surface alloys were found to display similar stability. Concerning the induced work function change, a different behaviour as a function of coverage was observed depending on the nature of the Sn@Ni surface model. Both overlayer adsorption and surface alloying were found to induce a work function decrease already at relatively low coverages ( 0.05 atom Å −2), regardless of the underlying surface orientation. However, while the work function obtained for stable surface alloys was found to monotonously decrease as the coverage increases, the work function for the stable overlayer structures goes through a minimum. For all investigated surface modifications, the change in work function was found to be consistent with the orientation of the charge transfer at the adsorbate–surface interface. The computed data in this work may serve as handles for experimental endeavours aiming to optimize properties of active materials through atomic-scale surface engineering

Improving the transferability of density functional theory predictions through correlation analysis : Structural and energetic properties of \mathrmNiX alloys (X=\mathrmC, \mathrmSi, \mathrmGe, \mathrmand \mathrmSn)

This work reports on the performance of density functional theory (DFT) for a series of single and binary systems, aiming for a quantitative description of NiX (X=C, Si, Ge, and Sn) alloys. Both semilocal GGA and a meta-GGA density functional, with and without dispersion corrections, are tested. We found in our study that no single functional simultaneously provides an accurate quantitative description of the investigated structural and energetic properties. However, the spread in computed DFT data could be rationalized in terms of the distribution of reduced density gradients and differences in the evolution of the exchange enhancement factors for different functionals. We demonstrate how to construct a regression model based on data from several density functionals that increases the predictivity of semilocal DFT. We foresee that the use of regression models (or extensions of it) can be valuable in the development of more accurate density functionals that in the future could provide a quantitative accuracy for complex multicomponent systems