Formation of Epitaxial PdO(100) During the Oxidation of Pd(100).

The catalytic oxidation of CO and CH4 can be strongly influenced by the structures of oxide phases that form on metallic catalysts during reaction. Here, we show that an epitaxial PdO(100) structure forms at temperatures above 600 K during the oxidation of Pd(100) by gaseous O atoms as well as exposure to O2-rich mixtures at millibar partial pressures. The oxidation of Pd(100) by gaseous O atoms preferentially generates an epitaxial, multilayer PdO(101) structure at 500 K, but initiating Pd(100) oxidation above 600 K causes an epitaxial PdO(100) structure to grow concurrently with PdO(101) and produces a thicker and rougher oxide. We present evidence that this change in the oxidation behavior is caused by a temperature-induced change in the stability of small PdO domains that initiate oxidation. Our discovery of the epitaxial PdO(100) structure may be significant for developing relationships among oxide structure, catalytic activity, and reaction conditions for applications of oxidation catalysis.

Structure of an Ultrathin Oxide on Pt3 Sn(111) Solved by Machine Learning Enhanced Global Optimization.

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 Pt3 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.

Structure of an Ultrathin Oxide on Pt3Sn(111) Solved by Machine Learning Enhanced Global Optimization.

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 Pt3Sn(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.

HIPPIE: a new platform for ambient-pressure X-ray photoelectron spectroscopy at the MAX IV Laboratory.

HIPPIE is a soft X-ray beamline on the 3 GeV electron storage ring of the MAX IV Laboratory, equipped with a novel ambient-pressure X-ray photoelectron spectroscopy (APXPS) instrument. The endstation is dedicated to performing in situ and operando X-ray photoelectron spectroscopy experiments in the presence of a controlled gaseous atmosphere at pressures up to 30 mbar [1 mbar = 100 Pa] as well as under ultra-high-vacuum conditions. The photon energy range is 250 to 2200 eV in planar polarization and with photon fluxes >1012 photons s-1 (500 mA ring current) at a resolving power of greater than 10000 and up to a maximum of 32000. The endstation currently provides two sample environments: a catalysis cell and an electrochemical/liquid cell. The former allows APXPS measurements of solid samples in the presence of a gaseous atmosphere (with a mixture of up to eight gases and a vapour of a liquid) and simultaneous analysis of the inlet/outlet gas composition by online mass spectrometry. The latter is a more versatile setup primarily designed for APXPS at the solid-liquid (dip-and-pull setup) or liquid-gas (liquid microjet) interfaces under full electrochemical control, and it can also be used as an open port for ad hoc-designed non-standard APXPS experiments with different sample environments. The catalysis cell can be further equipped with an IR reflection-absorption spectrometer, allowing for simultaneous APXPS and IR spectroscopy of the samples. The endstation is set up to easily accommodate further sample environments.

Catalytic Oxidation of Carbon Monoxide on a Curved Pd Crystal: Spatial Variation of Active and Poisoning Phases in Stationary Conditions.

Understanding nanoparticle catalysis requires novel approaches in which adjoining crystal orientations can be studied under the same reactive conditions. Here we use a curved palladium crystal and near-ambient pressure X-ray photoemission spectroscopy to characterize chemical species during the catalytic oxidation of CO in a whole set of surfaces vicinal to the (111) direction simultaneously. By stabilizing the reaction at fixed temperatures around the ignition point, we observe a strong variation of the catalytic activity across the curved surface. Such spatial modulation of the reaction stage is straightforwardly mapped through the photoemission signal from active oxygen species and poisoning CO, which are shown to coexist in a transient regime that depends on the vicinal angle. Line-shape analysis and direct comparison with ultrahigh vacuum experiments help identifying and quantifying all such surface species, allowing us to reveal the presence of surface oxides during reaction ignition and cooling-off.

Steps Control the Dissociation of CO2 on Cu(100).

CO2 reduction reactions, which provide one route to limit the emission of this greenhouse gas, are commonly performed over Cu-based catalysts. Here, we use ambient pressure X-ray photoelectron spectroscopy together with density functional theory to obtain an atomistic understanding of the dissociative adsorption of CO2 on Cu(100). We find that the process is dominated by the presence of steps, which promote both a lowering of the dissociation barrier and an efficient separation between adsorbed O and CO, reducing the probability for recombination. The identification of steps as sites for efficient CO2 dissociation provides an understanding that can be used in the design of future CO2 reduction catalysts.

Thermal reduction of ceria nanostructures on rhodium(111) and re-oxidation by CO2.

The thermal reduction of cerium oxide nanostructures deposited on a rhodium(111) single crystal surface and the re-oxidation of the structures by exposure to CO2 were investigated. Two samples are compared: a rhodium surface covered to ≈60% by one to two O-Ce-O trilayer high islands and a surface covered to ≈65% by islands of four O-Ce-O trilayer thickness. Two main results stand out: (1) the thin islands reduce at a lower temperature (870-890 K) and very close to Ce2O3, while the thicker islands need higher temperature for reduction and only reduce to about CeO1.63 at a maximum temperature of 920 K. (2) Ceria is re-oxidized by CO2. The rhodium surface promotes the re-oxidation by splitting the CO2 and thus providing atomic oxygen. The process shows a clear temperature dependence. The maximum oxidation state of the oxide reached by re-oxidation with CO2 differs for the two samples, showing that the thinner structures require a higher temperature for re-oxidation with CO2. Adsorbed carbon species, potentially blocking reactive sites, desorb from both samples at the same temperature and cannot be the sole origin for the observed differences. Instead, an intrinsic property of the differently sized CeOx islands must be at the origin of the observed temperature dependence of the re-oxidation by CO2.