Dehydrogenation of Ethylene on Supported Palladium Nanoparticles: A Double View from Metal and Hydrocarbon Sides

Restructuring of Palladium Nanoparticles during Oxidation by Molecular Oxygen

An interplay between Pd and PdO and their spatial distribution inside the particles are relevant for numerous catalytic reactions. Using in situ time-resolved X-ray absorption spectroscopy (XAS) supported by theoretical simulations, a mechanistic picture of the structural evolution of 2.3 nm palladium nanoparticles upon their exposure to molecular oxygen is provided. XAS analysis revealed the restructuring of the fcc-like palladium surface into the 4-coordinated structure of palladium oxide upon absorption of oxygen from the gas phase and formation of core@shell Pd@PdO structures. The reconstruction starts from the low-coordinated sites at the edges of palladium nanoparticles. Formation of the PdO shell does not affect the average Pd‒Pd coordination numbers, since the decrease of the size of the metallic core is compensated by a more spherical shape of the oxidized nanoparticles due to a weaker interaction with the support. The metallic core is preserved below 200 °C even after continuous exposure to oxygen, with its size decreasing insignificantly upon increasing the temperature, while above 200 °C, bulk oxidation proceeds. The Pd‒Pd distances in the metallic phase progressively decrease upon increasing the fraction of the Pd oxide due to the alignment of the cell parameters of the two phases.

Machine Learning for Quantitative Structural Information from Infrared Spectra: The Case of Palladium Hydride

Infrared spectroscopy (IR) is a widely used technique enabling to identify specific functional groups in the molecule of interest based on their characteristic vibrational modes or the presence of a specific adsorption site based on the characteristic vibrational mode of an adsorbed probe molecule. The interpretation of an IR spectrum is generally carried out within a fingerprint paradigm by comparing the observed spectral features with the features of known references or theoretical calculations. This work demonstrates a method for extracting quantitative structural information beyond this approach by application of machine learning (ML) algorithms. Taking palladium hydride formation as an example, Pd-H pressure-composition isotherms are reconstructed using IR data collected in situ in diffuse reflectance using CO molecule as a probe. To the best of the knowledge, this is the first example of the determination of continuous structural descriptors (such as interatomic distance and stoichiometric coefficient) from the fine structure of vibrational spectra, which opens new possibilities of using IR spectra for structural analysis.

Deep Reinforcement Learning Environment Approach Based on Nanocatalyst XAS Diagnostics Graphic Formalization

The most in-demand instrumental methods for new functional nanomaterial diagnostics employ synchrotron radiation, which is used to determine a material's electronic and local atomic structure. The high time and resource costs of researching at international synchrotron radiation centers and the problems involved in developing an optimal strategy and in planning the control of the experiments are acute. One possible approach to solving these problems involves the use of deep reinforcement learning agents. However, this approach requires the creation of a special environment that provides a reliable level of response to the agent's actions. As the physical experimental environment of nanocatalyst diagnostics is potentially a complex multiscale system, there are no unified comprehensive representations that formalize the structure and states as a single digital model. This study proposes an approach based on the decomposition of the experimental system into the original physically plausible nodes, with subsequent merging and optimization as a metagraphic representation with which to model the complex multiscale physicochemical environments. The advantage of this approach is the possibility to directly use the numerical model to predict the system states and to optimize the experimental conditions and parameters. Additionally, the obtained model can form the basic planning principles and allow for the optimization of the search for the optimal strategy with which to control the experiment when it is used as a training environment to provide different abstraction levels of system state reactions.

Atomistic simulations on the carbidisation processes in Pd nanoparticles

The formation of interstitial PdC _x nanoparticles (NPs) is investigated through DFT calculations. Insights on the mechanisms of carbidisation are obtained whilst the material's behaviour under conditions of increasing C-concentration is examined. Incorporation of C atoms in the Pd octahedral interstitial sites is occurring through the [111] facet with an activation energy barrier of 19.3-35.7 kJ mol^-1 whilst migration through the [100] facet corresponds to higher activation energy barriers of 124.5-127.4 kJ mol^-1. Furthermore, interstitial-type diffusion shows that C will preferentially migrate and reside at the octahedral interstitial sites in the subsurface region with limited mobility towards the core of the NP. For low C-concentrations, migration from the surface into the interstitial sites of the NPs is thermodynamically favored, resulting in the formation of interstitial carbide. Carbidisation reaction energies are exothermic up to 11-14% of C-concentration and slightly vary depending on the shape of the structure. The reaction mechanisms turn to endothermic for higher concentration levels showing that C will preferentially reside on the surface making the interstitial carbide formation unfavorable. As experimentally observed, our simulations confirm that there is a maximum concentration of C in Pd carbide NPs opening the way for further computational investigations on the activity of Pd carbides in directed catalysis.

Polymer Nanocomposite Containing Palladium Nanoparticles: Synthesis, Characterization, and Properties

Composite nanomaterials have been prepared through thermal decomposition of palladium diacetate. The composite contains palladium nanoparticles embedded in high-pressure polyethylene. The materials were studied by a number of different physico-chemical methods, such as transmission electron microscopy, X-ray diffraction, X-ray absorption spectroscopy, electron paramagnetic resonance, and EXAFS. The average size of the nanoparticles is 7.0 ± 0.5 nm. It is shown that with the decrease of metal content in the polymer matrix the average size of nanoparticles decreased from 7 to 6 nm, and the coordination number of palladium also decreased from 7 to 5.7. The mean size of palladium particles increases with the growing concentration of palladium content in the matrix. It is shown that the electrophysical properties of the material obtained depend on the filler concentration. The chemical composition of palladium components includes metallic palladium, palladium (III) oxide, and palladium dioxide. All samples have narrow lines (3-5 Oe) with a g factor of around two in the electron paramagnetic resonance (EPR) spectra. It is shown that EPR lines have uneven boarding by saturation lines investigation. The relaxation component properties are different for spectral components. It leads to the spectrum line width depending on the magnetic field value. At first approximation, the EPR spectra can be described as a sum of two Lorentzian function graphs, corresponding to the following two paramagnetic centers: one is on the surface, and one is inside the palladium particles. Some of the experimental characteristics were measured for the first time. The data obtained indicate interesting properties of palladium-based nanocomposites, which will be useful for obtaining products based on these materials.

Hydrogenation of ethylene over palladium: evolution of the catalyst structure by operando synchrotron-based techniques

Palladium-based catalysts are exploited on an industrial scale for the selective hydrogenation of hydrocarbons. The formation of palladium carbide and hydride phases under reaction conditions changes the catalytic properties of the material, which points to the importance of operando characterization for determining the relation between the relative fractions of the two phases and the catalyst performance. We present a combined time-resolved characterization by X-ray absorption spectroscopy (in both near-edge and extended regions) and X-ray diffraction of a working palladium-based catalyst during the hydrogenation of ethylene in a wide range of partial pressures of ethylene and hydrogen. Synergistic coupling of multiple techniques allowed us to follow the structural evolution of the palladium lattice as well as the transitions between the metallic, hydride and carbide phases of palladium. The nanometric dimensions of the particles resulted in the considerable contribution of both surface and bulk carbides to the X-ray absorption spectra. During the reaction, palladium carbide is formed, which does not lead to a loss of activity. Unusual contraction of the unit cell parameter of the palladium lattice in the spent catalyst was observed upon increasing hydrogen partial pressure.

The Effect of Shape-Controlled Pt and Pd Nanoparticles on Selective Catalytic Hydrodechlorination of Trichloroethylene

Tailoring the shape of nanoscale materials enables obtaining morphology-controlled surfaces exhibiting specific interactions with reactants during catalytic reactions. The specifics of nanoparticle surfaces control the catalytic performance, i.e., activity and selectivity. In this study, shape-controlled Platinum (Pt) and Palladium (Pd) nanoparticles with distinct morphology were produced, i.e., cubes and cuboctahedra for Pt and spheres and polyhedra/multiple-twins for Pd, with (100), (111 + 100), curved/stepped and (111) facets, respectively. These particles with well-tuned surfaces were subsequently deposited on a Zirconium oxide (ZrO2) support. The morphological characteristics of the particles were determined by high resolution transmission electron microscopy (HR-TEM) and X-ray diffraction (XRD), while their adsorption properties were investigated by Fourier transform infrared spectroscopy (FTIR) of CO adsorbed at room temperature. The effect of the nanoparticle shape and surface structure on the catalytic performance in hydrodechlorination (HDCl) of trichloroethylene (TCE) was examined. The results show that nanoparticles with different surface orientations can be employed to affect selectivity, with polyhedral and multiply-twinned Pd exhibiting the best ethylene selectivity.

In situ formation of surface and bulk oxides in small palladium nanoparticles

Evolution of surface and bulk palladium oxides in supported palladium nanoparticles was followed in situ using X-ray absorption spectroscopy. The surface oxide was found to be easily reducible in hydrogen at room temperature, while removal of bulk oxide required heating in hydrogen above 100 °C. We also found that the co-presence of hydrogen and oxygen favours a stronger oxidation of palladium particles compared to pure oxygen.