The Journal of Physical Chemistry C最新文献

We have studied catalytic ammonia oxidation with NO and O₂ on a VO_x/Rh(111) catalyst at θ_V < 0.5 monolayer equivalents (MLE) with photoemission electron microscopy (PEEM) at 10^–4 mbar and with spectroscopic photoemission and low-energy electron microscopy (SPELEEM) in the 10^–6 mbar range. With O₂ as oxidant, VO_x condenses into islands of macroscopic size, i.e., of diameters ranging from tens to several hundreds of microns. With NO a hole pattern in the VO_x layer develops under reaction conditions. In the NH₃ + O₂ reaction microspot-LEED (μLEED) identifies a (√3 × √3)-moiré pattern inside the VO_x islands and on the surrounding metal surface. In NH₃ oxidation with NO reaction microspot X-ray photoelectron spectroscopy (μXPS) shows the presence of nitrogen species on the bare metal surface, as well as on the VO_x layer. With NO as reactant, the interface region between the VO_x covered and bare metal surface areas is strongly broadened with about 100 μm width as compared to ≈30 μm width with O₂ as oxidant. Our data suggest that in ammonia oxidation over VO_x/Rh(111), oxidation with NO is less effective than oxidation with O₂.

In this work, the structural stability, electronic properties, and photocatalytic performance of three heterostructures─nonpolar/nonpolar GaN/ZrS₂ and nonpolar/polar GaN/ZrSO with different polarization directions (P↑ and P↓)─were systematically investigated using first-principles calculations. The GaN/ZrS₂ heterostructure was found to form a direct Z-scheme junction, with efficient charge separation driven by a built-in electric field. This internal field enhances the redox potential, making the GaN/ZrS₂ heterostructure highly suitable for overall photocatalytic water splitting. In contrast, the P↓ GaN/ZrSO heterostructure was shown to exhibit type II band alignment, where the presence of an intrinsic polarization field from the ZrSO monolayer further boosts its hydrogen evolution efficiency. Both GaN/ZrS₂ and P↓ GaN/ZrSO heterostructures demonstrated strong light absorption in the visible spectrum and favorable band-edge positions for redox reactions. Thermodynamic calculations of Gibbs free energy confirmed that spontaneous water splitting can occur under neutral conditions for both systems. Additionally, dielectric function analysis revealed enhanced visible light absorption, especially in the P↓ GaN/ZrSO system. These results indicate that GaN-based heterostructures offer significant potential as efficient and stable photocatalysts for water splitting, with the ability to harness visible light and optimize charge carrier dynamics through polarization effects. This study highlights the promise of these heterostructures for advancing sustainable energy applications.

Microkinetic models (MKMs) are widely used within the computational heterogeneous catalysis community to investigate complex reaction mechanisms, to rationalize experimental trends, and to accelerate the rational design of novel catalysts. However, constructing these models requires computationally expensive and manually tedious density functional theory (DFT) calculations for identifying transition states for each elementary reaction within the MKM. To address these challenges, we demonstrate a novel protocol that uses the open-source kinetics workflow tool Pynta to automate the iterative training of a reactive machine learning potential (rMLP). Specifically, using the silver-catalyzed partial oxidation of methanol as a prototypical example, we first demonstrate our workflow by training an rMLP to accelerate the parallel calculation of DFT-quality transition states for all 53 reactions, achieving a 7× speedup compared to a DFT-only strategy. Detailed analysis of our training curriculum reveals the shortcomings of using an adaptive sampling scheme with a single rMLP model to describe all reactions within the MKM simultaneously. We show that these limitations can be overcome using a balanced “reaction class” approach that uses multiple rMLP models, each describing a single class of similar transition states. Finally, we demonstrate that our Pynta-based workflow is also compatible with large pretrained foundational models. For example, by fine-tuning a top-performing graph neural network potential trained on the OC20 dataset, we observe an impressive 20× speedup with an 89% success rate in identifying transition states. This work highlights the synergistic potential of integrating automated tools with machine learning to advance catalysis research.

Structural distortions play a decisive role in the stability and performance of organic–inorganic mixed halide perovskites. Therefore, understanding the role of inevitably present intrinsic defects in the structural distortions is essential for the defect engineering of halide perovskites. In this study, we present an in-depth analysis of the structural distortions induced by the presence of five intrinsic defects, namely, CH₃NH₃ (MA), Pb and I vacancies, Pb interstitial, and Pb_MA antisite in CH₃NH₃PbI₃. Quantitative analysis of the octahedral distortions and MA molecular rotation showed that the Pb vacancy causes a maximum change in the isometric octahedral volume (∼14%) as well as MA molecule rotation (∼70°), while the asymmetric octahedral twisting and bond angle deviations are negligible. On the other hand, asymmetric octahedral distortions are highest in the I-vacant structure, where an average variation of ∼8° in the I–Pb–I bond angle was reported, and the effective coordination number of Pb drops to ∼5.2. Classical force-field based calculations revealed that the halide ion migration barrier varies proportionally with the isometric octahedral volume change and the MA molecule rotation, while the effect of asymmetric octahedral distortions was observed to be negligible. The total activation energy of halide vacancy diffusion increases by 0.3–1.1 eV due to the presence of intrinsic defects, where binding of the iodide vacancies with the intrinsic defects plays a dominating role. Inhibiting ionic migration through the interplay of defects is an effective strategy to suppress phase transitions and enhance the stability of perovskite-based devices, enabling their application in LEDs, photodetectors, and solar cells.