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Abstract: Solar H2O2 produced by O2 reduction provides a green, efficient, and ecological alternative to the industrial anthraquinone process and H2/O2 direct-synthesis. We report efficient photocatalytic H2O2 production at a rate of 73.4 mM h–1 in the presence of a sacrificial donor on a structurally engineered catalyst, alkali metal-halide modulated poly(heptazine imide) (MX → PHI). The reported H2O2 production is nearly 150 and >4250 times higher than triazine structured pristine carbon nitride under UV–visible and visible light (≥400 nm) irradiation, respectively. Furthermore, the solar H2O2 production rate on MX → PHI is higher than most of the previously reported carbon nitride (triazine, tri-s-triazine), metal oxides, metal sulfides, and other metal–organic photocatalysts. A record high AQY of 96% at 365 nm and 21% at 450 nm was observed. We find that structural modulation by alkali metal-halides results in a highly photoactive MX → PHI catalyst which has a broader light absorption range, enhanced light absorption ability, tailored bandgap, and a tunable band edge position. Moreover, this material has a different polymeric structure, high O2 trapping ability, interlayer intercalation, as well as surface decoration of alkali metals. The specific C≡N groups and surface defects, generated by intercalated MX, were also considered as potential contributors to the separation of photoinduced electron–hole pairs, leading to enhanced photocatalytic activity. A synergy of all these factors contributes to a higher H2O2 production rate. Spectroscopic data help us to rationalize the exceptional photochemical performance and structural characteristics of MX → PHI.

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Abstract: Understanding the nanoscopic chemical and structural changes that drive instabilities in emerging energy materials is essential for mitigating device degradation. The power conversion efficiency of halide perovskite photovoltaic devices has reached 25.7% in single junction and 29.8% in tandem perovskite/silicon cells1,2, yet retaining such performance under continuous operation has remained elusive3. Here, we develop a multimodal microscopy toolkit to reveal that in leading formamidinium-rich perovskite absorbers, nanoscale phase impurities including hexagonal polytype and lead iodide inclusions are not only traps for photo-excited carriers which themselves reduce performance4,5, but via the same trapping process are sites at which photochemical degradation of the absorber layer is seeded. We visualise illumination-induced structural changes at phase impurities associated with trap clusters, revealing that even trace amounts of these phases, otherwise undetected with bulk measurements, compromise device longevity. The type and distribution of these unwanted phase inclusions depends on film composition and processing, with the presence of polytypes being most detrimental for film photo-stability. Importantly, we reveal that performance losses and intrinsic degradation processes can both be mitigated by modulating these defective phase impurities, and demonstrate that this requires careful tuning of local structural and chemical properties. This multimodal workflow to correlate the nanoscopic landscape of beam sensitive energy materials will be applicable to a wide range of semiconductors for which a local picture of performance and operational stability has yet to be established.

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Abstract: The atomic arrangement of the terminating facets on spinel Co3O4 nanocrystals is strongly linked to its catalytic performance. However, the spinel crystal structure offers multiple possible surface terminations depending on the synthesis. Thus, understanding the terminating surface atomic structure is essential in developing high-performance Co3O4 nanocrystals. In this work, we present direct atomic-scale observation of the surface terminations of Co3O4 nanoparticles supported on hollow carbon spheres (HCSs) using exit wavefunction reconstruction from aberration-corrected transmission electron microscopy focal-series. The restored high-resolution phases show distinct resolved oxygen and cobalt atomic columns. The data show that the structure of {100}, {110}, and {111} facets of spinel Co3O4 exhibit characteristic active sites for carbon monoxide (CO) adsorption, in agreement with density functional theory calculations. Of these facets, the {100} and {110} surface terminations are better suited for CO adsorption than the {111}. However, the presence of oxygen on the {111} surface termination indicates this facet also plays an essential role in CO adsorption. Our results demonstrate direct evidence of the surface termination atomic structure beyond the assumed stoichiometry of the surface.

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Abstract: Single-atom catalytic sites may have existed in all supported transition metal catalysts since their first application. Yet, interest in the design of single-atom heterogeneous catalysts (SACs) only really grew when advances in transmission electron microscopy (TEM) permitted direct confirmation of metal site isolation. While atomic-resolution imaging remains a central characterization tool, poor statistical significance, reproducibility, and interoperability limit its scope for deriving robust characteristics about these frontier catalytic materials. Here, we introduce a customized deep-learning method for automated atom detection in image analysis, a rate-limiting step toward high-throughput TEM. Platinum atoms stabilized on a functionalized carbon support with a challenging irregular three-dimensional morphology serve as a practically relevant test system with promising scope in thermo- and electrochemical applications. The model detects over 20,000 atomic positions for the statistical analysis of important properties for establishing structure–performance relations over nanostructured catalysts, like the surface density, proximity, clustering extent, and dispersion uniformity of supported metal species. Good performance obtained on direct application of the model to an iron SAC based on carbon nitride demonstrates its generalizability for single-atom detection on carbon-related materials. The approach establishes a route to integrate artificial intelligence into routine TEM workflows. It accelerates image processing times by orders of magnitude and reduces human bias by providing an uncertainty analysis that is not readily quantifiable in manual atom identification, improving standardization and scalability.

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Abstract: Electrocatalytic organic compound oxidation reactions (OCORs) have been intensively studied for energy and environmentally benign applications. However, relatively little effort has been devoted to developing a fundamental understanding of OCOR, including the detailed competition with side reactions and activity limitations, thus inhibiting the rational design of high-performance electrocatalysts. Herein, by taking NiWO4-catalysed urea oxidation reaction (UOR) in aqueous media as an example, the competition between the OCOR and the oxygen evolution reaction (OER) within a wide potential range is examined. It is shown that the root of the competition can be ascribed to insufficient surface concentration of dynamic Ni3+, an active site shared by both UOR and OER. Similar phenomenon are observed in other OCOR electrocatalysts and systems. To address the issue, a “controllable reconstruction of pseudo-crystalline bimetal oxides” design strategy is proposed to maximise the dynamic Ni3+ population and manipulate the competition between UOR and OER. The optimised electrocatalyst delivers best-in-class performance and a ~10-fold increase in current density at 1.6 V versus the reversible hydrogen electrode for alkaline urea electrolysis compared to that of the pristine materials.