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A catalyst-coated diaphragm assembly to improve the performance and energy efficiency of alkaline water electrolysers

Alkaline water electrolysers are ideal for gigawatt-scale hydrogen production due to the usage of non-precious metal and low-cost raw materials. However, their performances are modest with the separated electrode and diaphragm structure which can date back to more than 100 years ago. Here we report a catalyst-coated diaphragm assembly to improve the performance of alkaline water electrolysers. The transport resistance of OH ions is reduced and the electrochemical surface area of catalysts is enlarged by more than forty fold, representing more than 40% increase in hydrogen production rate or as much as 16% reduction in energy consumption. The electrolyser with our catalyst-coated diaphragm assembly delivers current densities as high as 1 A cm−2 at 1.8 V or 2 A cm−2 at 2 V and shows good stability after more than 1000 hours of operation. Therefore, the catalyst-coated diaphragm assembly route is promising for the development of high-performance and efficient alkaline water electrolysers.

Modeling the impact of structure and coverage on the reactivity of realistic heterogeneous catalysts

Adsorbates often cover the surfaces of catalysts densely as they carry out reactions, dynamically altering their structure and reactivity. Understanding adsorbate-induced phenomena and harnessing them in our broader quest for improved catalysts is a substantial challenge that is only beginning to be addressed. Here we chart a path toward a deeper understanding of such phenomena by focusing on emerging in silico modeling methodologies, which will increasingly incorporate machine learning techniques. We first examine how adsorption on catalyst surfaces can lead to local and even global structural changes spanning entire nanoparticles, and how this affects their reactivity. We then evaluate current efforts and the remaining challenges in developing robust and predictive simulations for modeling such behavior. Last, we provide our perspectives in four critical areas—integration of artificial intelligence, building robust catalysis informatics infrastructure, synergism with experimental characterization, and adaptive modeling frameworks—that we believe can help surmount the remaining challenges in rationally designing catalysts in light of these complex phenomena.

Perovskite-driven solar C2 hydrocarbon synthesis from CO2

Photoelectrochemistry (PEC) presents a direct pathway to solar fuel synthesis by integrating light absorption and catalysis into compact electrodes. Yet, PEC hydrocarbon production remains elusive due to high catalytic overpotentials and insufficient semiconductor photovoltage. Here we demonstrate ethane and ethylene synthesis by interfacing lead halide perovskite photoabsorbers with suitable copper nanoflower electrocatalysts. The resulting perovskite photocathodes attain a 9.8% Faradaic yield towards C2 hydrocarbon production at 0 V against the reversible hydrogen electrode. The catalyst and perovskite geometric surface areas strongly influence C2 photocathode selectivity, which indicates a role of local current density in product distribution. The thermodynamic limitations of water oxidation are overcome by coupling the photocathodes to Si nanowire photoanodes for glycerol oxidation. These unassisted perovskite–silicon PEC devices attain partial C2 hydrocarbon photocurrent densities of 155 µA cm−2, 200-fold higher than conventional perovskite–BiVO4 artificial leaves for water and CO2 splitting. These insights establish perovskite semiconductors as a versatile platform towards PEC multicarbon synthesis.

Binary peptide coacervates as an active model for biomolecular condensates

Biomolecular condensates formed by proteins and nucleic acids are critical for cellular processes. Macromolecule-based coacervate droplets formed by liquid-liquid phase separation serve as synthetic analogues, but are limited by complex compositions and high molecular weights. Recently, short peptides have emerged as an alternative component of coacervates, but tend to form metastable microdroplets that evolve into rigid nanostructures. Here we present programmable coacervates using binary mixtures of diphenylalanine-based short peptides. We show that the presence of different short peptides stabilizes the coacervate phase and prevents the formation of rigid structures, allowing peptide coacervates to be used as stable adaptive compartments. This approach allows fine control of droplet formation and dynamic morphological changes in response to physiological triggers. As compartments, short peptide coacervates sequester hydrophobic molecules and enhance bio-orthogonal catalysis. In addition, the incorporation of coacervates into model synthetic cells enables the design of Boolean logic gates. Our findings highlight the potential of short peptide coacervates for creating adaptive biomimetic systems and provide insight into the principles of phase separation in biomolecular condensates.

Anion vacancies activate N2 to ammonia on Ba–Si orthosilicate oxynitride-hydride

Anion vacancies on metal oxide surfaces have been studied as either active sites or promoting sites in various chemical reactions involving oxidation/reduction processes. However, oxide materials rarely work effectively as catalysts in the absence of transition metal sites. Here we report a Ba–Si orthosilicate oxynitride–hydride as a transition-metal-free catalyst for efficient ammonia synthesis via an anion-vacancymediated mechanism. The facile desorption of H and N3− anions plus the flexibility of the crystal structure can accommodate a high density of electrons at vacancy sites, where N2 can be captured and directly activated to ammonia through hydrogenation processes. The ammonia synthesis rates reach 40.1 mmol g−1 h−1 at 300 °C by loading ruthenium nanoparticles. Although not found to dissociate N2, Ru instead facilitates the formation of anion vacancies at the Ru–support interface. This demonstrates a new route for anion-vacancymediated heterogeneous catalysis.

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