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High-entropy alloys have received considerable attention in the field of catalysis due to their exceptional properties. However, few studies hitherto focus on the origin of their outstanding performance and the accurate identification of active centers. Herein, we report a conceptual and experimental approach to overcome the limitations of single-element catalysts by designing a FeCoNiXRu (X: Cu, Cr, and Mn) High-entropy alloys system with various active sites that have different adsorption capacities for multiple intermediates. The electronegativity differences between mixed elements in HEA induce significant charge redistribution and create highly active Co and Ru sites with optimized energy barriers for simultaneously stabilizing OH * and H * intermediates, which greatly enhances the efficiency of water dissociation in alkaline conditions. This work provides an in-depth understanding of the interactions between specific active sites and intermediates, which opens up a fascinating direction for breaking scaling relation issues for multistep reactions. High-entropy alloy catalysts are an emerging class of materials and identification of catalytically active sites is critical. Here, we provide evidence that metal site electronegativity differences stabilize bound *OH and *H intermediates.

Single-atom Fe-N-C catalysts has attracted widespread attentions in the oxygen reduction reaction (ORR). However, the origin of ORR activity on Fe-N-C catalysts is still unclear, which hinder the further improvement of Fe-N-C catalysts. Herein, we provide a model to understand the ORR activity of Fe-N 4 site from the spatial structure and energy level of the frontier orbitals by density functional theory calculations. Taking the regulation of divacancy defects on Fe-N 4 site ORR activity as examples, we demonstrate that the hybridization between Fe 3 dz 2 , 3 dyz (3 dxz ) and O 2 π* orbitals is the origin of Fe-N 4 ORR activity. We found that the Fe–O bond length, the d-band center gap of spin states, the magnetic moment of Fe site and *O 2 as descriptors can accurately predict the ORR activity of Fe-N 4 site. Furthermore, these descriptors and ORR activity of Fe-N 4 site are mainly distributed in two regions with obvious difference, which greatly relate to the height of Fe 3 d projected orbital in the Z direction. This work provides a new insight into the ORR activity of single-atom M-N-C catalysts. It is of high importance to understand the origin of single-atom Fe-N 4 activity in oxygen reduction reaction. Here, the authors provide a model to understand the catalytic activity of Fe-N 4 site from the spatial structure and energy level of the frontier orbitals by density functional theory calculations.

Aqueous zinc batteries are appealing devices for cost-effective and environmentally sustainable energy storage. However, the zinc metal deposition at the anode strongly influences the battery cycle life and performance. To circumvent this issue, here we propose the use of lanthanum nitrate (La(NO 3 ) 3 ) as supporting salt for aqueous zinc sulfate (ZnSO 4 ) electrolyte solutions. Via physicochemical and electrochemical characterizations, we demonstrate that this peculiar electrolyte formulation weakens the electric double layer repulsive force, thus, favouring dense metallic zinc deposits and regulating the charge distribution at the zinc metal|electrolyte interface. When tested in Zn||VS 2 full coin cell configuration (with cathode mass loading of 16 mg cm −2 ), the electrolyte solution containing the lanthanum ions enables almost 1000 cycles at 1 A g −1 (after 5 activation cycles at 0.05 A g −1 ) with a stable discharge capacity of about 90 mAh g −1 and an average cell discharge voltage of ∼0.54 V. Zinc metal is a promising anode material for aqueous secondary batteries. However, the unfavourable morphologies formed on the electrode surface during cycling limit its application. Here, the authors report the tailoring of the surface morphology using a lanthanum nitrate aqueous electrolyte additive.

The hydrogen oxidation/evolution reactions are two of the most fundamental reactions in distributed renewable electrochemical energy conversion and storage systems. The identification of the reaction descriptor is therefore of critical importance for the rational catalyst design and development. Here we report the correlation between hydrogen oxidation/evolution activity and experimentally measured hydrogen binding energy for polycrystalline platinum examined in several buffer solutions in a wide range of electrolyte pH from 0 to 13. The hydrogen oxidation/evolution activity obtained using the rotating disk electrode method is found to decrease with the pH, while the hydrogen binding energy, obtained from cyclic voltammograms, linearly increases with the pH. Correlating the hydrogen oxidation/evolution activity to the hydrogen binding energy renders a monotonic decreasing hydrogen oxidation/evolution activity with the hydrogen binding energy, strongly supporting the hypothesis that hydrogen binding energy is the sole reaction descriptor for the hydrogen oxidation/evolution activity on monometallic platinum. Hydrogen oxidation and evolution are two of the key reactions in renewable energy conversion and storage devices. Here, the authors report the correlation between reaction rate and measured hydrogen binding energy for polycrystalline platinum in buffer solutions ranging from pH 0 to 13.

The rational design of molecules with desired properties is a long-standing challenge in chemistry. Generative neural networks have emerged as a powerful approach to sample novel molecules from a learned distribution. Here, we propose a conditional generative neural network for 3d molecular structures with specified chemical and structural properties. This approach is agnostic to chemical bonding and enables targeted sampling of novel molecules from conditional distributions, even in domains where reference calculations are sparse. We demonstrate the utility of our method for inverse design by generating molecules with specified motifs or composition, discovering particularly stable molecules, and jointly targeting multiple electronic properties beyond the training regime. The targeted discovery of molecules with specific structural and chemical properties is an open challenge in computational chemistry. Here, the authors propose a conditional generative neural network for the inverse design of 3d molecular structures.

Carbon materials doped with transition metal and nitrogen are highly active, non-precious metal catalysts for the electrochemical conversion of molecular oxygen in fuel cells, metal air batteries, and electrolytic processes. However, accurate measurement of their intrinsic turn-over frequency and active-site density based on metal centres in bulk and surface has remained difficult to date, which has hampered a more rational catalyst design. Here we report a successful quantification of bulk and surface-based active-site density and associated turn-over frequency values of mono- and bimetallic Fe/N-doped carbons using a combination of chemisorption, desorption and 57 Fe Mössbauer spectroscopy techniques. Our general approach yields an experimental descriptor for the intrinsic activity and the active-site utilization, aiding in the catalyst development process and enabling a previously unachieved level of understanding of reactivity trends owing to a deconvolution of site density and intrinsic activity. Iron and nitrogen doped carbon materials are widely studied electrocatalysts, however measurement of features such as intrinsic turn-over frequency and active site utilization has proved difficult. Here, the authors use a combination of chemisorption and spectroscopy techniques to determine these properties.

Discontinuous fibre composites represent a class of materials that are strong, lightweight and have remarkable fracture toughness. These advantages partially explain the abundance and variety of discontinuous fibre composites that have evolved in the natural world. Many natural structures out-perform the conventional synthetic counterparts due, in part, to the more elaborate reinforcement architectures that occur in natural composites. Here we present an additive manufacturing approach that combines real-time colloidal assembly with existing additive manufacturing technologies to create highly programmable discontinuous fibre composites. This technology, termed as ‘3D magnetic printing’, has enabled us to recreate complex bioinspired reinforcement architectures that deliver enhanced material performance compared with monolithic structures. Further, we demonstrate that we can now design and evolve elaborate reinforcement architectures that are not found in nature, demonstrating a high level of possible customization in discontinuous fibre composites with arbitrary geometries. Superior mechanical properties in natural composites are frequently achieved by the inclusion of locally orientated reinforcing particles. Here, the authors implement this design strategy synthetically by employing a 3D magnetic printing protocol to create programmable composite architectures.

Single-atom catalysts maximize the utilization of supported precious metals by exposing every single metal atom to reactants. To avoid sintering and deactivation at realistic reaction conditions, single metal atoms are stabilized by specific adsorption sites on catalyst substrates. Here we show by combining photoelectron spectroscopy, scanning tunnelling microscopy and density functional theory calculations that Pt single atoms on ceria are stabilized by the most ubiquitous defects on solid surfaces—monoatomic step edges. Pt segregation at steps leads to stable dispersions of single Pt 2+ ions in planar PtO 4 moieties incorporating excess O atoms and contributing to oxygen storage capacity of ceria. We experimentally control the step density on our samples, to maximize the coverage of monodispersed Pt 2+ and demonstrate that step engineering and step decoration represent effective strategies for understanding and design of new single-atom catalysts. Single metal atoms promise high catalytic performances, but their implementation in future systems depends on an understanding of how their underlying support medium can offer stabilization. Here, the authors investigate Pt 2+ on ceria to elucidate this important fundamental consideration.

Sodium-ion batteries are a potentially low-cost and safe alternative to the prevailing lithium-ion battery technology. However, it is a great challenge to achieve fast charging and high power density for most sodium-ion electrodes because of the sluggish sodiation kinetics. Here we demonstrate a high-capacity and high-rate sodium-ion anode based on ultrathin layered tin(II) sulfide nanostructures, in which a maximized extrinsic pseudocapacitance contribution is identified and verified by kinetics analysis. The graphene foam supported tin(II) sulfide nanoarray anode delivers a high reversible capacity of ∼1,100 mAh g −1 at 30 mA g −1 and ∼420 mAh g −1 at 30 A g −1 , which even outperforms its lithium-ion storage performance. The surface-dominated redox reaction rendered by our tailored ultrathin tin(II) sulfide nanostructures may also work in other layered materials for high-performance sodium-ion storage. Sodium ion batteries are a promising alternative to lithium ion technology, however their sluggish sodiation kinetics currently hinder performance. Here the authors fabricate ultrathin layered tin(II) sulfide nanostructures displaying a pseudocapacitance contribution for high capacity sodium ion anodes.

Recent experiments suggest that ground state chemical reactivity can be modified when placing molecular systems inside infrared cavities where molecular vibrations are strongly coupled to electromagnetic radiation. This phenomenon lacks a firm theoretical explanation. Here, we employ an exact quantum dynamics approach to investigate a model of cavity-modified chemical reactions in the condensed phase. The model contains the coupling of the reaction coordinate to a generic solvent, cavity coupling to either the reaction coordinate or a non-reactive mode, and the coupling of the cavity to lossy modes. Thus, many of the most important features needed for realistic modeling of the cavity modification of chemical reactions are included. We find that when a molecule is coupled to an optical cavity it is essential to treat the problem quantum mechanically to obtain a quantitative account of alterations to reactivity. We find sizable and sharp changes in the rate constant that are associated with quantum mechanical state splittings and resonances. The features that emerge from our simulations are closer to those observed in experiments than are previous calculations, even for realistically small values of coupling and cavity loss. This work highlights the importance of a fully quantum treatment of vibrational polariton chemistry. Experiments suggest that placing molecules in an infrared cavity alters their reactivity, an effect lacking a clear theoretical explanation. Here, the authors show that the key to understanding this process may lie in quantum light-matter interactions.