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Water electrolysis offers a promising energy conversion and storage technology for mitigating the global energy and environmental crisis, but there still lack highly efficient and pH-universal electrocatalysts to boost the sluggish kinetics for both cathodic hydrogen evolution reaction (HER) and anodic oxygen evolution reaction (OER). Herein, we report uniformly dispersed iridium nanoclusters embedded on nitrogen and sulfur co-doped graphene as an efficient and robust electrocatalyst for both HER and OER at all pH conditions, reaching a current density of 10 mA cm −2 with only 300, 190 and 220 mV overpotential for overall water splitting in neutral, acidic and alkaline electrolyte, respectively. Based on probing experiments, operando X-ray absorption spectroscopy and theoretical calculations, we attribute the high catalytic activities to the optimum bindings to hydrogen (for HER) and oxygenated intermediate species (for OER) derived from the tunable and favorable electronic state of the iridium sites coordinated with both nitrogen and sulfur. Water electrolysis offers a promising energy conversion technology, although there is still a need to understand the catalysis on the atomic-level. Here, the authors report Ir nanoclusters coordinated with both N and S as an efficient and pH-universal electrocatalyst for overall water splitting.

This paper constructs a theoretical framework integrating health risk transmission, remote work constraints, and spatial equilibrium to analyze the impact mechanisms of major public health events on the real estate market. This study finds that pandemics affect market equilibrium through multiple channels, including changes in residents’ utility functions, the reshaping of labor market structures, and adjustments in location choices. The model combines the SIR model from epidemiology with spatial economics to depict the endogenous decision mechanism of health risks. By constructing a two-sector general equilibrium model that includes remote work sectors, this study reveals the impact of technological change on the spatial structure of the real estate market. Based on the mobility preference theory, an asset pricing framework incorporating health risk premiums is established. Comparative static analysis shows that the health risk transmission coefficient influences housing prices through two channels: directly lowering willingness to pay and indirectly affecting the distribution of population density. Dynamic analysis indicates that, under specific parameter conditions, the market exhibits asymptotic stability. Policy simulation results show that the transmission effects of monetary and fiscal policies exhibit significant spatial heterogeneity, requiring policymakers to pay more attention to regional differences. This study not only enriches the analytical tools of real estate economics but also provides theoretical support for relevant policy formulation.

The ability to precisely engineer the doping of sub-nanometer bimetallic clusters offers exciting opportunities for tailoring their catalytic performance with atomic accuracy. However, the fabrication of singly dispersed bimetallic cluster catalysts with atomic-level control of dopants has been a long-standing challenge. Herein, we report a strategy for the controllable synthesis of a precisely doped single cluster catalyst consisting of partially ligand-enveloped Au 4 Pt 2 clusters supported on defective graphene. This creates a bimetal single cluster catalyst (Au 4 Pt 2 /G) with exceptional activity for electrochemical nitrogen (N 2 ) reduction. Our mechanistic study reveals that each N 2 molecule is activated in the confined region between cluster and graphene. The heteroatom dopant plays an indispensable role in the activation of N 2 via an enhanced back donation of electrons to the N 2 LUMO. Moreover, besides the heteroatom Pt, the catalytic performance of single cluster catalyst can be further tuned by using Pd in place of Pt as the dopant. The fabrication of singly dispersed metal cluster catalysts with atomic-level control of dopants is a long-standing challenge. Here, the authors report a strategy for the synthesis of a precisely doped single cluster catalyst which shows exceptional activity for electrochemical dinitrogen reduction.

Single-atom catalysts (SACs) have been applied in many fields due to their superior catalytic performance. Because of the unique properties of the single-atom-site, using the single atoms as catalysts to synthesize SACs is promising. In this work, we have successfully achieved Co 1 SAC using Pt 1 atoms as catalysts. More importantly, this synthesis strategy can be extended to achieve Fe and Ni SACs as well. X-ray absorption spectroscopy (XAS) results demonstrate that the achieved Fe, Co, and Ni SACs are in a M 1 -pyrrolic N 4 (M= Fe, Co, and Ni) structure. Density functional theory (DFT) studies show that the Co(Cp) 2 dissociation is enhanced by Pt 1 atoms, thus leading to the formation of Co 1 atoms instead of nanoparticles. These SACs are also evaluated under hydrogen evolution reaction (HER) and oxygen evolution reaction (OER), and the nature of active sites under HER are unveiled by the operando XAS studies. These new findings extend the application fields of SACs to catalytic fabrication methodology, which is promising for the rational design of advanced SACs. Synthesizing single-atom catalysts through a general method presents a great challenge. Here the authors report that Fe, Co and Ni single-atom catalysts can be obtained using pre-located isolated Pt atoms as the catalyst and identify the role of Pt single atoms in the synthesis process.

The study of dynamics on artificial neurons and neuronal networks is of great significance to understand brain functions and develop neuromorphic systems. Recently, memristive neuron and neural network models offer great potential in the investigation of neurodynamics. Many chaotic dynamics including chaos, transient chaos, hyperchaos, coexisting attractors, multistability, and extreme multistability have been researched based on the memristive neurons and neural networks. In this review, we firstly introduce the basic definition of chaotic dynamics and review several traditional artificial neuron and neural network models. Then we categorize memristive neuron and neural network models with different biological function mechanisms into five types: memristive autapse neuron, memristive synapse-coupled bi-neuron network, memristive synaptic weight neural network, neuron under electromagnetic radiation, and neural network under electromagnetic radiation. The modeling mechanisms of each type are explained and described in detail. Furthermore, the pioneer works and some recent important papers related to those types are introduced. Finally, some open problems in this field are presented to further explore future work.

The SARS-CoV-2 Omicron variant exhibits striking immune evasion and is spreading rapidly worldwide. Understanding the structural basis of the high transmissibility and enhanced immune evasion of Omicron is of high importance. Here, using cryo-electron microscopy, we present both the closed and the open states of the Omicron spike (S) protein, which appear more compact than the counterparts of the G614 strain 1 , potentially related to enhanced inter-protomer and S1–S2 interactions induced by Omicron residue substitution. The closed state showing dominant population may indicate a conformational masking mechanism for the immune evasion of Omicron. Moreover, we captured three states for the Omicron S–ACE2 complex, revealing that the substitutions on the Omicron RBM result in new salt bridges and hydrogen bonds, more favourable electrostatic surface properties, and an overall strengthened S–ACE2 interaction, in line with the observed higher ACE2 affinity of Omicron S than of G614. Furthermore, we determined the structures of Omicron S in complex with the Fab of S3H3, an antibody that is able to cross-neutralize major variants of concern including Omicron, elucidating the structural basis for S3H3-mediated broad-spectrum neutralization. Our findings shed light on the receptor engagement and antibody neutralization or evasion of Omicron and may also inform the design of broadly effective vaccines against SARS-CoV-2. The structures of the open and closed states of the Omicron spike protein and its complex with the ACE2 receptor or a broadly neutralizing antibody are resolved and shed light on the receptor engagement and antibody neutralization of Omicron.

Metal–dielectric Janus colloids subjected to perpendicular a.c. electric fields can self-organize into swarms, chains, clusters and isotropic gases, depending on the frequency of the field. Active materials represent a new class of condensed matter in which motile elements may collectively form dynamic, global structures out of equilibrium 1 , 2 , 3 . Here, we present a general strategy to reconfigure active particles into various collective states by introducing imbalanced interactions. We demonstrate the concept with computer simulations of self-propelled colloidal spheres, and experimentally validate it in a two-dimensional (2D) system of metal–dielectric Janus colloids subjected to perpendicular a.c. electric fields. The mismatched, frequency-dependent dielectric responses of the two hemispheres of the colloids allow simultaneous control of particle motility and colloidal interactions. We realized swarms, chains, clusters and isotropic gases from the same precursor particle by changing the electric-field frequency. Large-scale polar waves, vortices and jammed domains are also observed, with the persistent time-dependent evolution of their collective structure evoking that of classical materials. This strategy of asymmetry-driven active self-organization should generalize rationally to other active 2D and three-dimensional (3D) materials.

High-efficiency water electrolysis is the key to sustainable energy. Here we report a highly active and durable RuIrO x ( x  ≥ 0) nano-netcage catalyst formed during electrochemical testing by in-situ etching to remove amphoteric ZnO from RuIrZnO x hollow nanobox. The dispersing-etching-holing strategy endowed the porous nano-netcage with a high exposure of active sites as well as a three-dimensional accessibility for substrate molecules, thereby drastically boosting the electrochemical surface area (ECSA). The nano-netcage catalyst achieved not only ultralow overpotentials at 10 mA cm −2 for hydrogen evolution reaction (HER; 12 mV, pH = 0; 13 mV, pH = 14), but also high-performance overall water electrolysis over a broad pH range (0 ~ 14), with a potential of mere 1.45 V (pH = 0) or 1.47 V (pH = 14) at 10 mA cm −2 . With this universal applicability of our electrocatalyst, a variety of readily available electrolytes (even including waste water and sea water) could potentially be directly used for hydrogen production. Water electrolysis is considered a key reaction for future sustainable fuel generation. Here, authors report a three-dimensional RuIrOx nano-netcage catalyst that shows high activities and efficiencies for pH-universal overall water splitting.

Amides are one of the most important organic compounds that are widely applied in medicine, biochemistry, and materials science. To find an efficient synthetic method of amides is a challenge for organic chemistry. We report here a facile synthesis method of primary and secondary amides through a direct amidation of esters with sodium amidoboranes (NaNHRBH 3 , R = H, Me), at room temperature without using catalysts and other reagents. This process is rapid and chemoselective, and features quantitative conversion and wide applicability for esters tolerating different functional groups. The experimental and theoretical studies reveal a reaction mechanism with nucleophilic addition followed by a swift proton transfer-induced elimination reaction. Amides are important organic compounds that are widely applied in medicine, biochemistry, and materials science. Here, the authors report a method for synthesis of primary and secondary amides through a direct amidation of esters with sodium amidoboranes (NaNHRBH 3 , R = H, Me), at room temperature without the use of catalysts.

Supported noble metal nanoparticles (including nanoclusters) are widely used in many industrial catalytic processes. While the finely dispersed nanostructures are highly active, they are usually thermodynamically unstable and tend to aggregate or sinter at elevated temperatures. This scenario is particularly true for supported nanogold catalysts because the gold nanostructures are easily sintered at high temperatures, under reaction conditions, or even during storage at ambient temperature. Here, we demonstrate that isolated Au single atoms dispersed on iron oxide nanocrystallites (Au 1 /FeO x ) are much more sinteringresistant than Au nanostructures, and exhibit extremely high reaction stability for CO oxidation in a wide temperature range. Theoretical studies revealed that the positively charged and surface-anchored Au1 atoms with high valent states formed significant covalent metal-support interactions (CMSIs), thus providing the ultra-stability and remarkable catalytic performance. This work may provide insights and a new avenue for fabricating supported Au catalysts with ultra-high stability.