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The electrochemical N2 reduction reaction (ENRR), driven by renewable electricity and run under ambient conditions, offers a promising sustainable avenue for carbon‐neutral NH3 production. Yet, to efficiently bind and activate the inert N2 remains challenge. Herein, effective and stable electrochemical NH3 synthesis on Sm(OH)3 via enhanced adsorption of hydrogen and dinitrogen by dual integration of sulfur dopants and oxygen vacancies (VO) is reported. The resulting S‐doped lanthanide electrocatalyst attains both a good NH3 yield rate, exceeding 21 μgNH3 h−1 mgcat.−1, and an NH3 faradaic efficiency of over 29% at −0.3 V (vs reversible hydrogen electrode) in an H‐type cell using a neutral electrolyte, figures of merit that are largely maintained after 2 days of consecutive polarization. Density functional theory calculations show that the adsorption energy barrier of N2 on S‐Sm(OH)3(VO) is greatly lowered by the introduction of VO. In addition, the S sites improve the adsorption of hydrogen produced via the Volmer reaction, which is conducive to the formation of the *N–NH intermediate (i.e., the potential determining step, PDS) on adjacent Sm sites, and thereby significantly promotes the reaction kinetics of ENRR. The PDS free energy for the catalyst is comparable with the values at the peak of the ENRR volcano plots of leading transition metal catalyst surfaces. [ABSTRACT FROM AUTHOR]

Hyperspectral imaging technology produces images that capture both spatial and spectral details of features, constituting a key data source in remote sensing detection. However, the accuracy of classifying hyperspectral remote sensing images is influenced by factors such as extensive data volume, high redundancy, and numerous spectral bands exhibiting significant correlation. To address these challenges, we introduce a two-layer with dual-branch 3D/2D-Attention cascade network model named DBANet. Firstly, the model employs principal component analysis to extract the raw data's primary features to reduce the data's complexity. Subsequently, the data undergoes two layers of 3D convolution and 2D convolution combined with a cascade structure of attention mechanism to fully extract the data's spatial, spectral, and textural feature information. Finally, the classification of input images is computed using a fully connected layer combined with the LogSoftmax function. Our DBANet demonstrates notable advantages in feature extraction and classification performance compared to other methods, as evidenced by the comprehensive qualitative and quantitative results of three public hyperspectral remote sensing datasets. It exhibits superior performance in the classification of hyperspectral remote-sensing images. [ABSTRACT FROM AUTHOR]

Green solvent processing of perovskite light‐emitting diodes (PeLEDs) is a necessity for their future commercialization. However, the almost insoluble nature of perovskites in most green solvents strongly impedes the progress of green solvent‐processed PeLEDs. Here, a novel green solvent triethylene glycol (TEG) is used as the processing solvent for perovskites. TEG has better solubility for perovskite precursors than most reported green solvents. Moreover, it is found that the low vapor pressure of TEG solvent and stable precursor solution render a much wider time window for the so‐called antisolvent treatment than that of perovskite precursor solution in commonly dimethyl sulfoxide. High‐quality perovskite film can be readily synthesized with the antisolvent treatment at a time window of 70–100 s, and the resultant green PeLEDs demonstrate nearly identical light‐emitting efficiencies. Together with further interface modification, the optimized green PeLEDs processed with TEG exhibit an external quantum efficiency of 20.4% and a maximal luminance over 38000 cd m−2. It is the first successful attempt to fabricate high‐efficiency PeLEDs utilizing green solvent and is enlightening for the development of high‐performance PeLEDs prepared with eco‐friendly solvents. [ABSTRACT FROM AUTHOR]

Active particle systems, such as human crowds, are out of equilibrium posing a significant challenge in identifying a suitable equation of state. However, several previous observations suggest that a crowd's speed distribution may conform to a two-dimensional Maxwell–Boltzmann distribution under certain yet-to-be-determined conditions. Our research uncovers that the divergence between the fluctuation velocity magnitude's probability density function and its best 2D Maxwell–Boltzmann fit diminishes in a power-law fashion with decreasing collision time scale between individuals. These findings are robustly supported by both experimental data and simulations with diverse boundary conditions and force potentials. The equilibrium characteristics of crowds are interpreted through a canonical ensemble framework. Furthermore, we show that high pressure indicates equilibrium characteristics in human crowds. Remarkably, we reveal the ideal gas law for human crowds without resorting to any behavior assumption. We demonstrate the predictive capability of the ideal gas law on both observational and modeling data. Our research highlights a new pathway to explore and validate traditional thermodynamic quantities and laws in the setting of high-pressure human crowds, advancing our understanding of active matter systems. • Under high density, the human crowd will exhibit equilibrium characteristics. • A wide range of simulations and experiments robustly supports the equilibrium-like behavior. • We reveal the ideal gas law for human crowds without resorting to any behavior assumption. [ABSTRACT FROM AUTHOR]

Medium/high-entropy materials have attracted more and more attention in catalytic field in view of their unique properties, yet the related catalytic mechanisms remain ambiguous. Herein, we demonstrate a two-step method for the preparations of medium-entropy metal sulfides (MESs) nanoparticles through the sulfuration of metal-organic frameworks (MOFs) precursors. Compared with the MOF precursor, MES has better electrocatalytic performance in oxygen evolution and reduction reactions (OER/ORR). Electron energy loss spectroscopy (EELS) and X-ray photoelectron spectroscopy (XPS) characterization indicate that the sulfidation can lead metallic ions to possessing higher valence states. Furthermore, the regulation of electronic structure are further proved by density functional theory (DFT) calculations. Rechargeable zinc-air batteries assembled with the Fe 1.2 (CoNi) 1.8 S 6 MES nanoparticles catalyst superior performances outperforming the commercial catalyst (Pt/C+RuO 2). The reported two-step method of fabrication strategy for preparing medium-entropy metal sulfides may further contribute to fundamental research into and industrial applications of medium-entropy materials in the rechargeable zinc-air batteries. [Display omitted] • The medium-entropy metal sulfides (MESs) were prepared via a two-step method. • Fe 1.2 (CoNi) 1.8 S 6 MES nanoparticles show high performance for both OER and ORR. • Electronic structure of MES can be opportunely regulated after sulfuration. • Rechargeable zinc-air battery assembled with MES delivers excellent performance. [ABSTRACT FROM AUTHOR]

The recent outbreak of Corona Virus Disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been a severe threat to the global public health and economy, however, effective drugs to treat COVID-19 are still lacking. Here, we employ a deep learning-based drug repositioning strategy to systematically screen potential anti-SARS-CoV-2 drug candidates that target the cell entry mechanism of SARS-CoV-2 virus from 2635 FDA-approved drugs and 1062 active ingredients from Traditional Chinese Medicine herbs. In silico molecular docking analysis validates the interactions between the top compounds and host receptors or viral spike proteins. Using a SARS-CoV-2 pseudovirus system, we further identify several drug candidates including Fostamatinib, Linagliptin, Lysergol and Sophoridine that can effectively block the cell entry of SARS-CoV-2 variants into human lung cells even at a nanomolar scale. These efforts not only illuminate the feasibility of applying deep learning-based drug repositioning for antiviral agents by targeting a specified mechanism, but also provide a valuable resource of promising drug candidates or lead compounds to treat COVID-19. • A host-directed drug repurposing targeting the cell entry mechanism of SARS-CoV-2. • Three independent deep learning methods for drug repurposing. • Thousands of approved drugs and natural compounds for repurposing. • Validation of top drug candidates by molecular docking and virus entry assay. [ABSTRACT FROM AUTHOR]

Development of low‐cost and high‐efficiency electrocatalysts for overall water splitting is of great significance in the sustainable hydrogen economy. Herein, Fe1.2(CoNi)1.8Sex medium‐entropy metal selenides (MESes) nanoparticles are prepared via the selenylation of metal‐organic frameworks (MOFs) precursors. The optimal Fe1.2(CoNi)1.8Se6 MESe exhibits an outstanding electrocatalytic performance in alkaline media, offering low overpotentials of 66 and 216 mV at 10 mA cm−2 for the hydrogen evolution reaction and oxygen evolution reaction, respectively. A full electrolysis apparatus with Fe1.2(CoNi)1.8Se6 MESe as both cathode and anode displays an excellent performance, achieving 10 mA cm−2 at a potential of 1.55 V. Furthermore, density functional theory calculations demonstrate that the formation of MESe enhances the surface charge density and brings the d‐band center closer to Fermi level, as compared with that of the MOF precursor. Overall, the proposed strategy of medium‐entropy materials presents a low‐cost approach to fabricate energy storage and conversion devices. [ABSTRACT FROM AUTHOR]

The surface tension of a liquid fuel is an important parameter in the fuel atomization process. B/JP-10 nanofluid fuels with different particle concentrations (5 mass%, 10 mass%, 15 mass% and 20 mass%) were prepared by selecting 100 nm, 300 nm and 500 nm B particles by a two-step method, in which Tween-85 was used as a surfactant. The surface tension of the above nanofluid fuels was tested at different temperatures (10–90 ℃) using the platinum plate method to investigate the effects of surfactant, temperature, particle concentration and temperature on the surface tension of B/JP-10 nanofluid fuels. The results show that the addition of surfactants helps to reduce the surface tension of the nanofluid fuel. The surface tension of the nanofluid fuel is higher than that of pure JP-10 and increases with increasing particle concentration and decreases with increasing particle size. The surface tension of the suspended fuel decreases linearly with increasing temperature in a certain temperature range (10–60 °C). [ABSTRACT FROM AUTHOR]

Aluminum (Al) particles are widely used in propellants, thermite and pyrotechnics. However, commonly used micro Al has drawbacks such as agglomeration, high ignition temperature and slow burning rate, making its energy potential not fully exploited in applications. Therefore, exploring pathways to enhance the combustion of Al particles has become the focus at present. Herein, L -malic acid (LMA) was used to corrode the surface of Al particles to obtain a sample (named LMAl) with an average specific surface area of 11.456 m2/g (corresponding to Al particles with a diameter of 194 nm). The particle size distribution of LMAl did not change significantly compared to pristine Al. The XPS results showed that a small amount of LMA and corrosion products remained on the surface of the LMAl particles. Thermal analysis tests showed that the thermal oxidation rate and efficiency of LMAl was dramatically higher than that of pristine Al. Compared with the pristine Al, the combustion characterization parameters of LMAl such as combustion intensity, ignition delay time, maximum combustion temperature, mass burning rate and combustion efficiency were all improved. This trend was maintained after blending the ammonium perchlorate (AP). The condensed combustion products (CCPs) of Al revealed a large number of agglomerates and unburned Al particles. While many broken particles and tentacle-like structures were found in the CCPs of LMAl. Overall, compared to Al, the combustion of LMAl is significantly enhanced. The thermal reaction and combustion behaviors of the two are quite different. This study provides new insights into improving the ignition and combustion of Al. [ABSTRACT FROM AUTHOR]

Proton exchange membranes with high selectivity are urgently required in energy and electronic technologies. Although Nafion represents the state‐of‐the‐art commercial proton exchange membrane material,it still suffers from the permeation of undesirable substances, like hydrogen in fuel cells and vanadium ions in redox flow batteries, due to the unmatched sizes between its ionic domains (3–5 nm) and these substances. In this work, we present a supramolecular modification strategy that simultaneously enhances the proton conductivity and selectivity of Nafion. We employ fluoroalkyl‐grafted polyoxometalate (POMs) nanoclusters as supramolecular additives to modify Nafion via co‐assembly. These POMs can precisely and robustly decorate at Nafion ionic domains, with their fluoroalkyl chains anchoring into the perfluorinated matrix while their inorganic clusters stay in the ionic regions. The hybrid membranes, with continuous proton hopping sites and nanoscale steric hindrance offered by POMs, exhibit a 56 % increase in proton conductivity and a 100 % improvement in proton/vanadium selectivity. This leads to significantly enhanced power density and energy efficiency in fuel cells and vanadium flow batteries, respectively. These results underscore the intriguing potential of molecular cluster additives in improving the functions of ion‐conducting membranes. [ABSTRACT FROM AUTHOR]

Proton exchange membranes with high selectivity are urgently required in energy and electronic technologies. Although Nafion represents the state‐of‐the‐art commercial proton exchange membrane material,it still suffers from the permeation of undesirable substances, like hydrogen in fuel cells and vanadium ions in redox flow batteries, due to the unmatched sizes between its ionic domains (3–5 nm) and these substances. In this work, we present a supramolecular modification strategy that simultaneously enhances the proton conductivity and selectivity of Nafion. We employ fluoroalkyl‐grafted polyoxometalate (POMs) nanoclusters as supramolecular additives to modify Nafion via co‐assembly. These POMs can precisely and robustly decorate at Nafion ionic domains, with their fluoroalkyl chains anchoring into the perfluorinated matrix while their inorganic clusters stay in the ionic regions. The hybrid membranes, with continuous proton hopping sites and nanoscale steric hindrance offered by POMs, exhibit a 56 % increase in proton conductivity and a 100 % improvement in proton/vanadium selectivity. This leads to significantly enhanced power density and energy efficiency in fuel cells and vanadium flow batteries, respectively. These results underscore the intriguing potential of molecular cluster additives in improving the functions of ion‐conducting membranes. [ABSTRACT FROM AUTHOR]

Although π‐conjugated two dimensional (2D) covalent organic frameworks (COFs) have been extensively reported, developing fully π‐conjugated 3D COFs is still an extremely difficult problem due to the lack of fully π‐conjugated 3D linkers. We synthesize a fully conjugated 3D COF (BUCT‐COF‐1) by designing a saddle‐shaped building block of aldehyde‐substituted cyclooctatetrathiophene (COThP)‐CHO. As a consequence of the fully conjugated 3D network, BUCT‐COF‐1 demonstrates ultrahigh Hall electron mobility up to ≈3.0 cm2 V−1 s−1 at room temperature, which is one order of magnitude higher than the current π‐conjugated 2D COFs. Temperature‐dependent conductivity measurements reveal that the charge carriers in BUCT‐ COF‐1 exhibit the band‐like transport mechanism, which is entirely different from the hopping transport phenomena observed in common organic materials. The findings indicate that fully conjugated 3D COFs can achieve electron delocalization and charge‐transport pathways within the whole 3D skeleton, which may open up a new frontier in the design of organic semiconducting materials. [ABSTRACT FROM AUTHOR]

Although π‐conjugated two dimensional (2D) covalent organic frameworks (COFs) have been extensively reported, developing fully π‐conjugated 3D COFs is still an extremely difficult problem due to the lack of fully π‐conjugated 3D linkers. We synthesize a fully conjugated 3D COF (BUCT‐COF‐1) by designing a saddle‐shaped building block of aldehyde‐substituted cyclooctatetrathiophene (COThP)‐CHO. As a consequence of the fully conjugated 3D network, BUCT‐COF‐1 demonstrates ultrahigh Hall electron mobility up to ≈3.0 cm2 V−1 s−1 at room temperature, which is one order of magnitude higher than the current π‐conjugated 2D COFs. Temperature‐dependent conductivity measurements reveal that the charge carriers in BUCT‐ COF‐1 exhibit the band‐like transport mechanism, which is entirely different from the hopping transport phenomena observed in common organic materials. The findings indicate that fully conjugated 3D COFs can achieve electron delocalization and charge‐transport pathways within the whole 3D skeleton, which may open up a new frontier in the design of organic semiconducting materials. [ABSTRACT FROM AUTHOR]

Wnt/β-catenin signaling is a conserved pathway crucially governing development, homeostasis, and oncogenesis. Discoveries of its regulators hold great values in both basic and translational research. Through screening, we identified a deubiquitinase, USP10, as a critical modulator of β-catenin. Mechanistically, USP10 binds to key scaffold Axin1 via conserved motifs and stabilizes Axin1 through K48-linked deubiquitination. Surprisingly, USP10 physically tethers Axin1 and β-catenin and promotes the phase separation for β-catenin suppression regardless of the enzymatic activity. Function-wise, USP10 enzymatic activity preferably regulates embryonic development and both the enzymatic activity and physical function jointly control intestinal homeostasis by antagonizing β-catenin. In colorectal cancer, USP10 substantially represses cancer growth mainly through physical promotion of phase separation and correlates with Wnt/β-catenin magnitude clinically. Collectively, we discovered USP10 functioning in multiple biological processes against β-catenin and unearthed the enzyme-dependent and -independent "dual-regulating" mechanism. These two functions of USP10 work in parallel and are context dependent. [Display omitted] • USP10 acts as a suppressor of Wnt/β-catenin signaling • USP10 stabilizes Axin1 via K48-linked deubiquitination • USP10 promotes phase separation to inhibit β-catenin regardless of DUB activity • The DUB-dependent and -independent paths work in parallel and are context dependent Wang et al. discovered USP10 as a suppressor of Wnt/β-catenin signaling. USP10 stabilizes the key scaffold protein Axin1 through DUB activity and facilitates the liquid-liquid phase separation to constrain β-catenin physically. The enzymatic-dependent and -independent functions work in parallel and are context dependent, thus presenting a prototype of protein functioning. [ABSTRACT FROM AUTHOR]

• Model prediction deviation less than 10%. • Aluminum agglomerate morphology close to experimental results. • Detailed information on particle size distribution of aluminum condensed phase products. Aluminum is an important additive in solid propellants used to improve energy efficiency, but agglomeration of aluminum particles can reduce the specific impulse of the engine, increase two-phase flow losses and cause ablation of the adiabatic layer. Therefore, it is important to understand the mechanism of formation, mode of movement and particle size characteristics of aluminum agglomerates in solid propellants to study the inhibition of agglomeration. In this paper, a three-dimensional numerical simulation of aluminum particle agglomeration near the burning surface of solid propellants was conducted using the discrete unit method based on direct tracking calculations of the detailed motion of individual particles. The model considered physical processes such as burning surface motion, aluminum particle precipitation, turbulent pulsation and the heating and melting of aluminum particle and used a grid-based contact detection method to accelerate the computational process. The agglomeration process of a solid propellant with specific formulation was experimentally investigated. Aluminum particle aggregates underwent splitting, and the final aluminum particle agglomerates were spherical droplets with typical structure. The agglomeration process of this propellant was investigated by means of a simulation. The accuracy of the agglomeration model was verified by comparing the results of the model for the agglomeration process and the shape and size distribution of agglomerates with available experimental data. Compared with the experimental results, the deviations of the equivalent particle sizes of agglomerates D 10 , D 50 , D 90 , D 4,3 , and D 3,2 obtained by using the simulation results were 6.3%, 6.3%, 9.4%, 7.5% and 6.7%, respectively. The aluminum particle agglomeration model established in this paper can predict the particle size distribution of aluminum agglomerates near the burning surface of solid propellants. The model was also used to further investigate the effects of aluminum particle content, ammonium perchlorate (AP) particle size and environmental pressure on aluminum particle agglomeration. Increasing the aluminum content or AP particle size aggravated aluminum particle agglomeration, whereas increasing pressure weakened it. [ABSTRACT FROM AUTHOR]

B/JP-10 suspension fuel is a novel energetic blended fuel with high application prospects, but it suffers from incomplete energy release in the actual combustion process. In this study, B/EtOH/JP-10 suspension fuels with different EtOH contents were prepared by a two-step method. The ignition and combustion characteristics were investigated using a CO 2 laser ignition test system. The focus is on the effect of EtOH addition on the fragmentation process and energy release of boron agglomerates. The results show that the addition of EtOH changes the ignition pattern of B/JP-10 suspension fuel and thus shortens its ignition delay, and the ignition delay of fuel droplets decreases with increasing EtOH content when the EtOH content is >31.2 wt%. During the combustion process, on the one hand, EtOH will strengthen the droplet's own "microburst" in the early stage of combustion, transporting JP-10 vapor and active boron to the oxygen-rich zone, thus improving the utilization of oxygen around the droplet; on the other hand, after the agglomerates are formed, EtOH will gradually break the agglomerates and transport active boron outward, promoting the contact between active boron and oxygen and finally improving the overall energy release efficiency of the fuel. • First improved energy release characteristics of boron-based suspension fuels from the base fluid perspective • "Microburst" behavior during two-phase combustion process is critical to the fuel system energy release • EtOH can break boron agglomerates from inside to promote the energy release of boron particles [ABSTRACT FROM AUTHOR]

The CRISPR-based nucleic acid detection systems have shown great potential for point-of-care testing of viral pathogens, especially in the context of COVID-19 pandemic. Here we optimize several key parameters of reaction chemistry and develop a Chemical Enhanced CRISPR Detection system for nucleic acid (termed CECRID). For the Cas12a/Cas13a-based signal detection phase, we determine buffer conditions and substrate range for optimal detection performance, and reveal a crucial role of bovine serum albumin in enhancing trans-cleavage activity of Cas12a/Cas13a effectors. By comparing several chemical additives, we find that addition of L-proline can secure or enhance Cas12a/Cas13a detection capability. For isothermal amplification phase with typical LAMP and RPA methods, inclusion of L-proline can also enhance specific target amplification as determined by CRISPR detection. Using SARS-CoV-2 pseudovirus, we demonstrate CECRID has enhanced detection sensitivity over chemical additive-null method with either fluorescence or lateral flow strip readout. Thus, CECRID provides an improved detection power and system robustness, and helps to develop enhanced reagent formula or test kit towards practical application of CRISPR-based diagnostics. • Several key parameters behind Cas12a/Cas13a-based nucleic acid detection are determined and optimized. • Bovine serum albumin is a bona fide enhancer for CRISPR detection. • L-proline can greatly improve the performance for both target amplification phase and CRISPR detection phase. • An enhanced reagent formula and CRISPR-based nucleic acid detection system are provided. [ABSTRACT FROM AUTHOR]