Constrained C2 adsorbate orientation enables CO-to-acetate electroreduction.

The carbon dioxide and carbon monoxide electroreduction reactions, when powered using low-carbon electricity, offer pathways to the decarbonization of chemical manufacture1,2. Copper (Cu) is relied on today for carbon-carbon coupling, in which it produces mixtures of more than ten C2+ chemicals3-6: a long-standing challenge lies in achieving selectivity to a single principal C2+ product7-9. Acetate is one such C2 compound on the path to the large but fossil-derived acetic acid market. Here we pursued dispersing a low concentration of Cu atoms in a host metal to favour the stabilization of ketenes10-chemical intermediates that are bound in monodentate fashion to the electrocatalyst. We synthesize Cu-in-Ag dilute (about 1 atomic per cent of Cu) alloy materials that we find to be highly selective for acetate electrosynthesis from CO at high *CO coverage, implemented at 10 atm pressure. Operando X-ray absorption spectroscopy indicates in situ-generated Cu clusters consisting of <4 atoms as active sites. We report a 12:1 ratio, an order of magnitude increase compared to the best previous reports, in the selectivity for acetate relative to all other products observed from the carbon monoxide electroreduction reaction. Combining catalyst design and reactor engineering, we achieve a CO-to-acetate Faradaic efficiency of 91% and report a Faradaic efficiency of 85% with an 820-h operating time. High selectivity benefits energy efficiency and downstream separation across all carbon-based electrochemical transformations, highlighting the importance of maximizing the Faradaic efficiency towards a single C2+ product11.

Autophagy Induced by Low Shear Stress Leads to Endothelial Glycocalyx Disruption.

INTRODUCTION: Previous studies have confirmed that low shear stress (LSS) induces glycocalyx disruption, leading to endothelial dysfunction. However, the role of autophagy in LSS-induced glycocalyx disruption and relevant mechanism are not clear. In this study, we hypothesized that LSS may promote autophagy, disrupting the endothelium glycocalyx. METHODS: Human umbilical vein endothelial cells were subjected to physiological shear stress and LSS treatments, followed by the application of autophagy inducers and inhibitors. Additionally, cells were treated with specific matrix metalloproteinase-2 (MMP-2) and matrix metalloproteinase-9 (MMP-9) inhibitor. The expression of autophagic markers, glycocalyx, MMP-2, and MMP-9 was measured. RESULTS: LSS impacted the expression of endothelium autophagy markers, increasing the expression of LC3II.LC3I-1 and Beclin-1, and decreasing the levels of p62, accompanied by glycocalyx disturbance. Moreover, LSS upregulated the expression of MMP-2 and MMP-9 and downregulated the levels of syndecan-1 and heparan sulfate (HS). Additionally, expression of MMP-2 and MMP-9 was increased by an autophagy promoter but was decreased by autophagy inhibitor treatment under LSS. Autophagy and MMP-2 and MMP-9 further caused glycocalyx disruption. CONCLUSION: LSS promotes autophagy, leading to glycocalyx disruption. Autophagy increases the expression of MMP-2 and MMP-9, which are correlated with the glycocalyx destruction induced by LSS.

Designing State-of-the-Art Gas Sensors: From Fundamentals to Applications.

Gas sensors are crucial in environmental monitoring, industrial safety, and medical diagnostics. Due to the rising demand for precise and reliable gas detection, there is a rising demand for cutting-edge gas sensors that possess exceptional sensitivity, selectivity, and stability. Due to their tunable electrical properties, high-density surface-active sites, and significant surface-to-volume ratio, nanomaterials have been extensively investigated in this regard. The traditional gas sensors utilize homogeneous material for sensing where the adsorbed surface oxygen species play a vital role in their sensing activity. However, their performance for selective gas sensing is still unsatisfactory because the employed high temperature leads to the poor stability. The heterostructures nanomaterials can easily tune sensing performance and their different energy band structures, work functions, charge carrier concentration and polarity, and interfacial band alignments can be precisely designed for high-performance selective gas sensing at low temperature. In this review article, we discuss in detail the fundamentals of semiconductor gas sensing along with their mechanisms. Further, we highlight the existed challenges in semiconductor gas sensing. In addition, we review the recent advancements in semiconductor gas sensor design for applications from different perspective. Finally, the conclusion and future perspectives for improvement of the gas sensing performance are discussed.

Interface Engineering Induced Electron Redistribution at PtNs /NiTe-Ns Interfaces for Promoting pH-Universal and Chloride-Tolerant Hydrogen Evolution Reaction.

Exploring highly efficient hydrogen evolution reaction (HER) electrocatalysts for large-scale water electrolysis in the full potential of hydrogen (pH) range is highly desirable, but it remains a significant challenge. Herein, a simple pathway is proposed to synthesize a hybrid electrocatalyst by decorating small metallic platinum (Pt) nanosheets on a large nickel telluride nanosheet (termed as PtNs /NiTe-Ns). The as-prepared PtNs /NiTe-Ns catalyst only requires overpotentials of 72, 162, and 65 mV to reach a high current density of 200 mA cm-2 in alkaline, neutral and acidic conditions, respectively. Theoretical calculations reveal that the combination of metallic Pt and NiTe-Ns subtly modulates the electronic redistribution at their interface, improves the charge-transfer kinetics, and enhances the performance of Ni active sites. The synergy between the Pt site and activated Ni site near the interface in PtNs /NiTe-Ns promotes the sluggish water-dissociation kinetics and optimizes the subsequent oxyhydrogen/hydrogen intermediates (OH*/H*) adsorption, accelerating the HER process. Additionally, the superhydrophilicity and superaerophobicity of PtNs /NiTe-Ns facilitate the mass transfer process and ensure the rapid desorption of generated bubbles, significantly enhancing overall alkaline water/saline water/seawater electrolysis catalytic activity and stability.

Engineering Amorphous/Crystalline Ru(OH)3/CoFe-Layered Double Hydroxide for Hydrogen Evolution at 1000 mA cm-2.

For large-scale industrial applications, it is highly desirable to create effective, economical electrocatalysts with long-term stability for the hydrogen evolution reaction (HER) at a large current density. Herein, we report a unique motif with crystalline CoFe-layered hydroxide (CoFe-LDH) nanosheets enclosed by amorphous ruthenium hydroxide (a-Ru(OH)3/CoFe-LDH) to realize the efficient hydrogen production at 1000 mA cm-2, with a low overpotential of 178 mV in alkaline media. During the continuous HER process for 40 h at such a large current density, the potential remains almost constant with only slight fluctuations, indicating good long-term stability. The remarkable HER performance can be attributed to the charge redistribution caused by abundant oxygen vacancies in a-Ru(OH)3/CoFe-LDH. The increased electron density of states lowers the charge-transfer resistance and promotes the formation and release of H2 molecules. The water-splitting electrolyzer with a-Ru(OH)3/CoFe-LDH as both an anode and a cathode in 1.0 M KOH demonstrates stable hydrogen production and a 100% faradic efficiency. The design strategy of interface engineering in this work will inspire the design of practical electrocatalysts for water splitting on an industrial scale.

IMGC-GNN: A multi-granularity coupled graph neural network recommendation method based on implicit relationships.

In the application recommendation field, collaborative filtering (CF) method is often considered to be one of the most effective methods. As the basis of CF-based recommendation methods, representation learning needs to learn two types of factors: attribute factors revealed by independent individuals (e.g., user attributes, application types) and interaction factors contained in collaborative signals (e.g., interactions influenced by others). However, existing CF-based methods fail to learn these two factors separately; therefore, it is difficult to understand the deeper motivation behind user behaviors, resulting in suboptimal performance. From this point of view, we propose a multi-granularity coupled graph neural network recommendation method based on implicit relationships (IMGC-GNN). Specifically, we introduce contextual information (time and space) into user-application interactions and construct a three-layer coupled graph. Then, the graph neural network approach is used to learn the attribute and interaction factors separately. For attribute representation learning, we decompose the coupled graph into three homogeneous graphs with users, applications, and contexts as nodes. Next, we use multilayer aggregation operations to learn features between users, between contexts, and between applications. For interaction representation learning, we construct a homogeneous graph with user-context-application interactions as nodes. Next, we use node similarity and structural similarity to learn the deep interaction features. Finally, according to the learned representations, IMGC-GNN makes accurate application recommendations to users in different contexts. To verify the validity of the proposed method, we conduct experiments on real-world interaction data from three cities and compare our model with seven baseline methods. The experimental results show that our method has the best performance in the top-k recommendation.

Atomic Metal-Support Interaction Enables Reconstruction-Free Dual-Site Electrocatalyst.

Real bifunctional electrocatalysts for hydrogen evolution reaction and oxygen evolution reaction have to be the ones that exhibit a steady configuration during/after reaction without irreversible structural transformation or surface reconstruction. Otherwise, they can be termed as "precatalysts" rather than real catalysts. Herein, through a strongly atomic metal-support interaction, single-atom dispersed catalysts decorating atomically dispersed Ru onto a nickel-vanadium layered double hydroxide (LDH) scaffold can exhibit excellent HER and OER activities. Both in situ X-ray absorption spectroscopy and operando Raman spectroscopic investigation clarify that the presence of atomic Ru on the surface of nickel-vanadium LDH is playing an imperative role in stabilizing the dangling bond-rich surface and further leads to a reconstruction-free surface. Through strong metal-support interaction provided by nickel-vanadium LDH, the significant interplay can stabilize the reactive atomic Ru site to reach a small fluctuation in oxidation state toward cathodic HER without reconstruction, while the atomic Ru site can stabilize the Ni site to have a greater structural tolerance toward both the bond constriction and structural distortion caused by oxidizing the Ni site during anodic OER and boost the oxidation state increase in the Ni site that contributes to its superior OER performance. Unlike numerous bifunctional catalysts that have suffered from the structural reconstruction/transformation for adapting the HER/OER cycles, the proposed Ru/Ni3V-LDH is characteristic of steady dual reactive sites with the presence of a strong metal-support interaction (i.e., Ru and Ni sites) for individual catalysis in water splitting and is revealed to be termed as a real bifunctional electrocatalyst.

A Single-Atom Fe-N-C Catalyst with Ultrahigh Utilization of Active Sites for Efficient Oxygen Reduction.

Fe-N-C single-atom catalysts (SACs) are emerging as a promising class of electrocatalysts for the oxygen reduction reaction (ORR) to replace Pt-based catalysts. However, due to the limited loading of Fe for SACs and the inaccessibility of internal active sites, only a small portion of the sites near the external surface are able to contribute to the ORR activity. Here, this work reports a metal-organic framework-derived Fe-N-C SAC with a hierarchically porous and concave nanoarchitecture prepared through a facile but effective strategy, which exhibits superior electrocatalytic ORR activity with a half-wave potential of 0.926 V (vs RHE) in alkaline media and 0.8 V (vs RHE) in acidic media while maintaining excellent stability. The superior ORR activity of the as-designed catalyst stems from the unique architecture, where the hierarchically porous architecture contains micropores as Fe SAC anchoring sites, meso-/macro-pores as accessible channels, and concave shell for increasing external surface area. The unique architecture has dramatically enhanced the utilization of previously blocked internal active sites, as confirmed by a high turnover frequency of 3.37 s-1 and operando X-ray absorption spectroscopy analysis with a distinct shift of adsorption edge.

Ultrasonic-assisted decoration of Ag2WO4, AgI, and Ag nanoparticles over tubular g-C3N4: Plasmonic photocatalysts for impressive removal of tetracycline under visible light.

The development of an efficient, eco-friendly, and low-cost photocatalyst is essential for addressing environmental and energy crises. In this regard, we report novel plasmonic photocatalysts through adorning tubular g-C3N4 with Ag2WO4, Ag, and AgI nanoparticles (TGCN/Ag/Ag2WO4/AgI) fabricated via a facile ultrasonic-irradiation procedure. The TGCN/Ag/Ag2WO4/AgI (20%) nanocomposite presented the excellent photocatalytic ability for removal of tetracycline hydrochloride under visible light, which was almost 45.6, 4.03, and 1.32 times more than GCN, TGCN, and TGCN/Ag/Ag2WO4 (20%) photocatalysts, respectively. Interestingly, the photocatalyst displayed impressive ability for the degradations of amoxicilline, rhodamine B, methyl orange, fuchsine, and methylene blue, which was 14.7, 52.2, 9.8, 13.2, and 7.46 times as much as pure GCN. The outcomes of DRS, PL, EIS, and photocurrent density analyses proved that the impressive activity could be related to the highly promoted harvesting of visible light, segregation of charge carriers, and improved charge migrations. In addition, trapping tests exhibited that •O2- and h+ were active species in the photocatalysis process.

Synthesis and Micromechanistic Studies of Sensitized Bentonite for Methyl Orange and Rhodamine-B Adsorption from Wastewater: Experimental and DFT-Based Analysis.

This work reports the formation of a novel adsorbent, prepared by activating bentonite with cinnamic acid, which is highly efficient to remove dyes from wastewater. The adsorption efficiency of the cinnamic acid activated bentonite was compared with unmodified bentonite by removing methyl orange and rhodamine-B from polluted water. The characterization was performed through X-ray diffraction (XRD) Fourier transform infrared (FTIR) and scanning electron microscopy (SEM). The results indicated that acidic pH and low temperature were more suitable for the selected dyes adsorption. The analysis of the data was done by the Langmuir and Freundlich isotherms; the Freundlich isotherm showed more suitability for the equilibrium data. The data were further analyzed by pseudo-first and pseudo-second-order models to study adsorption kinetics. The results showed that methyl orange and rhodamine-B adsorption obeyed pseudo-order kinetics. The results obtained from this research suggested that acid activation of bentonite with cinnamic acid increased the surface area of the clay and hence enhanced its adsorption efficiency. The maximum adsorption efficiency for the removal of methyl orange and rhodamine-B was up to 99.3 mg g-1 and 44.7 mg g-1, respectively, at 25 °C. This research provides an economical modification technique of bentonite, which makes it cost-effective and a good adsorbent for wastewater treatment.

Accurate Sybil Attack Detection Based on Fine-Grained Physical Channel Information.

With the development of the Internet-of-Things (IoT), wireless network security has more and more attention paid to it. The Sybil attack is one of the famous wireless attacks that can forge wireless devices to steal information from clients. These forged devices may constantly attack target access points to crush the wireless network. In this paper, we propose a novel Sybil attack detection based on Channel State Information (CSI). This detection algorithm can tell whether the static devices are Sybil attackers by combining a self-adaptive multiple signal classification algorithm with the Received Signal Strength Indicator (RSSI). Moreover, we develop a novel tracing scheme to cluster the channel characteristics of mobile devices and detect dynamic attackers that change their channel characteristics in an error area. Finally, we experiment on mobile and commercial WiFi devices. Our algorithm can effectively distinguish the Sybil devices. The experimental results show that our Sybil attack detection system achieves high accuracy for both static and dynamic scenarios. Therefore, combining the phase and similarity of channel features, the multi-dimensional analysis of CSI can effectively detect Sybil nodes and improve the security of wireless networks.

Anodic Hydrazine Oxidation Assists Energy-Efficient Hydrogen Evolution over a Bifunctional Cobalt Perselenide Nanosheet Electrode.

Water electrolysis is a promising source of hydrogen; however, technological challenges remain. Intensive efforts have focused on developing highly efficient and earth-abundant electrocatalysts for water splitting. An effective strategy is proposed, using a bifunctional tubular cobalt perselenide nanosheet electrode, in which the sluggish oxygen evolution reaction is substituted with anodic hydrazine oxidation so as to assist energy-efficient hydrogen production. Specifically, this electrode produces a current density of 10 mA cm-2 at -84 mV for hydrogen evolution and -17 mV for hydrazine oxidation in 1.0 m KOH and 0.5 m hydrazine electrolyte. An ultralow cell voltage of only 164 mV is required to generate a current density of 10 mA cm-2 for 14 hours of stable water electrolysis.

Synthesis of fluorine-doped α-Fe2O3 nanorods toward enhanced lithium storage capability.

Nanostructured fluorine-doped α-Fe2O3 nanorods were synthesized based on a one-step low temperature hydrothermal method. The XPS results verified that fluorine has been successfully incorporated into the hematite lattice. The delivered lithium capacity was effectively improved owing to the fluorine doping comparing with the pristine α-Fe2O3. The increase in electrochemical capacity of fluorine-doped α-Fe2O3 was then studied from the pointviews of nanostructure, electronic properties, and magnetic characteristics.

Hybrid Flexible Resistive Random Access Memory-Gated Transistor for Novel Nonvolatile Data Storage.

Here, a single-device demonstration of novel hybrid architecture is reported to achieve programmable transistor nodes which have analogies to flash memory by incorporating a resistive switching random access memory (RRAM) device as a resistive switch gate for field effect transistor (FET) on a flexible substrate. A high performance flexible RRAM with a three-layered structure is fabricated by utilizing solution-processed MoS2 nanosheets sandwiched between poly(methyl methacrylate) polymer layers. Gate coupling with the pentacene-based transistor can be controlled by the RRAM memory state to produce a nonprogrammed state (inactive) and a programmed state (active) with a well-defined memory window. Compared to the reference flash memory device based on the MoS2 floating gate, the hybrid device presents robust access speed and retention ability. Furthermore, the hybrid RRAM-gated FET is used to build an integrated logic circuit and a wide logic window in inverter logic is achieved. The controllable, well-defined memory window, long retention time, and fast access speed of this novel hybrid device may open up new possibilities of realizing fully functional nonvolatile memory for high-performance flexible electronics.

Atomic resolution of nitrogen-doped graphene on Cu foils.

Atomic-level substitutional doping can significantly tune the electronic properties of graphene. Using low-temperature scanning tunneling microscopy and spectroscopy, the atomic-scale crystalline structure of graphene grown on polycrystalline Cu, the distribution of nitrogen dopants and their effect on the electronic properties of graphene were investigated. Both the graphene sheet growth and nitrogen doping were performed using microwave plasma-enhanced chemical vapor deposition. The results indicated that the nitrogen dopants preferentially sit at the grain boundaries of the graphene sheets and confirmed that plasma treatment is a potential method to incorporate foreign atoms into the graphene lattice to tailor the graphene's electronic properties.

How big five personality traits influence information sharing on social media: A meta analysis.

Research interest in information sharing behavior on social media has significantly increased over the past decade. However, empirical studies on the relationship between Big Five personality traits and information sharing behavior have yielded contradictory conclusions. We aimed to investigate how Big Five personality influences information sharing behavior on social media. This meta-analysis systematically reviewed high-quality studies indexed by web of science and CNKI from the past decade (n = 27, with 31969 samples) and performed a meta-analysis to examine the association between Big Five personality traits and information sharing behavior. The literature search was performed in September 2023. The meta-analysis results showed that extraversion (ß = 0.05**) had a positive relationship with information sharing behavior on social media. Agreeableness (ß = -0.06**), conscientiousness (ß = -0.03**), and neuroticism (ß = -0.03**) had negative relationships with information sharing behavior on social media. However, the relationship between openness and information sharing behavior was not clearly observed due to insufficient research. The meta-analysis results are made available to the scientific community to enhance research, comprehension, and utilization of social media.

A study of blockchain-based liquidity cross-chain model.

Blockchain cross-chaining is about interconnectivity and interoperability between chains and involves both physical to virtual digital aspects and cross-chaining between digital networks. During the process, the liquidity transfer of information or assets can increase the use of items with other chains, so it is worth noting that the enhancement of cross-chain liquidity is of great practical importance to cross-chain technology. In this model, Layerzero is used as the primary secure cross-chain facility to build a full-chain identity by unifying NFT-distributed autonomous cross-chain identity IDs; applying super-contract pairs to enhance cross-chain liquidity; and initiating a dynamic transaction node creditworthiness model to increase the security of the cross-chain model and its risk management. Finally, by verifying three important property metrics timeliness is improved by at least 18%, robustness is increased by at least 50.9%, and radius of convergence is reduced by at least 25%. It is verified that the liquidity cross-chain model can eliminate the authentication transition between hierarchies while saving the cross-chain time cost, as a way to truly realize the liquid interoperability between multiple chains of blockchain.

Predictive role of glycocalyx components and MMP-9 in cardiopulmonary bypass patients for ICU stay.

Background: Shedding of glycocalyx is relevant to worse prognosis in surgical patients, and elevated levels of serum matrix metalloproteinase-9 (MMP-9) are associated with this phenomenon. This study aimed to investigate the dynamic alterations of serum glycocalyx components and MMP-9 during cardiopulmonary bypass (CPB), and evaluate their predictive capacities for prolonged intensive care unit (ICU) stay, as well as their correlation with coagulation dysfunction. Methods: This retrospective study analyzed serum levels of syndecan-1, heparan sulfate (HS), and MMP-9 at different time points during CPB, and assessed their association with prolonged ICU stay and coagulation dysfunction. Results: Syndecan-1, HS, and MMP-9 exhibited divergent changes during CPB. Serum levels of syndecan-1 (AUC = 78.0 %) and MMP-9 (AUC = 78.4 %) were validated as reliable predictors for prolonged ICU stay, surpassing the predictive value of creatinine (AUC = 70.0 %). Syndecan-1 (rho = 0.566, P < 0.01 at T1 and rho = 0.526, P < 0.01 at T2) and HS (rho = 0.403, P < 0.05 at T4) exhibited correlations with activated partial thromboplastin time (APTT) ratio beyond the normal range. Conclusions: Our findings advocate the potential efficacy of serum glycocalyx components and MMP-9 as early predictive indicators for extended ICU stay following cardiac surgery with CPB. Additionally, we observed a correlation between glycocalyx disruption during CPB and coagulation dysfunction. Further studies with expansive cohorts are warranted to consolidate our findings and explore the predictive potential of other glycocalyx components.

A motif for B/O-site modulation in LaFeO3 towards boosted oxygen evolution.

Here, a series of transition metal (Ni) doped iron-based perovskite oxides LaFe1-xNixO3-δ (x = 0, 0.25, 0.5, 0.75, 1) were prepared, and then the perovskite oxide with the optimized nickel-iron ratio was doped with non-metallic elements (N). Experimental and theoretical investigations reveal that the co-doping breaks the traditional linear constraint relationship (GOOH - GOH = 3.2 eV) and the theoretical overvoltage is reduced from 0.64 V (LaFeO3-δ) to 0.44 V (LaFe0.5Ni0.5O3-δ/N). Specifically, Ni-doping can accelerate electron transfer and improve the conductivity. Moreover, N-doping can reduce the adsorption energy of *OH/*O and enhance the adsorption energy of *OOH. We demonstrated that the optimized cation and anion co-doped LaFe0.5Ni0.5O3-δ/N perovskite oxide exhibits an excellent OER performance, with a low overpotential of 270.6 mV at 10 mA cm-2 and a small Tafel slope of 65 mV dec-1 in 1 M KOH solution, markedly exceeding that of the parent perovskite oxide LaFeO3-δ (300.9 mV) and commercial IrO2 (289.1 mV). It also delivers decent durability with no significant degradation after a 35 h stability test. This work reveals the internal mechanism of perovskite oxide by doping cation and anion for water oxidation, which broadens the idea for the rational design of new perovskite-based sustainable energy catalysts.

Tailoring Oxygen Reduction Reaction Kinetics of Fe-N-C Catalyst via Spin Manipulation for Efficient Zinc-Air Batteries.

The interaction between oxygen species and metal sites of various orbitals exhibits intimate correlation with the oxygen reduction reaction (ORR) kinetics. Herein, a new approach for boosting the inherent ORR activity of atomically dispersed Fe-N-C matrix is represented by implanting Fe atomic clusters nearby. The as-prepared catalyst delivers excellent ORR activity with half-wave potentials of 0.78 and 0.90 V in acidic and alkaline solutions, respectively. The decent ORR activity can also be validated from the high-performance rechargeable Zn-air battery. The experiments and density functional theory calculations reveal that the electron spin-state of monodispersed Fe active sites is transferred from the low spin (LS, t2g 6 eg 0) to the medium spin (MS, t2g 5 eg 1) due to the involvement of Fe atomic clusters, leading to the spin electron filling in σ∗ orbit, by which it favors OH- desorption and in turn boosts the reaction kinetics of the rate-determining step. This work paves a solid way for rational design of high-performance Fe-based single atom catalysts through spin manipulation.