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Inspired by the active site of methane monooxygenase, we designed a Cu2O cluster anchored in the six-membered nitrogen cavity of a C2N monolayer (Cu2O@C2N) as a stable and efficient enzyme-like catalyst. Density functional theory (DFT) calculations reveal that the bridged Cu-O-Cu structure within C2N exhibits strong electronic coupling, which is favorable for methanol formation. Two competing mechanisms—the concerted and radical-rebound pathways—were systematically investigated, with the former being energetically preferred due to lower energy barriers and more stable intermediate states. Furthermore, strain engineering was employed to tune the geometric and electronic structure of the Cu-O-Cu site. Biaxial strain modulates the Cu-O-Cu bond angle, adsorption properties, and d-band center alignment, thereby selectively enhancing the concerted pathway. A volcano-like trend was observed between the applied strain and the methanol formation barrier, with 1% tensile strain yielding the overall energy barrier to methanol formation (ΔGoverall) as low as 1.31 eV. N2O effectively regenerated the active site and demonstrated strain-responsive kinetics. The electronic descriptor Δε (εd − εp) captured the structure–activity relationship, confirming the role of strain in regulating catalytic performance. This work highlights the synergy between geometric confinement and mechanical modulation, offering a rational design strategy for advanced C1 activation catalysts.

HighlightsHighly sensitive and selective room-temperature NO2 gas sensors by sensitizing MoS2 nanosheets with PbS quantum dots were demonstrated. In this device architecture, the receptor and transduction function as well as the utility factor of semiconductor gas sensors could be enhanced simultaneously.The strategy of sensitizing 2D semiconductors with quantum dots as sensitive and selective receptors for gas molecules may offer a powerful new degree of freedom to the surface and interface engineering of semiconductor gas sensors.The Internet of things for environment monitoring requires high performance with low power-consumption gas sensors which could be easily integrated into large-scale sensor network. While semiconductor gas sensors have many advantages such as excellent sensitivity and low cost, their application is limited by their high operating temperature. Two-dimensional (2D) layered materials, typically molybdenum disulfide (MoS2) nanosheets, are emerging as promising gas-sensing materials candidates owing to their abundant edge sites and high in-plane carrier mobility. This work aims to overcome the sluggish and weak response as well as incomplete recovery of MoS2 gas sensors at room temperature by sensitizing MoS2 nanosheets with PbS quantum dots (QDs). The huge amount of surface dangling bonds of QDs enables them to be ideal receptors for gas molecules. The sensitized MoS2 gas sensor exhibited fast and recoverable response when operated at room temperature, and the limit of NO2 detection was estimated to be 94 ppb. The strategy of sensitizing 2D nanosheets with sensitive QD receptors may enhance receptor and transducer functions as well as the utility factor that determine the sensor performance, offering a powerful new degree of freedom to the surface and interface engineering of semiconductor gas sensors.

Compared with noble metals, semiconductors with surface plasmon resonance effect are another type of SERS substrate materials. The main obstacles so far are that the semiconducting materials are often unstable and easy to be further oxidized or decomposed by laser irradiating or contacting with corrosive substances. Here, we report that metallic MoO 2 can be used as a SERS substrate to detect trace amounts of highly risk chemicals including bisphenol A (BPA), dichloropheno (DCP), pentachlorophenol (PCP) and so on. The minimum detectable concentration was 10 −7  M and the maximum enhancement factor is up to 3.75 × 10 6 . To the best of our knowledge, it may be the best among the metal oxides and even reaches or approaches to Au/Ag. The MoO 2 shows an unexpected high oxidation resistance, which can even withstand 300 °C in air without further oxidation. The MoO 2 material also can resist long etching of strong acid and alkali. Semiconducting materials are potential SERS substrates as alternatives to noble metals, but often suffer from poor stabilities and sensitivities. Here, the authors use molybdenum dioxide as a SERS material, showing high enhancement factors and stability to oxidation even at high temperatures.

A major feature of acute lung injury (ALI) is excessive inflammation in the lung. Vitexin is an active component from medicinal plants which has antioxidant and anti-inflammatory activities. Oxidative stress and inflammation play important roles in the pathophysiological processes in ALI. In the current study, we investigate the effect and potential mechanisms of Vitexin on lipopolysaccharide (LPS)-induced ALI. ALI was induced by LPS intratracheal instillation in C57BL/6 wild-type mice and Nrf2 gene knocked down (Nrf2-/-) mice. One hour before LPS challenge, Vitexin or vehicle intraperitoneal injection was performed. Bronchoalveolar lavage fluid and lung tissues were examined for lung inflammation and injury at 24 h after LPS challenge. Our animal study's results showed that LPS-induced recruitment of neutrophils and elevation of proinflammatory cytokine levels were attenuated by Vitexin treatment. Vitexin decreased lung edema and alveolar protein content. Moreover, Vitexin activated nuclear factor erythroid-2-related factor 2 (Nrf2), and increased the activity of its target gene heme oxygenase (HO)-1. The LPS-induced reactive oxygen species were inhibited by Vitexin. In addition, the activation of the nucleotide-binding domain and leucine-rich repeat PYD-containing protein 3 (NLRP3) inflammasome was suppressed by Vitexin. However, these effects of Vitexin were abolished in the Nrf2-/- mice. Our cell studies showed that Vitexin enhanced the expression of Nrf2 and HO-1 activity. Moreover, reactive oxygen species (ROS) and IL-1β productions were reduced in Vitexin-treated cells. However, knockdown of Nrf2 by siRNA in RAW cells reversed the benefit of Vitexin. Vitexin suppresses LPS-induced ALI by controlling Nrf2 pathway.

Single-atom catalysts supported by two-dimensional materials have been widely used in the electrochemical CO2 reduction reaction (CO2RR). Defects are inevitably generated during the preparation of two-dimensional materials. In this study, six Fe–N4-doped graphene catalysts (CAT1–CAT6) containing single carbon vacancy defects were designed and calculated using density functional theory (DFT) calculations. The stability, catalytic activity and product selectivity of these catalysts for CO2RR to C1 products CO, HCOOH, CH3OH and CH4 were discussed and compared with the defect-free Fe−N4-doped graphene catalyst (CAT0). The results show that CAT1–CAT6 all exhibit excellent thermodynamic and electrochemical stabilities. The possible reaction pathways for CO2 reduction to different C1 products were systematically investigated. The CAT2, CAT3 and CAT6 exhibit high selectivity for HCOOH, whereas the products of CAT1, CAT4 and CAT5 are HCOOH, CH3OH and CH4, the same as those of CAT0. Moreover, these six catalysts more effectively suppress the competing hydrogen evolution reaction (HER) compared to CAT0, indicating that the defect improves the catalytic selectivity of CO2RR. Among all of the catalysts, CAT2 demonstrates the most prominent catalytic activity and selectivity toward the CO2 reduction reaction (CO2RR). The large distortion of Fe−N4 in *HCOO with CAT2 contributes to the lower limiting potential UL. We hope that the finding that the large distortion of Fe−N4 could lower the limiting potential will provide theoretical insights for the design of more efficient CO2RR electrocatalysts.

In order to further study the expansion characteristics of left-turning non-motorized vehicles at intersections and the relationship between expansion characteristics and vehicle-bicycle conflicts, the trajectory point data of left-turning non-motorized vehicles are extracted using video trajectory tracking technology, and construct the cubic curve expansion envelope equation with the highest fitting degree. For the purpose of quantifying the expansion degree of non-motor vehicles after starting, two intersections in Guangxi Zhuang Autonomous Region were selected for case analysis, and the numerical range of expansion degree of the intersection with a left-turn waiting area and the intersection without a left-turn waiting area was obtained. Study the mathematical relationship between the expansion degree and its influencing factors, and establish the multivariate nonlinear regression equation between the expansion degree and the left-turn non-motorized vehicle flow, the number of parallel non-motorized vehicles, and the left-turn green light time. Analyze the vehicle-bicycle conflicts caused by the expansion of left-turning non-motorized vehicles, determine the essential factors affecting the number of non-motorized vehicles, and establish the multiple linear regression equation between the number of non-motorized vehicles and the number of left-turning non-motorized vehicles, the expansion degree, and the number of parallel non-motorized vehicles, the results show that the model has high accuracy. By analyzing the expansion characteristics of left-turning non-motorized vehicles at intersections, the relationship between different influencing factors and the expansion degree is obtained. Then the vehicle-bicycle conflicts under the influence of expansion characteristics is analyzed, providing theoretical ideas for improving traffic efficiency and optimizing traffic organization at intersections.

The electrocatalytic nitrogen reduction reaction (NRR) is considered a viable alternative to the Haber–Bosch process for ammonia synthesis, and the design of highly active and selective catalysts is crucial for the industrialization of the NRR. Dual-atom catalysts (DACs) with dual active sites offer flexible active sites and synergistic effects between atoms, providing more possibilities for the tuning of catalytic performance. In this study, we designed 48 graphene-based DACs with N4O2 coordination (MM′@N4O2-G) using density functional theory. Through a series of screening strategies, we explored the reaction mechanisms of the NRR for eight catalysts in depth and revealed the “acceptance–donation” mechanism between the active sites and the N2 molecules through electronic structure analysis. The study found that the limiting potential of the catalysts exhibited a volcano-shaped relationship with the d-band center of the active sites, indicating that the synergistic effect between the bimetallic components can regulate the d-band center position of the active metal M, thereby controlling the reaction activity. Furthermore, we investigated the selectivity of the eight DACs and identified five potential NRR catalysts. Among them, MoCo@N4O2-G showed the best NRR performance, with a limiting potential of −0.20 V. This study provides theoretical insights for the design and development of efficient NRR electrocatalysts.

Defect engineering can effectively regulate the catalytic activity of single-atom catalysts anchored on the graphene substrate. Based on graphene with topological defects consisting of 5,7-membered carbon rings, we designed and investigated twenty transition metal single-atom catalysts TM-N4-C57 (TM = Sc~Cu, Zr~Mo, Ru, Rh, Hf~Ir) for electrocatalytic nitrogen reduction reaction (NRR) using density functional theory (DFT) calculations. Employing a screening strategy that considers binding energy, N2 adsorption, catalytic activity, selectivity, and thermal stability, we ultimately screened out two electrocatalysts (Mo-N4-C57 and W-N4-C57) with excellent catalytic activity and selectivity. The NRR pathways on these two catalysts proceed through distal and consecutive pathways, with limiting potentials of −0.19 and −0.53 V for Mo-N4-C57 and W-N4-C57, respectively. The activity origin was elucidated through the analysis of partial density of states (PDOS) and crystal orbital Hamilton populations (COHP), suggesting that the interaction between Mo and NH2 in the *NH2 intermediate is relatively weak. An excellent linear relationship between UL and ICOHP has been identified, suggesting it as a descriptor. This work provides a theoretical basis for designing efficient NRR catalysts with modified second coordination spheres.

We report the synthesis of seven new proluciferins for convenient activity determination of enzymes belonging to the cytochrome P450 (CYP) 4 family. Biotransformation of these probe substrates was monitored using each of the twelve human CYP4 family members, and eight were found to act at least on one of them. For all substrates, activity of CYP4Z1 was always highest, while that of CYP4F8 was always second highest. Site of metabolism (SOM) predictions involving SMARTCyp and docking experiments helped to rationalize the observed activity trends linked to substrate accessibility and reactivity. We further report the first homology model of CYP4F8 including suggested substrate recognition residues in a catalytically competent conformation accessed by replica exchange solute tempering (REST) simulations.

For the discrimination of false targets, the discrimination probability can be improved by increasing the number of radar stations. However, that may result in a serious waste of equipment resources when too many radars are involved. An asymptotic subset selection strategy based on target positioning characteristics is proposed to address the above issues. Several effective strategies are considered to select some transmitters and receivers to form a radar subset, such as the rapid shrinkage method, global shrinkage method, and predetermined size method, which can guarantee the preset discrimination performance of limited equipment resources and reduce the waste of resources. All of the selected stations have good spatial distribution or strong discrimination capacity in multistatic radar system. Compared with the exhaustive search, the proposed subset selection strategy affords a significant reduction in terms of time complexity. The simulation results show that the radar subset can maintain approximate discrimination performance with the original multistatic radar systems. At the same time, the proposed method optimizes the number of radar stations and reduces data processing time and required communication links, thus effectively saving operating costs.