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Molecular imaging is partly defined as in vivo imaging of biological or biochemical processes using various markers [...].Molecular imaging is partly defined as in vivo imaging of biological or biochemical processes using various markers [...].

Electrolyte engineering advances Li metal batteries (LMBs) with high Coulombic efficiency (CE) by constructing LiF-rich solid electrolyte interphase (SEI). However, the low conductivity of LiF disturbs Li + diffusion across SEI, thus inducing Li + transfer-driven dendritic deposition. In this work, we establish a mechanistic model to decipher how the SEI affects Li plating in high-fluorine electrolytes. The presented theory depicts a linear correlation between the capacity loss and current density to identify the slope k (determined by Li + mobility of SEI components) as an indicator for describing the homogeneity of Li + flux across SEI, while the intercept dictates the maximum CE that electrolytes can achieve. This model inspires the design of an efficient electrolyte that generates dual-halide SEI to homogenize Li + distribution and Li deposition. The model-driven protocol offers a promising energetic analysis to evaluate the compatibility of electrolytes to Li anode, thus guiding the design of promising electrolytes for LMBs. The low conductivity of LiF disturbs Li + diffusion across solid electrolyte interphase (SEI) and induces Li + transfer-driven dendritic growth. Herein, the authors establish a mechanistic model to decipher how the SEI affects realistic Li plating in high-fluorine electrolytes.

Electrochemical CO 2 reduction can produce valuable products with high energy densities but the process is plagued by poor selectivities and low yields. Propanol represents a challenging product to obtain due to the complicated C 3 forming mechanism that requires both stabilization of *C 2 intermediates and subsequent C 1 –C 2 coupling. Herein, density function theory calculations revealed that double sulfur vacancies formed on hexagonal copper sulfide can feature as efficient electrocatalytic centers for stabilizing both CO* and OCCO* dimer, and further CO–OCCO coupling to form C 3 species, which cannot be realized on CuS with single or no sulfur vacancies. The double sulfur vacancies were then experimentally synthesized by an electrochemical lithium tuning strategy, during which the density of sulfur vacancies was well-tuned by the charge/discharge cycle number. The double sulfur vacancy-rich CuS catalyst exhibited a Faradaic efficiency toward n-propanol of 15.4 ± 1% at −1.05 V versus reversible hydrogen electrode in H-cells, and a high partial current density of 9.9 mA cm −2 at −0.85 V in flow-cells, comparable to the best reported electrochemical CO 2 reduction toward n-propanol. Our work suggests an attractive approach to create anion vacancy pairs as catalytic centers for multi-carbon-products. Electrochemical CO 2 reduction to the valuable n-propanol is challenging due to the complicated C 3 forming mechanism. Here, authors demonstrate double sulfur vacancies formed on hexagonal copper sulfide can serve as efficient electrocatalytic centers.

Elevating the charging cut-off voltage is one of the efficient approaches to boost the energy density of Li-ion batteries (LIBs). However, this method is limited by the occurrence of severe parasitic reactions at the electrolyte/electrode interfaces. Herein, to address this issue, we design a non-flammable fluorinated sulfonate electrolyte by multifunctional solvent molecule design, which enables the formation of an inorganic-rich cathode electrolyte interphase (CEI) on high-voltage cathodes and a hybrid organic/inorganic solid electrolyte interphase (SEI) on the graphite anode. The electrolyte, consisting of 1.9 M LiFSI in a 1:2  v / v mixture of 2,2,2-trifluoroethyl trifluoromethanesulfonate and 2,2,2-trifluoroethyl methanesulfonate, endows 4.55 V-charged graphite||LiCoO 2 and 4.6 V-charged graphite||NCM811 batteries with capacity retentions of 89% over 5329 cycles and 85% over 2002 cycles, respectively, thus resulting in energy density increases of 33% and 16% compared to those charged to 4.3 V. This work demonstrates a practical strategy for upgrading the commercial LIBs. The parasitic reactions at the electrolyte/electrode interfaces inhibit the increase of the charging cut-off voltage and the improvement of energy density. Herein, the authors design multifunctional solvent molecules and propose a practical design principle to stabilize the electrolyte/electrode interfaces for high-voltage Li ion batteries.

Long-chain alcohols synthesis (LAS, C 5+ OH) from syngas provides a promising route for the conversion of coal/biomass/natural gas into high-value chemicals. Cu-Fe binary catalysts, with the merits of cost effectiveness and high CO conversion, have attracted considerable attention. Here we report a nano-construct of a Fe 5 C 2 -Cu interfacial catalyst derived from Cu 4 Fe 1 Mg 4 -layered double hydroxide (Cu 4 Fe 1 Mg 4 -LDH) precursor, i.e ., Fe 5 C 2 clusters (~2 nm) are immobilized onto the surface of Cu nanoparticles (~25 nm). The interfacial catalyst exhibits a CO conversion of 53.2%, a selectivity of 14.8 mol% and a space time yield of 0.101 g g cat −1 h −1 for long-chain alcohols, with a surprisingly benign reaction pressure of 1 MPa. This catalytic performance, to the best of our knowledge, is comparable to the optimal level of Cu-Fe catalysts operated at much higher pressure (normally above 3 MPa). Long-chain alcohols synthesis from syngas conversion is a promising route for the production of high-value chemicals. Here the authors show that a heterogeneous Fe 5 C 2 /Cu catalyst derived from layered double hydroxides precursor exhibits excellent performance with a space time yield of 0.101 g g cat −1 h −1 at a low pressure of 1 MPa.

Visible near-infrared spectroscopy (VNIR) is extensively researched for obtaining soil property information due to its rapid, cost-effective, and environmentally friendly advantages. Despite its widespread application and significant achievements in soil property analysis, current soil prediction models continue to suffer from low accuracy. To address this issue, we propose a convolutional neural network model that can achieve high-precision soil property prediction by creating 2D multi-channel inputs and applying a multi-scale spatial attention mechanism. Initially, we explored two-dimensional multi-channel inputs for seven soil properties in the public LUCAS spectral dataset using the Gramian Angular Field (GAF) method and various preprocessing techniques. Subsequently, we developed a convolutional neural network model with a multi-scale spatial attention mechanism to improve the network’s extraction of relevant spatial contextual information. Our proposed model showed superior performance in a statistical comparison with current state-of-the-art techniques. The RMSE (R²) values for various soil properties were as follows: organic carbon content (OC) of 19.083 (0.955), calcium carbonate content (CaCO3) of 24.901 (0.961), nitrogen content (N) of 0.969 (0.933), cation exchange capacity (CEC) of 6.52 (0.803), pH in H2O of 0.366 (0.927), clay content of 4.845 (0.86), and sand content of 12.069 (0.789). Our proposed model can effectively extract features from visible near-infrared spectroscopy data, contributing to the precise detection of soil properties.

Forest soils play an important role in controlling global warming by reducing atmospheric methane (CH 4 ) concentrations. However, little attention has been paid to how nitrogen (N) deposition may alter microorganism communities that are related to the CH 4 cycle or CH 4 oxidation in subtropical forest soils. We investigated the effects of N addition (0, 30, 60, or 90 kg N ha −1  yr −1 ) on soil CH 4 flux and methanotroph and methanogen abundance, diversity, and community structure in a Moso bamboo ( Phyllostachys edulis ) forest in subtropical China. N addition significantly increased methanogen abundance but reduced both methanotroph and methanogen diversity. Methanotroph and methanogen community structures under the N deposition treatments were significantly different from those of the control. In N deposition treatments, the relative abundance of Methanoculleus was significantly lower than that in the control. Soil pH was the key factor regulating the changes in methanotroph and methanogen diversity and community structure. The CH 4 emission rate increased with N addition and was negatively correlated with both methanotroph and methanogen diversity but positively correlated with methanogen abundance. Overall, our results suggested that N deposition can suppress CH 4 uptake by altering methanotroph and methanogen abundance, diversity, and community structure in subtropical Moso bamboo forest soils.

The application of classic foaming agent faces several issues, including excessive use of defoaming agent, inadequate defoaming, pipeline blockage due to silicone oil precipitation, and high development cost of the foaming agent. To address the aforementioned issues, a novel intelligent foaming agent was created. This resulted in the development of a new intelligent foaming and discharging agent system. The study focused on analyzing key performance indicators of the foaming agent system, including temperature resistance, salt resistance, oil resistance, phase transition temperature point, foaming ability, foam half-life, liquid carrying capacity, and self-defoaming ability. The experimental findings indicate that TS-1 and ESAB exhibit favorable foaming performance and stability under the conditions of 90 °C temperature, 20 × 10 4  mg/L salinity, and 40% condensate oil content after a 1:1 mixture. Additionally, they are capable of undergoing phase transition within the temperature range of 12 to 15.2 °C. The Waring blender stirring method resulted in the foaming agent solution, which had a concentration of 3 g/L, reaching a volume of 487 mL. The foam’s half-life was 20 min, and the liquid carrying rate was 91.7%. After a duration of 20 min, the rate of self-defoaming was 81.6%. The addition of the self-developed synergist facilitated the defoaming process, which was successfully accomplished within a time frame of 10 min. Moreover, the self-defoaming rate achieved a remarkable 100%. The foam drainage agent system may autonomously react to variations in ambient temperature and achieve phase transition behavior through temperature stimulation. This is accomplished by utilizing the natural temperature difference between the bottom hole and the wellhead during foam drainage gas recovery operations. This innovation presents a novel concept for the foam drainage agent used in recovering drainage gas. It simplifies the operation of gas recovery in oil and gas wells, provides solutions for further smartening up oil and gas fields. It holds immense theoretical and practical importance.

A primary problem affecting the sustainable development of aquaculture is fish skin diseases. In order to prevent the outbreak of fish diseases and to provide prompt treatment to avoid mass mortality of fish, it is essential to detect and identify skin diseases immediately. Based on the YOLOv4 model, coupled with lightweight depthwise separable convolution and optimized feature extraction network and activation function, the detection and identification model of fish skin disease is constructed in this study. The developed model is tested for the diseases hemorrhagic septicemia, saprolegniasis, benedeniasis, and scuticociliatosis, and applied to monitor the health condition of fish skin in deep-sea cage culture. Results show that the MobileNet3-GELU-YOLOv4 model proposed in this study has an improved learning ability, and the number of model parameters is reduced. Compared to the original YOLOv4 model, its mAP and detection speed increased by 12.39% and 19.31 FPS, respectively. The advantages of the model are its intra-species classification capability, lightweight deployment, detection accuracy, and speed, making the model more applicable to the real-time monitoring of fish skin health in a deep-sea aquaculture environment.

The escalating utilization of ionizing radiation across medicine and industry underscored the paramount urgency of effective radioprotective materials. Conventional materials such as lead and concrete are widely used, and lead-free materials have also emerged to solve the problems of cumbersome and toxic lead, such as metal-containing micro/nano materials and polymers. Nevertheless, there is still a significant challenge in meeting the urgent need for lightweight and biocompatible alternatives. To tackle this challenge, this work utilizes molecular engineering of melanin to develop a panel of metal-free melanin materials with enhanced conjugation, heightened physical shielding against radiation and effective antioxidant properties. Furthermore, engineered melanin materials demonstrated in vivo γ-ray protection, increasing mice survival from ~12% to 100% after 6 Gy total body irradiation. Growing use of ionizing radiation in medicine and industry has increased risk of radiation exposure and injury. Here, Deng et al. utilize molecular engineering of melanin to develop a panel of metal-free melanin materials for shielding against γ-ray radiation.