4 research outputs found

    Prediction of Carbon Dioxide Reduction Catalyst Using Machine Learning with a Few-Feature Model: WLEDZ

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    Cu-based alloy catalysts are widely used in the field of carbon dioxide reduction reaction (CO2RR), due to the good selectivity and low overpotential. In order to achieve efficient exploration of alloy catalysts for CO2RR, a machine learning (ML) model, based on a gradient boosting regression (GBR) algorithm, is developed. By implementing a rigorous feature selection process, the dimensionality of feature space is reduced from thirteen to five, including work function (W), local electronegativity (Loc_EN), electronegativity (EN), interplanar spacing (D), and atomic number (Z), which is referred to as the WLEDZ model. The few-feature model has a high performance as that with many features, and the ML model successfully and rapidly predicts the adsorption energy of the key intermediates (HCOO, CO, and COOH) in the CO2RR process. In addition, eight Cu-based bimetallic catalysts are predicted with highly promising alternatives. This demonstrates that the WLEDZ few-feature ML model can screen highly promising bimetallic alloy for CO2RR and can also be used for the design of other types of catalysts

    Image_3_A comprehensive mouse brain acetylome-the cellular-specific distribution of acetylated brain proteins.tif

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    Nε-lysine acetylation is a reversible posttranslational modification (PTM) involved in multiple physiological functions. Genetic and animal studies have documented the critical roles of protein acetylation in brain development, functions, and various neurological disorders. However, the underlying cellular and molecular mechanism are still partially understood. Here, we profiled and characterized the mouse brain acetylome and investigated the cellular distribution of acetylated brain proteins. We identified 1,818 acetylated proteins, including 5,196 acetylation modification sites, using a modified workflow comprising filter-aided sample preparation (FSAP), acetylated peptides enrichment, and MS analysis without pre- or post-fraction. Bioinformatics analysis indicated these acetylated mouse brain proteins were mainly located in the myelin sheath, mitochondrial inner membrane, and synapse, as well as their involvement in multiple neurological disorders. Manual annotation revealed that a set of brain-specific proteins were acetylation-modified. The acetylation of three brain-specific proteins was verified, including neurofilament light polypeptide (NEFL), 2’,3’-cyclic-nucleotide 3’-phosphodiesterase (CNP), and neuromodulin (GAP43). Further immunofluorescence staining illustrated that acetylated proteins were mainly distributed in the nuclei of cortex neurons and axons of hippocampal neurons, sparsely distributed in the nuclei of microglia and astrocytes, and the lack of distribution in both cytoplasm and nuclei of cerebrovascular endothelial cells. Together, this study provided a comprehensive mouse brain acetylome and illustrated the cellular-specific distribution of acetylated proteins in the mouse brain. These data will contribute to understanding and deciphering the molecular and cellular mechanisms of protein acetylation in brain development and neurological disorders. Besides, we proposed some problems that need to be solved in future brain acetylome research.</p

    Built-in Electric Field-Induced Work Function Reduction in C–Co<sub>3</sub>O<sub>4</sub> for Efficient Electrochemical Nitrogen Reduction

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    Co3O4 is a highly selective catalyst for the electrochemical conversion of N2 to NH3. However, the large work function (WF) of Co3O4 leads to unsatisfactory activity. To address this issue, a strong built-in electric field (BIEF) was constructed in Co3O4 by doping C atoms (C–Co3O4) to reduce the WF for improving the electrocatalytic performance. C–Co3O4 exhibited a remarkable NH3 yield of 38.5 μg h–1 mgcat–1 and a promoted FE of 15.1% at −0.3 V vs RHE, which were 2.2 and 1.9 times higher than those of pure Co3O4, respectively. Kelvin probe force microscopy (KPFM), zeta potential, and ultraviolet photoelectron spectrometry (UPS) confirmed the formation of strong BIEF and WF reduction in C–Co3O4. Additionally, in situ Raman measurements and density functional theory (DFT) calculations revealed the relationship between BIEF and WF and provided insights into the reaction mechanism. Our work offers valuable guidance for the design and development of more efficient nitrogen reduction catalysts
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