Nanocluster-agminated amorphous cobalt nanofilms for highly selective electroreduction of nitrate to ammonia.

Developing highly-efficient electrocatalysts for the nitrate reduction reaction (NITRR) is a persistent challenge. Here, we present the successful synthesis of 14 amorphous/low crystallinity metal nanofilms on three-dimensional carbon fibers (M-NFs/CP), including Al, Ti, Mn, Fe, Co, Ni, Cu, Zn, Ag, In, Sn, Pb, Au, or Bi, using rapid thermal evaporation. Among these samples, our study identifies the amorphous Co nanofilm with fine agglomerated Co clusters as the optimal electrocatalyst for NITRR in a neutral medium. The resulting Co-NFs/CP exhibits a remarkable Faradaic efficiency (FENH3) of 91.15 % at - 0.9 V vs RHE, surpassing commercial Co foil (39 %) and Co powder (20 %), despite sharing the same metal composition. Furthermore, during the electrochemical NITRR, the key intermediates on the surface of the Co-NFs/CP catalyst were detected by in situ Fourier-transform infrared (FTIR) spectroscopy, and the possible reaction ways were probed by Density functional theory (DFT) calculations. Theoretical calculations illustrate that the abundant low-coordinate Co atoms of Co-NFs/CP could enhances the adsorption of *NO3 intermediates compared to crystalline Co. Additionally, the amorphous Co structure lowers the energy barrier for the rate-determining step (*NH2→*NH3). This work opens a new avenue for the controllable synthesis of amorphous/low crystallinity metal nano-catalysts for various electrocatalysis reaction applications.

Synthesis, biological activities and docking studies of pleuromutilin derivatives with piperazinyl urea linkage.

Antibiotics resistance is becoming increasingly common, involving almost all antibiotics on the market. Diseases caused by drug resistant bacteria, such as MRSA, have high mortality and negatively affect public health. The development of new drugs would be an effective means of solving this problem. Modifications based on bioactive natural products could greatly shorten drug development time and improve success rate. Pleuromutilin, a natural product from the basidiomycete bacterial species, is a promising antibiotic candidate. In this study, a series of novel pleuromutilin derivatives possessing piperazinyl urea linkage were efficiently synthesised, and their antibacterial activities and bactericidal properties were evaluated via MIC, MBC and Time-kill kinetics assays. The results showed that all compounds exhibited potent activities against tested strains, especially MRSA strains with MIC values as low as 0.125 µg/mL; 8 times lower than that of marketed antibiotic Tiamulin. Docking studies indicate substituted piperazinyl urea derivatives could provide hydrogen bonds and initiate π-π stacking between molecules and surrounding residues.

Geometric Positioning Accuracy Improvement of ZY-3 Satellite Imagery Based on Statistical Learning Theory.

With the increasing demand for high-resolution remote sensing images for mapping and monitoring the Earth's environment, geometric positioning accuracy improvement plays a significant role in the image preprocessing step. Based on the statistical learning theory, we propose a new method to improve the geometric positioning accuracy without ground control points (GCPs). Multi-temporal images from the ZY-3 satellite are tested and the bias-compensated rational function model (RFM) is applied as the block adjustment model in our experiment. An easy and stable weight strategy and the fast iterative shrinkage-thresholding (FIST) algorithm which is widely used in the field of compressive sensing are improved and utilized to define the normal equation matrix and solve it. Then, the residual errors after traditional block adjustment are acquired and tested with the newly proposed inherent error compensation model based on statistical learning theory. The final results indicate that the geometric positioning accuracy of ZY-3 satellite imagery can be improved greatly with our proposed method.