The hard X-ray nanoprobe beamline at the SSRF

The hard X-ray nanoprobe beamline BL13U is a phase-Ⅱ beamline project at the Shanghai Synchrotron Radiation Facility.The beamline aims to enable comprehensive experiments at high spatial resolutions ranging from 50 to 10 nm. The X-ray energy range of the beamline, 5–25 keV, can detect most elements in the periodic table. Two operating modes were designed to accommodate the experimental requirements of high-energy resolution or high photon flux, respectively. X-ray nanofluorescence, nanodiffraction, and coherent diffraction imaging are developed as the main experimental techniques for BL13U. This paper describes the beamline optics, end station configurations, experimental methods under development, and preliminary test results. This comprehensive overview aims to provide a clear understanding of the beamline capabilities and potential applications.

Deep learning for estimation of Kirkpatrick-Baez mirror alignment errors

A deep learning-based automated Kirkpatrick-Baez mirror alignment method is proposed for synchrotron radiation.We trained a convolutional neural network(CNN)on simulated and experimental imaging data of a focusing system.Instead of learning directly from bypass images,we use a scatterer for X-ray modulation and speckle generation for image feature enhancement.The smallest normalized root-mean-square error on the validation set was 4%.Compared with conventional alignment methods based on motor scanning and analyzer setups,the present method simplified the optical layout and estimated alignment errors using a single-exposure experiment.Single-shot misalignment error estimation only took 0.13 s,significantly outperforming conventional methods.We also demonstrated the effects of the beam quality and pretraining using experimental data.The proposed method exhibited strong robustness,can handle high-precision focusing systems with complex or dynamic wavefront errors,and provides an important basis for intelligent control of future synchrotron radiation beamlines.

Surface engineering on MnO_(2)nanorods by La single atoms to accelerate oxygen reduction kinetics

Surface engineering,which modulates the electronic structure and adsorption/desorption properties of electrocatalysts,is one of the key strategies for improving the catalytic performance.Herein,we demonstrate a facile solid-phase reaction for surface engineering of MnO_(2)to boost the oxygen reduction kinetics.Via reaction with surface hydroxy groups,La single atoms with loading amount up to 2.7 wt%are anchored onto a-MnO_(2)nanorods.After surface engineering,the oxygen reduction reaction(ORR)kinetics is significantly improved with the half-wave potential from 0.70 to 0.84 V,the number of transferred electrons from 2.5 to 3.9 and the limiting current density from 4.8 to 6.0 mA·cm^(-2).In addition,the catalyst delivers superior discharge performance in both alkaline and neutral metal–air batteries.Density functional theory(DFT)calculations reveal that atomic La modulates the surface electronic configuration of MnO_(2),reduces its d-band center and thus lowers the OOH*and O*reaction energy barrier.This work provides a new route for rational design of highly active electrocatalyst and holds great potential for application in various catalytic reactions.