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A broadband online X‐ray spectrometer has been designed and commissioned at the SUD beamline of the Shanghai Soft X‐ray Free‐Electron Laser Facility, which can deliver both SASE and seeded FEL pulses to user experiments, spanning the photon energy range of 50–620 eV. The resolving powers of the spectrometer calibrated via online measurement at 92 eV and 249 eV are ∼20000 and ∼15000, respectively, and the absolute photon energy is characterized by an electron time‐of‐flight spectrometer. The high energy resolution provided by the spectrometer can differentiate the fine structure in the FEL spectrum, to determine its pulse length. [ABSTRACT FROM AUTHOR]

Graphite, a key anode material in lithium-ion batteries, primarily relies on the Acheson graphitization furnace (AGF) for production. This research focuses on the power supply module of the AGF, particularly the electrodes and their power transmission clamps. A three-dimensional transient electric-thermal-fluid coupling model was developed to numerically analyze the temperature and electric field distributions during operation. The study revealed that heat conduction through furnace electrodes dominates temperature rise. Notably, clamping plates within transmission clamps exhibit high temperatures and gradients, posing a thermal failure risk. Efficient cooling plate design with liquid-cooled channels is crucial for temperature control. Additionally, maintaining high electrode temperatures reduces resistivity, lowering power consumption in the power supply module. This study provides insights into optimizing AGF power supply module design, emphasizing the importance of effective cooling strategies for clamping plates and the benefits of maintaining elevated electrode temperatures for energy efficiency. [ABSTRACT FROM AUTHOR]

Due to safety requirements, insensitive behavior under slow cook-off conditions is the desirable behavior for HTPE propellant. As a low sensitivity oxidant, PSAN is used to partially replace for AP in HTPE propellant formulation to improve the slow cook-off behavior further. But the effect of PSAN on the slow cook-off behavior of propellant is inconclusive. So, in this paper, two kinds of HTPE composite propellant contained either AP as oxidant or a mixture of AP and PSAN were manufactured, named HTPE/AP/Al propellant and HTPE/AP/PSAN/Al propellant respectively. Then the slow cook-off behavior of the two propellants were tested. The results indicated that the slow cook-off response of HTPE/AP/PSAN/Al propellant was much more violent than the response of HTPE/AP/Al propellant. Then the possible mechanism was proposed. It expressed that, during the slow cook-off test, the PSAN decomposed much more than AP, the crack and hole produced in propellant grain; meanwhile the decomposition of PSAN also accelerated the decomposition of HTPE binder, the the crack and hole or AP particles could not be covered effectively by the liquefied decomposition product of HTPE binder; if the ignition occurred, the combustion of thermal damaged propellant was sensitive to pressure, leading a violent response to slow cook-off. [ABSTRACT FROM AUTHOR]

This study explores the limitations of TiO 2 as a photocatalyst, focusing on its narrow bandwidth and high electron-hole complexation probabilities that restrict its applications. A novel one-pot synthesis method for TiO 2 /hydrochar matrix composites is presented, with variations achieved through control of hydrothermal temperature, time, and loading concentration. The efficacy of these composites in ammonia removal is investigated, revealing optimal performance for the composite denoted as 3Ti-160-7, synthesized with a titanium salt concentration of 0.3 mol L -1 , a hydrothermal temperature of 160 °C, and a hydrothermal time of 7 hours. Comparative analyses with commercial TiO 2 (P25) and hydrochar demonstrate superior performance of 3Ti-160-7, exhibiting significantly lower ammonia concentration and reduced NO and NO 2 concentrations. This research underscores the cost-effectiveness and application potential of TiO 2 /hydrochar matrix composites, offering valuable insights for the enhancement of photocatalytic activity and broader applicability in addressing TiO 2 -related challenges., Competing Interests: The authors declare no competing interests., (This journal is © The Royal Society of Chemistry.)

Background: Perineural invasion (PNI) of intrahepatic cholangiocarcinoma (ICC) is a strong independent risk factor for tumour recurrence and long-term patient survival. However, there is a lack of noninvasive tools for accurately predicting the PNI status. The authors develop and validate a combined model incorporating radiomics signature and clinicoradiological features based on machine learning for predicting PNI in ICC, and used the Shapley Additive explanation (SHAP) to visualize the prediction process for clinical application., Methods: This retrospective and prospective study included 243 patients with pathologically diagnosed ICC (training, n =136; external validation, n =81; prospective, n =26, respectively) who underwent preoperative contrast-enhanced computed tomography between January 2012 and May 2023 at three institutions (three tertiary referral centres in Guangdong Province, China). The ElasticNet was applied to select radiomics features and construct signature derived from computed tomography images, and univariate and multivariate analyses by logistic regression were used to identify the significant clinical and radiological variables with PNI. A robust combined model incorporating radiomics signature and clinicoradiological features based on machine learning was developed and the SHAP was used to visualize the prediction process. A Kaplan-Meier survival analysis was performed to compare prognostic differences between PNI-positive and PNI-negative groups and was conducted to explore the prognostic information of the combined model., Results: Among 243 patients (mean age, 61.2 years ± 11.0 (SD); 152 men and 91 women), 108 (44.4%) were diagnosed as PNI-positive. The radiomics signature was constructed by seven radiomics features, with areas under the curves of 0.792, 0.748, and 0.729 in the training, external validation, and prospective cohorts, respectively. Three significant clinicoradiological features were selected and combined with radiomics signature to construct a combined model using machine learning. The eXtreme Gradient Boosting exhibited improved accuracy and robustness (areas under the curves of 0.884, 0.831, and 0.831, respectively). Survival analysis showed the construction combined model could be used to stratify relapse-free survival (hazard ratio, 1.933; 95% CI: 1.093-3.418; P =0.021)., Conclusions: We developed and validated a robust combined model incorporating radiomics signature and clinicoradiological features based on machine learning to accurately identify the PNI statuses of ICC, and visualize the prediction process through SHAP for clinical application., (Copyright © 2023 The Author(s). Published by Wolters Kluwer Health, Inc.)