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As the anode material of LIBs, the SnS2 electrode boasts a reversible specific capacity as high as 1231 mA h g−1. Additionally, SnS2 possesses a CdI2-type layered structure with a layer spacing of 0.59 nm, which allows it to accommodate numerous lithium ions and facilitate rapid charge transfer. However, as a semiconductor material, SnS2's low electronic conductivity significantly hampers its lithium storage performance. In this paper, we propose enhancing the intrinsic electronic conductance of SnS2 through fluorine doping and the introduction of sulfur vacancies, thereby constructing the F-SnS2−x structure. The stability and superiority of this structure are confirmed by a series of theoretical calculations. The stability and rationality of the structure were characterized using the phonon spectrum. Calculation of the density of states and lithium ion diffusion barriers demonstrates that F-SnS2−x exhibits exceptional electron/lithium ion transport kinetics. Furthermore, the results of lithium ion binding energy and differential charge show that there is a strong interaction between the F-SnS2−x structure and lithium ions, which is advantageous for achieving long-term cycle stability. Importantly, one F-SnS2−x molecule can adsorb up to 4.5 Li atoms, yielding a corresponding theoretical specific capacity of 702 mA h g−1, which surpasses that of SnS2 with 4 atoms (586 mA h g−1). The theoretical calculation results of this work can provide valuable insights for improving the electronic conductivity and lithium storage performance of other metal sulfides. [ABSTRACT FROM AUTHOR]

SnO2 possesses a high theoretical capacity and excellent chemical stability, making it a suitable candidate for anode material in LIBs. However, its inherently low intrinsic conductivity and the volume effect hinder its Li + storage performance. To address this, we were guided by the idea of increasing the intrinsic conductivity of SnO2, introducing F-doping and oxygen vacancies into the SnO2 structure to constructed F-SnO2−x crystals. The stability and rationality of this structure were investigated through phonon spectrum calculations. Furthermore, the density of states calculations revealed the band gap of the F-SnO2−x crystal is only 0.03 eV, significantly lower than that of SnO2 (2.44 eV). Additionally, the lithium ion diffusion barrier corresponding to F-SnO2−x is 0.33 eV, which is also lower than that of SnO2 (0.72 eV). Consequently, the fast electron/lithium ion transport dynamics is favorable for the F-SnO2−x material in achieving excellent rate performance. Besides, the results of differential charge density analysis indicate that the F-SnO2−x electrode exhibits a charge transfer of 0.83 eV with lithium ions, accompanied by a binding energy of − 5.11 eV, these values surpass those of SnO2 material, suggesting a robust interaction between the F-SnO2−x crystal and lithium ions. Consequently, this strong interaction is advantageous for the electrode to maintain long-term cycling stability. The research outcomes of this work present novel approaches to enhancing the electrical conductivity and lithium storage capabilities of SnO2. [ABSTRACT FROM AUTHOR]

To address the issues of tedious optimization processes, insufficient fitting accuracy of surrogate models, and low optimization efficiency in drone propeller airfoil design, this paper proposes an aerodynamic optimization method for propeller airfoils based on DBO-BP (Dum Beetle Optimizer-Back-Propagation) and NSWOA (Non-Dominated Sorting Whale Optimization Algorithm). The NACA4412 airfoil is selected as the research subject, optimizing the original airfoil at three angles of attack (2°, 5° and 10°). The CST (Class Function/Shape Function Transformation) airfoil parametrization method is used to parameterize the original airfoil, and Latin hypercube sampling is employed to perturb the original airfoil within a certain range to generate a sample space. CFD (Computational Fluid Dynamics) software (2024.1) is used to perform aerodynamic analysis on the airfoil shapes within the sample space to construct a sample dataset. Subsequently, the DBO algorithm optimizes the initial weights and thresholds of the BP neural network surrogate model to establish the DBO-BP neural network surrogate model. Finally, the NSWOA algorithm is utilized for multi-objective optimization, and CFD software verifies and analyzes the optimization results. The results show that at the angles of attack of 2°, 5° and 10°, the test accuracy of the lift coefficient is increased by 45.35%, 13.4% and 49.3%, and the test accuracy of the drag coefficient is increased by 12.5%, 39.1% and 13.7%. This significantly enhances the prediction accuracy of the BP neural network surrogate model for aerodynamic analysis results, making the optimization outcomes more reliable. The lift coefficient of the airfoil is increased by 0.04342, 0.01156 and 0.03603, the drag coefficient is reduced by 0.00018, 0.00038 and 0.00027, respectively, and the lift-to-drag ratio is improved by 2.95892, 2.96548 and 2.55199, enhancing the convenience of airfoil aerodynamic optimization and improving the aerodynamic performance of the original airfoil. [ABSTRACT FROM AUTHOR]

Induced pluripotent stem cells (iPSCs) hold great potential for cell therapy and tissue engineering. Neural crest stem cells (NCSCs) are multipotent that are capable of differentiating into mesenchymal lineages. In this study, we investigated whether iPSC-derived NCSCs (iPSC-NCSCs) have potential for tendon repair. Human iPSC-NCSCs were suspended in fibrin gel and transplanted into a rat patellar tendon window defect. At 4 weeks post-transplantation, macroscopical observation showed that the repair of iPSC-NCSC-treated tendons was superior to that of non-iPSC-NCSC-treated tendons. Histological and mechanical examinations revealed that iPSC-NCSCs treatment significantly enhanced tendon healing as indicated by the improvement in matrix synthesis and mechanical properties. Furthermore, transplanted iPSC-NCSCs produced fetal tendon-related matrix proteins, stem cell recruitment factors, and tenogenic differentiation factors, and accelerated the host endogenous repair process. This study demonstrates a potential strategy of employing iPSC-derived NCSCs for tendon tissue engineering.

A method is described for determining and calibrating the CIE Whiteness Index (WI) of an OBA‐treated specimen without incorporating into the measurement system a mechanically adjustable UV filter. The method requires spectrophotometric measurement of the specimen under two lights: UV‐excluded to infer the reflectance r(λ) and UV to infer the fluorescence profile f(λ). Also required is a stored illuminant spectrum Iin(λ) that covers at least the whole visible wavelengths. Only one scalar value k is then needed to mathematically characterize the total spectral radiance factor (TSRF) of the same specimen under Iin(λ). Calibration uses a reference specimen with known WI, and adjusts k until the computed WI matches the reference WI value. If Iin(λ) is the illuminant chosen from ASTM E313 to define the WI, the k adjustment reduces to solving a single quadratic equation for k that involves the reference WI. In general, relative to directly measuring a specimen's TSRF, it is more instrument‐independent to use the current method to characterize TSRF. Therefore, if a fluorescent specimen is measured using UV and UV‐excluded illuminants, a complete, instrument‐stable characterization of the specimen's TSRF can be derived by adjusting k, which can be done through a closed‐form relation of k to the WI. [ABSTRACT FROM AUTHOR]