Solid electrolyte interphase (SEI) is an in situ formed thin coating on lithium ion battery (LIB) electrodes. The mechanical property of SEI largely defines the cycling performance and the safety of LIBs but has been rarely investigated. Here, we report quantitatively the Young's modulus of SEI films on MnO anodes. The inhomogeneity of SEI film in morphology, structure, and mechanical properties provides new insights to the evolution of SEI on electrodes. Furthermore, the quantitative methodology established in this study opens a new approach to direct investigation of SEI properties in various electrode materials systems.

Bi2Se3 attracts intensive attention as a typical thermoelectric material and a promising topological insulator material. However, previously reported Bi2Se3 nanostructures are limited to nanoribbons and smooth nanoplates. Herein, we report the synthesis of spiral Bi2Se3 nanoplates and their screw-dislocation-driven (SDD) bidirectional growth process. Typical products showed a bipyramid-like shape with two sets of centrosymmetric helical fringes on the top and bottom faces. Other evidence for the unique structure and growth mode include herringbone contours, spiral arms, and hollow cores. Through the manipulation of kinetic factors, including the precursor concentration, the pH value, and the amount of reductant, we were able to tune the supersaturation in the regime of SDD to layer-by-layer growth. Nanoplates with preliminary dislocations were discovered in samples with an appropriate supersaturation value and employed for investigation of the SDD growth process.

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The water quality index (WQI) has been used to identify threats to water quality and to support better water resource management. This study combines a machine learning algorithm, WQI, and remote sensing spectral indices (difference index, DI; ratio index, RI; and normalized difference index, NDI) through fractional derivatives methods and in turn establishes a model for estimating and assessing the WQI. The results show that the calculated WQI values range between 56.61 and 2,886.51. We also explore the relationship between reflectance data and the WQI. The number of bands with correlation coefficients passing a significance test at 0.01 first increases and then decreases with a peak appearing after 1.6 orders. WQI and DI as well as RI and NDI correlation coefficients between optimal band combinations of the peak also appear after 1.6 orders with R2 values of 0.92, 0.58 and 0.92. Finally, 22 WQI estimation models were established by POS-SVR to compare the predictive effects of these models. The models based on a spectral index of 1.6 were found to perform much better than the others, with an R2 of 0.92, an RMSE of 58.4, and an RPD of 2.81 and a slope of curve fitting of 0.97.