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Lithium (Li) metal is considered as a promising anode material for high‐energy batteries; yet, its practical application is hindered by uncontrolled Li dendrite growth, especially at a high rate. Herein, a dual conductive gradient V2CTx/MoO3 (DG‐V2CTx/MoO3) host that integrates electronic/ionic conductive gradients and lithiophilicity is prepared by layer‐by‐layer assembly for dendrite‐free Li anodes. Gradient LiF deriving from different amount of V2CTx endows a good ionic conductive gradient; while, MoO3 is regarded as a spacer to avoid the restacking of V2CTx, increasing space for Li deposition. The dual conductive gradients effectively optimize the current density and Li+ flux distribution at the bottom, achieving fast reduction of Li+ and a "bottom–up" Li deposition mode. Meanwhile, the lithiophilic V2CTx and MoO3 guide the homogeneous Li growth. As a result, the symmetrical half‐cells based on DG‐V2CTx/MoO3@Li anodes conduct 700 h at 5 mAh cm−2 and 20 mA cm−2. The DG‐V2CTx/MoO3@Li||LiFePO4 full‐cells maintain a capacity retention of 85.4% after 1350 cycles at 2 C. Remarkably, the DG‐V2CTx/MoO3@Li||LiNi0.6Co0.2Mn0.2O2 full‐cells can run 150 cycles with 80.6% capacity retention even at harsh conditions. The well‐adjusted materials and structures with both dual conductive gradients and lithiophilic properties will bring inspiration for novel material design of other metal batteries. [ABSTRACT FROM AUTHOR]

MEMS sensor is a new type of sensor manufactured by micro electronics and micro machining technology. Compared with traditional sensors, it has the characteristics of small size, light weight, low cost, low power consumption, high reliability, suitable for batch production, easy integration and intelligent realization. This project adopts a multi in one sensor based on MEMS principle. The sensor is a wireless passive three-axis sensor that integrates acceleration, speed, displacement, temperature, inclination and other parameters. It is very convenient to install and disassemble, and can realize the cycle monitoring of the whole wind field.

Wind speed and wind direction indicator in wind turbine is a very important component in the whole power generation system. Inaccurate or incorrect sensor signals will not only make the wind turbine inefficient, but also affect the safe operation of the wind turbine and the life of other components. After the warranty period, after the wind power plant takes over the wind power operation and maintenance, the maintenance demand of the above sensors will be greatly increased. In this project, numerical simulation is used to evaluate the status of wind speed and direction indicator, so as to automatically capture data, compare data, and generate correction coefficients.

Leaf mass per area (LMA) is a key structural parameter that reflects the functional traits of leaves and plays a vital role in simulating the material and energy cycles of plant ecosystems. In this study, vertical whorl-by-whorl sampling of LMA was conducted in a young Larix principis-rupprechtii plantation during the growing season at the Saihanba Forest Farm. The vertical and seasonal variations in LMA were analysed. Subsequently, a predictive model of LMA was constructed. The results revealed that the LMA varied significantly between different crown whorls and growing periods. In the vertical direction of the crown, the LMA decreased with increasing crown depth, but the range of LMA values from the tree top to the bottom was, on average, 30.4 g/m2, which was approximately 2.5 times greater in the fully expanded phase than in the early leaf-expanding phase. During different growing periods, the LMA exhibited an allometric growth trend that increased during the leaf-expanding phase and then tended to stabilize. However, the range of LMA values throughout the growing period was, on average, 40.4 g/m2. Among the univariate models, the leaf dry matter content (LDMC) performed well (adjusted determination coefficient (Ra2) = 0.45, root mean square error (RMSE) = 13.48 g/m2) in estimating the LMA. The correlation between LMA and LDMC significantly differed at different growth stages and at different vertical crown whorls. The dynamic predictive model of LMA constructed with the relative depth in the crown (RDINC) and date of the year (DOY) as independent variables was reliable in both the assessments (Ra2 = 0.68, RMSE = 10.25 g/m2) and the validation (absolute mean error (MAE) = 8.05 g/m2, fit index (FI) = 0.682). Dynamic simulations of crown LMA provide a basis for elucidating the mechanism of crown development and laying the foundation for the construction of an ecological process model. [ABSTRACT FROM AUTHOR]

In the photolithography process of integrated circuits （IC） manufacturing, it is desired that the photoresist resins have both smaller polydispersity index (PDI) and lower trace metal ion concentrations. The commercial environmentally stable chemical amplified photoresist (ESCAP) resins for 248 nm lithography are synthesized by free radical polymerization with PDI >1.5. Although using atom transfer radical polymerization (ATRP) can result in lower PDI, the potential of high metal ion contamination is a major concern, as the reaction initiators usually are copper‐containing compounds. In this study, copolymer of p‐acetoxy styrene and tert‐butyl acrylate [poly(AOST‐co‐TBA)] is synthesized via ATRP achieving PDI as low as 1.25. It is then purified by ion exchange with two different resins, IRC747 and A15, which are effective at removing Cu and other metal ions. This reduces the total metal ion concentration in the copolymer powder to <30 ppb with individual metal ion <6 ppb. This is the first reported ATRP synthesized ESCAP resin having both low PDI and metal ion concentrations suitable for 248 nm photoresist application. [ABSTRACT FROM AUTHOR]