Azobenzene mesogens mediated preparation of Sn S nanocrystals encapsulated with in-situ N-doped carbon and their enhanced electrochemical performance for lithium ion batteries application

In this work,azobenzene mesogen-containing tin thiolates have been synthesized,which possess ordered lamellar structures persistent to higher temperature and serve as liquid crystalline precursors.Based on the preorganized tin thiolate precursors,Sn S nanocrystals encapsulated with in-situ N-doped carbon layer have been achieved through a simple solventless pyrolysis process with the azobenzene mesogenic thiolate precursor served as Sn,S,N,and C sources simultaneously.Thus prepared nanocomposite materials as anode of lithium ion batteries present a large specific capacity of 604.6 m Ah·g^（-1）at a current density of 100 m A·g^（-1）,keeping a high capacity retention up to 96% after 80 cycles,and display high rate capability due to the synergistic effect of well-dispersed Sn S nanocrystals and N-doped carbon layer.Such encouraging results shed a light on the controlled preparation of advanced nanocomposites based on liquid crystalline metallomesogen precursors and may boost their novel intriguing applications.

Enhancement of the polynomial functions response surface model for real-time analyzing ozone sensitivity

Quantification of the nonlinearities between ambient ozone(O3)and the emissions of nitrogen oxides(NOx)and volatile organic compound(VOC)is a prerequisite for an effective O3 control strategy.An Enhanced polynomial functions Response Surface Model(Epf-RSM)with the capability to analyze O3-NOx-VOC sensitivities in real time was developed by integrating the hill-climbing adaptive method into the optimized Extended Response Surface Model(ERSM)system.The Epf-RSM could single out the best suited polynomial function for each grid cell to quantify the responses of O3 concentrations to precursor emission changes.Several comparisons between Epf-RSM and pf-ERSM(polynomial functions based ERSM)were performed using out-of-sample validation,together with comparisons of the spatial distribution and the Empirical Kinetic Modeling Approach diagrams.The comparison results showed that Epf-RSM effectively addressed the drawbacks of pf-ERSM with respect to overfitting in the margin areas and high biases in the transition areas.The O3 concentrations predicted by Epf-RSM agreed well with Community Multi-scale Air Quality simulation results.The case study results in the Pearl River Delta and the north-western area of the Shandong province indicated that the O3 formations in the central areas of both the regions were more sensitive to anthropogenic VOC in January,April,and October,while more NOx-sensitive in July.