基于纸喷雾离子化衍生质谱法快速检测PM2.5中的醌污染物

醌类化合物是PM2.5中的一类有害物质。本研究建立了纸喷雾离子化衍生质谱法快速测定PM2.5中的醌类污染物。通过衍生化反应在醌化合物中引入氨基，提高醌在纸喷雾中的离子化效率。随后对衍生化试剂种类、电压、喷雾溶剂种类等反应条件进行优化。在最优实验条件下，采用内标法定量分析1,4-苯醌、甲基对苯醌、1,4-萘醌和1,4-蒽醌，4种化合物均呈现较好的线性关系，其检出限分别为4.49、20.89、0.13、0.17 ng。利用该方法分析PM2.5实际样品中的萘醌和蒽醌，均获得了较好的定性和定量结果。     

Effect of LiTFSI and LiFSI on Cycling Performance of Lithium Metal Batteries Using Thermoplastic Polyurethane/Halloysite Nanotubes Solid Electrolyte

All-solid-state lithium batteries(ASSLB) are promising candidates for next-generation energy storage devices.Nevertheless,the large-scale commercial application of high energy density AS S LB with the polymer electrolyte still faces challenges.In this study,a thin solid polymer composite electrolyte(SPCE) is prepared through a facile and cost-effective strategy with an infiltration of thermoplastic polyurethane(TPU),lithium salt(LiTFSI or LiFSI),and halloysite nanotubes(HNTs) in a porous framework of polyethylene separator(PE)(TPU-HNTs-LiTFSI-PE or TPU-HNTs-LiFSI-PE).The composition,electrochemical performance,and especially the effect of anions(TFSI~-and FSI~-) on cycling performance are investigated.The results reveal that the flexible TPU-HNTs-LiTFSI-PE and TPU-HNTs-LiFSI-PE with a thickness of 34 μm exhibit wide electrochemical windows of 4.9 and 5.1 V(vs.Li+/Li) at 60℃,respectively.Reduction in FSI~-tends to form more LiF and sulfur compounds at the interface between TPU-HNTs-LiFSI-PE and Li metal anode,thus enhancing the interfacial stability.As a result,cell composed of TPU-HNTs-LiFSI-PE exhibits a smaller increase in interfacial resistance of solid electrolyte interphase(SEI) with a distinct decrease in charge-transfer resistance during cycling.Li|Li symmetric cell with TPU-HNTs-LiFSI-PE could keep its stable overpotential profile for nearly 1300 h with a low hysteresis of approximately39 mV at a current density of 0.1 mA cm~(-2),while a sudden voltage rise with internal cell impedance-surge signals was observed within 600 h for cell composed of TPU-HNTs-LiTFSI-PE.The initial capacities of NCMITPU-HNTs-LiTFSIPEILi and NCMITPU-HNTs-LiFSI-PEILi cells were 149 and 114 mAh g~(-1),with capacity retention rates of 83.52% and89.99% after 300 cycles at 0.5 C,respectively.This study provides a valuable guideline for designing flexible SPCE,which shows great application prospect in the practice of ASSLB.     

气藏平均地层压力跟踪计算新方法

平均地层压力是产能评价和动态分析的基础，准确、快速获取平均地层压力对高效开发气藏意义重大。基于地层压力随时间变化的规律，分析了平均地层压力的变化规律。研究结果表明：平均地层压力等效点仅随时间发生改变，平均地层压力的下降速率等于或者近似等于井底流压的下降速率。从封闭弹性驱动气藏的物质平衡方程出发，考虑偏差系数和井底流压随平均地层压力的变化，推导建立了平均地层压力跟踪计算新方法，根据生产数据可迭代计算平均地层压力。方法验证结果显示，采气速度和采出程度共同影响模型的计算结果。应用实例表明，跟踪计算法与压力恢复试井和物质平衡法之间的相对误差均较小，满足工程计算精度要求，且跟踪计算法不需依托生产测试数据，节约了测试费用，避免了测试占产。     

Direct View on the Origin of High Li+ Transfer Impedance in All-Solid-State Battery

Large interfacial resistance plays a dominant role in the performance of all-solid-state lithium-ion batteries. However, the mechanism of interfacial resistance has been under debate. Here, the Li⁺ transport at the interfacial region is investigated to reveal the origin of the high Li⁺ transfer impedance in a LiCoO₂(LCO)/LiPON/Pt all-solid-state battery. Both an unexpected nanocrystalline layer and a structurally disordered transition layer are discovered to be inherent to the LCO/LiPON interface. Under electrochemical conditions, the nanocrystalline layer with insufficient electrochemical stability leads to the introduction of voids during electrochemical cycles, which is the origin of the high Li⁺ transfer impedance at solid electrolyte-electrode interfaces. In addition, at relatively low temperatures, the oxygen vacancies migration in the transition layer results in the formation of Co₃O₄ nanocrystalline layer with nanovoids, which contributes to the high Li⁺ transfer impedance. This work sheds light on the mechanism for the high interfacial resistance and promotes overcoming the interfacial issues in all-solid-state batteries.     

Enhanced electrochemical performance of LiNi0.8Co0.1Mn0.1O2 via titanium and boron co-doping

Titanium and boron are simultaneously introduced into LiNi_0.8Co_0.1Mn_0.1O₂ to improve the structural stability and electrochemical performance of the material. X-ray diffraction studies reveal that Ti⁴⁺ ion replaces Li⁺ ion and reduces the cation mixing; B³⁺ ion enters the tetrahedron of the transition metal layers and enlarges the distance of the [LiO₆] layers. The co-doped sample has spherical secondary particles with elongated and enlarged primary particles, in which Ti and B elements distribute uniformly. Electrochemical studies reveal the co-doped sample has improved rate performance (183.1 mAh·g^-1 at 1 C and 155.5 mAh·g^-1 at 10 C) and cycle stability (capacity retention of 94.7% after 100 cycles at 1 C). EIS and CV disclose that Ti and B co-doping reduces charge transfer impedance and suppresses phase change of LiNi_0.8Co_0.1Mn_0.1O_2.     

Molecular fingerprint and machine learning to accelerate design of high-performance homochiral metal–organic frameworks

Computational screening was employed to calculate the enantioseparation capabilities of 45 functionalized homochiral metal–organic frameworks (FHMOFs), and machine learning (ML) and molecular fingerprint (MF) techniques were used to find new FHMOFs with high performance. With increasing temperature, the enantioselectivities for (R,S)-1,3-dimethyl-1,2-propadiene are improved. The “glove effect” in the chiral pockets was proposed to explain the correlations between the steric effect of functional groups and performance of FHMOFs. Moreover, the neighborhood component analysis and RDKit/MACCS MFs show the highest predictive effect on enantioselectivities among the four ML classification algorithms with nine MFs that were tested. Based on the importance of MF, 85 new FHMOFs were designed, and a newly designed FHMOF, NO₂-NHOH-FHMOF, with high similarity to the optimal MFs achieved improved chiral separation performance, with enantioselectivities of 85%. The design principles and new chiral pockets obtained by ML and MFs could facilitate the development of new materials for chiral separation.     

基于全局优化与深度学习的条形码识别方法

提出了一种在深度神经网络的基础上结合全局优化方法的条形码识别算法,利用卷积循环网络提取出条码中各字元的特征并进行分类,较传统方法具有更强的适应性与泛化能力,再进一步结合全局优化的方法,以达到充分利用条码结构性先验信息的目的,能显著提升方法的效果,尤其是将全局优化方法引入到神经网络中进行端到端学习,不仅保持了两者的优势同时还进一步提高了识别精度.实验结果证明了所提方法的有效性,达到约99.48％的识别精度,超越了传统的图像处理方法.     

超临界机组发生FAC的因素及相互关系分析

为了减轻因流动加速腐蚀(FAC)引起的锅炉结垢加速、汽水系统管道厚度减小甚至爆裂现象，对超临界机组发生流动加速腐蚀的机理及其主要影响因素进行了研究，并讨论了管壁内表面粗糙度、蒸汽含汽率、pH值、溶氧量对FAC的影响，以及温度与pH值、温度与流速、pH值与溶解氧量、溶解氧量与氢电导率等影响因素之间的相互作用关系，最后结合实际电厂的运行数据验证了分析结果。研究表明：减小工质流速、管壁粗糙度和氢电导率，增大给水的pH值和溶解氧含量可以使FAC的腐蚀速率减小，超临界加氧处理时pH值应在8.9～9.2之间，溶解氧量范围为45～100μg/L,氢电导率的期望值在0.1μS/cm以下。由于各影响因素之间的作用十分复杂，本文只给出了大致范围和趋势，并未给出准确数据。