基于NiCo2O4纳米片电极的非对称混合电容器

The looming global energy crisis and ever-increasing energy demands have catalyzed the development of renewable energy storage systems. In this regard, supercapacitors (SCs) have attracted widespread attention because of their advantageous attributes such as high power density, excellent cycle stability, and environmental friendliness. However, SCs exhibit low energy density and it is important to optimize electrode materials to improve the overall performance of these devices. Among the various electrode materials available, spinel nickel cobaltate (NiCo₂O₄) is particularly interesting because of its excellent theoretical capacitance. Based on the understanding that the performances of the electrode materials strongly depend on their morphologies and structures, in this study, we successfully synthesized NiCo₂O₄ nanosheets on Ni foam via a simple hydrothermal route followed by calcination. The structures and morphologies of the as-synthesized products were characterized by X-ray diffraction, scanning electron microscopy, and Brunauer-Emmett-Teller (BET) surface area analysis, and the results showed that they were uniformly distributed on the Ni foam support. The surface chemical states of the elements in the samples were identified by X-ray photoelectron spectroscopy. The as-synthesized NiCo₂O₄ products were then tested as cathode materials for supercapacitors in a traditional three-electrode system. The electrochemical performances of the NiCo₂O₄ electrode materials were studied and the area capacitance was found to be 1.26 C·cm^-2 at a current density of 1 mA·cm^-2. Furthermore, outstanding cycling stability with 97.6% retention of the initial discharge capacitance after 10000 cycles and excellent rate performance (67.5% capacitance retention with the current density from 1 to 14 mA·cm^-2) were achieved. It was found that the Ni foam supporting the NiCo₂O₄ nanosheets increased the conductivity of the electrode materials. However, it is worth noting that the contribution of nickel foam to the areal capacitance of the electrode materials was almost zero during the charge and discharge processes. To further investigate the practical application of the as-synthesized NiCo₂O₄ nanosheets-based electrode, a device was assembled with the as-prepared samples as the positive electrode and active carbon (AC) as the negative electrode. The assembled supercapacitor showed energy densities of 0.14 and 0.09 Wh·cm^-3 at 1.56 and 4.5 W·cm^-3, respectively. Furthermore, it was able to maintain 95% of its initial specific capacitance after 10000 cycles. The excellent electrochemical performance of the NiCo₂O₄ nanosheets could be ascribed to their unique spatial structure composed of interconnected ultrathin nanosheets, which facilitated electron transportation and ion penetration, suggesting their potential applications as electrode materials for high performance supercapacitors. The present synthetic route can be extended to other ternary transition metal oxides/sulfides for future energy storage devices and systems.     

Ostrowski-Taussky不等式的推广

行列式的概念是矩阵分析中的一个很基本的概念,其中一个非常重要的应用就是解线性方程组.由于行列式的概念是和矩阵特征值紧密相关的,研究行列式的一些性质可以从侧面反映出该矩阵特征值的一些性质.Ostrowski-Taussky不等式是一个关于行列式的不等式,利用矩阵极分解的概念,给出了不等式的一个新的证明,并且推广了不等式.     

冷冻法硝酸磷肥工艺中酸不溶物提纯研究

采用酸浸、磁选酸浸、水淬/研磨酸浸等不同工艺对冷冻法硝酸磷肥生产工艺中的废渣-酸不溶物进行了提纯处理,利用X射线荧光光谱仪(XRF测试)对酸不溶物提纯前后各成分含量的变化进行了分析,从中得出了不同工艺流程对酸不溶物纯度的影响,最终确定了最佳的酸不溶物处理工艺.结果表明:在酸浸实验中,盐酸酸浸效果最佳,可将酸不溶物中SiO2纯度达到82.43;;在酸浸工艺前加入磁选、水淬、研磨的工序均可有效提升酸不溶物的提纯效果;冷冻法硝酸磷肥工艺中酸不溶物最佳的提纯工艺路线为:干燥、筛分、水洗、磁选、研磨、盐酸酸浸,处理后酸不溶物中SiO2纯度达到88.92;,符合微硅粉的生产要求.     

基于NPP-VIIRS夜间灯光数据的山西省GDP空间化模拟

选取山西省为研究对象，以美国国家极轨合作仪件-可见红外成像辐射计套件（NPP-VIIRS）夜间灯光数据、GDP统计数据等为数据源，构建GDP空间化拟合模型，建立山西省GDP密度图，据此研究山西省经济的空间差异性。通过对NPP-VIIRS夜间灯光数据的空间化处理，提取灯光指数，并将其与GDP进行回归拟合，建立最佳回归模型，得到GDP密度拟合图；利用县级GDP数据进行线性纠正，从而提高GDP的模拟精度。结果表明：（1）NPP-VIIRS夜间灯光数据与GDP的相关性较高，可用于山西省GDP模拟；（2）与GDP分区建模相比，GDP整体建模的精度更高；（3）山西省GDP的空间分布整体呈由城市中心逐渐向周边辐射的特点，构成GDP过渡带。     

数据驱动计算力学研究进展

以数字孪生、人工智能为核心的大数据理念正深刻影响着第四次工业革4 命，数据驱动计算力学在此背景下应运而生并展现勃勃生机。与此同时，航5 空航天等尖端工业领域对高性能材料与结构的先进制造与安全评估提出了更6 严峻的挑战，经典计算力学已很难实现成倍缩短产品研发周期、实时跟踪产7 品信息并提供解决方案的目标。因此，发展面向高性能材料与结构的数据驱8 动计算力学正当其时且刻不容缓。本文拟通过梳理数据驱动计算力学的部分9 研究现状，探讨并浅析数据驱动计算力学的发展趋势.     

力学研究中"大数据"的启示、应用与挑战

大数据在全世界发展迅猛, 应用成效显著.大数据独特的思维和方法, 为科学研究与探索提供了全新的范式.力学研究中,高时空分辨率、多参数同步观测与高精度、大规模模拟手段的发展,为力学大数据的发展提供了契机,大数据、机器智能方法的应用正呈现快速上升趋势.本文旨在分析大数据思维方法在力学研究中的应用, 及其启示与挑战.首先从大数据资源、大数据科学及大数据技术3个层面分析了大数据的内涵及研究态势,概括了国内外政府及组织机构的大数据发展规划.而后对比分析了力学思维方法与大数据思维方法的特点,指出两者的本质区别在于数据使用方式的不同而带来的范式差异:大数据采用数据驱动模型替代力学中的偏微分方程组以描述问题,在复杂系统的分析、预测中优势显著.回顾了大数据方法在材料性能预测、材料本构建模、湍流建模、结构健康监测及试验力学等方面的最新研究进展,以及动态数据驱动与数字孪生等大数据驱动的建模模拟新范式.总结了大数据在力学研究中应用的3种方式, 即驱动已有模型改进,挖掘复杂隐含的规律, 以及替代已有的理论方法等. 最后,建议以力学研究为主体和牵引, 大数据与力学双驱动,推动大数据与力学交叉形成理论与方法突破、及学科发展新方向.      

依从者平均因果效应的统计推断

本文主要研究临床试验中出现不依从现象时依从子总体的平均因果效应的统计推断。考虑在实际服药状态是二值变量且有相关性,治疗响应变量连续取值的情形,同时考虑协变量对治疗效果有影响的情况下,给出了治疗效果参数的可识别性及近似条件极大似然估计,且构造了记分检验统计量。对特殊模型进行了模拟,结果表明与理论预期一致。