Effect of Silane Flow Rate on Structure and Corrosion Resistance of Ti-Si-N Thin Films Deposited by a Hybrid Cathodic Arc and Chemical Vapour Process

Ti-Si-N thin flms with different silicon contents are deposited by a cathodic arc technique in an Ar＋N2＋SiH4 mixture atmosphere. With the increase of silane flow rate, the content of silicon in the Ti-Si-N films varies from 2.0 at. % to 12.2 at. %. Meanwhile, the cross-sectional morphology of these films changes from an apparent columnar microstructure to a dense fine-grained structure. The x-ray diffractometer （XRD） and x-ray photoelectron spectroscopy （XPS） results show that the Ti-Si-N film consists of TiN crystallites and SiNx amorphous phase. The corrosion resistance is improved with the increase of silane flow rate. Growth defects in the films produced play a key role in the corrosion process, especially for the local corrosion. The porosity of the films decreases from 0.13%to 0.00032% by introducing silane at the flow rate of 14sccm.     

单模激光Lorenz系统反同步控制研究

提出了一种实现异结构混沌系统反同步控制的方法。根据Lyapunov 稳定性理论给出控制器的结构。以单模激光Lorenz系统和Rossler系统为例,验证了这种控制器的有效性。进一步研究了不确定混沌系统的反同步,并以不确定单模激光Lorenz系统和Rossler系统为例,实现了混沌反同步控制,同时系统中不确定参数得到识别。仿真模拟结果验证了这种方法的有效性。设计的反同步控制方法可用于任意混沌系统,具有一定的普适性。     

GPU-Accelerated Large-Scale Excited-State Simulation Based on Divide-and-Conquer Time-Dependent Density-Functional Tight-Binding

The present study implemented the divide-and-conquer time-dependent density-functional tight-binding (DC-TDDFTB) code on a graphical processing unit (GPU). The DC method, which is a linear-scaling scheme, divides a total system into several fragments. By separately solving local equations in individual fragments, the DC method could reduce slow central processing unit (CPU)-GPU memory access, as well as computational cost, and avoid shortfalls of GPU memory. Numerical applications confirmed that the present code on GPU significantly accelerated the TDDFTB calculations, while maintaining accuracy. Furthermore, the DC-TDDFTB simulation of 2-acetylindan-1,3-dione displays excited-state intramolecular proton transfer and provides reasonable absorption and fluorescence energies with the corresponding experimental values. © 2019 Wiley Periodicals, Inc.     

Hydrangea‐like NiCo‐based Bimetal‐organic Frameworks,and their Pros and Cons as Supercapacitor Electrode Materials in Aqueous Electrolytes

Hydrangea‐like NiCo‐based bimetal‐organic frameworks (NiCo‐MOF) are synthesized in DMF‐EtOH solution via a solvothermal method, using 4,4′‐biphenyldicarboxylic acid as a ligand. NiCo‐MOF having a highest capacity of 1056.6 F · g^–1 at 0.5 A · g^–1 and 457.7 F · g^–1 even at 10 A · g^–1 is achieved at a Ni/Co/BPDC molar ratio of 1:1:1, a temperature of 170 °C and a reaction time of 12 hours. It exhibits secondary 3D microsphere structures assembled by primary 2D nanosheet structures, good crystalline structure and good thermal stability below 350 °C in air. All the electrochemical data show that NiCo‐MOF has the pros and cons as supercapacitor electrode materials in aqueous electrolytes. On the one hand, NiCo‐MOF has a high capacity even at a high current density, low internal resistance, charge‐transfer resistance and ion diffusion impendence, owing to the ordered coordination structure, 2D nanosheet structure and 3D assembled microsphere structure of NiCo‐MOF. On the other hand, the cycling stability and rate capability are not ideal enough due to the hydrolysis of coordination bonds in aqueous electrolytes, especially, in alkaline solution. The good dispersion and high electrochemical activity of metal ions bring a high capacity for NiCo‐MOF, but they result in the poor stability of NiCo‐MOF. In the future work, finding a suitable organic electrolyte is an effective way to enhance the cycling stability of NiCo‐MOF as well as deriving more stable skeleton materials from NiCo‐MOF.     

基于Adaptive Elastic Net方法的近红外光谱建模技术

当近红外光谱信息远远大于样本量时,对光谱信息进行自动变量选择进而建立光谱与微量成分含量之间的稀疏线性模型重要且具有挑战性。针对聚苯醚生产过程中微量成分邻甲酚难以测量的问题,将变量选择方法Adaptive Elastic Net用于建立近红外光谱与邻甲酚含量之间的定量校正模型,并将其模型性能与ElasticNet方法进行对比。在变量数目远远大于样本量的情形下,ElasticNet方法虽可以实现变量选择,但由于其系数估计不具备Oracle性质,使得模型的可解释性和预测精度受到影响,而Adaptive Elastic Net方法通过对L1惩罚项施加自适应权重从而很好的解决了上述问题并提高了模型性能。为了验证Adaptive Elastic Net方法的模型性能指标,用最终被选中的自变量数目来评价模型复杂度;利用复相关系数R2来评价模型的可解释性,利用平均相对预测误差MRPE(mean relative prediction error)和预测相关系数R_p来评价模型的预测精度。Elastic Net方法建立的模型性能指标为：NSIV=529,R2=0.96, MRPE=3.22％, R_p=0.97; Adaptive Elastic Net方法的性能指标为：NSIV=139, R2=0.99, MRPE=2.00％, R_p=0.99。结果表明：Adaptive Elastic Net所建立模型的性能指标优于Elastic Net方法,可以得到更加简单且具有较强可解释性和较高预测精度的稀疏线性模型。     

基于互信息熵-近红外光谱的过程模式故障检测

近红外光谱分析在工业过程故障检测方面具有独特的优势,是一种准确且高效的方法。结合互信息熵和传统的主成分分析,对近红外光谱特征信息进行提取,通过构建过程的模式来刻画工业过程的运行状态。利用近红外光谱数据,从有机分子含氢基团振动信息中获取工业系统的过程模式,从微观分子层面探索提高工业过程故障检测准确率的有效方法,结合贝叶斯统计学习技术,提出了基于近红外光谱数据的工业过程故障检测技术。针对近红外光谱信息量丰富,谱带较宽,特征性不强的特点,首先对工业过程不同运行状态下的近红外光谱吸光度数据进行一阶导数预处理,采用主成分分析法（principal component analysis,PCA）压缩光谱数据量,扩大不同运行状态下光谱特征信息的差异性,提取光谱的内部特征信息。然后采用互信息熵（mutual information entropy,MIE）作为光谱特征信息相关性度量函数,基于最小冗余最大相关算法进一步减少光谱特征信息间的冗余并最大化光谱特征信息与类别的相关性,弥补了PCA无监督特征波长选择的不足,提出一种基于PCA-MIE的过程模式构建方法,获得的过程模式子集更紧凑更具类别表现力。再利用贝叶斯统计学习算法,根据后验概率对构建的模式子集进行决策,判别生产过程的正常状态和故障状态。由于过程模式子集结合了PCA浓聚方差的优势和互信息熵相关性测度的特征信息选择方法,蕴含了更多的近红外光谱的本质信息与内在规律,从而更能刻画工业过程的运行状态。接着,设置测试准确率TA作为评估标准,用以评价故障检测方法的性能效果。最后利用某化工厂提供的原油脱盐脱水过程近红外光谱数据对所提方法进行验证,并与传统近红外光谱特征信息提取方法PCA和MIE方法性能进行对比分析,结果表明基于PCA-MIE的过程模式故障检测方法几乎在所有维数子集上性能都优于其他两种方法,在特征维数为18维时获得最高的准确率94. 6%,证明了方法的优越性。     

表面活性剂溶胀胶束：性能及应用

溶胀胶束是表面活性剂胶束增溶其它物质后使胶束膨胀的一种胶束状态,因其能显著提高难溶性物质的溶解度而备受关注。针对近年来对溶胀胶束的研究进展,综述了溶胀胶束的最大增溶量、增溶过程以及增溶后形貌尺寸的变化等问题,总结了影响胶束增溶作用的因素,厘清了溶胀胶束与微乳液的异同,介绍了溶胀胶束的应用,展望了其应用前景与发展方向。     

H型群上的非线性Liouville定理

对H型群上的次线性方程△Gu+up=0进行了研究,其中△G是对应的sublaplace算子.通过将移动平面方法推广到H型群上,证明了在一定条件下的p和函数u,次线性方程△Gu+up=0的唯一解是u≡0.     

托卡马克聚变堆堆芯参数时空分布的数值研究

本文描述包括聚变α粒子、高能束注入及回旋辐射的较完整的托卡马克聚变堆堆芯一维输运模型和程序。所得到的粒子、磁场及能量时空分布是合理的,与实验定标律外推及INTOR预计值一致。借助数值分析了α粒子能量利用及分配、束注入特性、等离子体约束、杂质和初边条件对结果的影响,可供设计准稳态热核堆芯时参考。