硼掺杂VO2（M）纳米棒的合成、相转变及光学特性

采用V2O5和硼酸为原材料,草酸为还原剂,在水热条件下,成功制备出硼(B)掺杂VO2(B)纳米棒,经Ar气环境退火后,得到了V1-xBxO2(M)系列样品。样品的结构、形貌和相转变温度分别用X-射线粉末衍射(XRD)仪、扫描电子显微镜(SEM)和差示扫描量热仪(DSC)等进行表征。用X-射线光电子谱(XPS)来表征样品的组份和元素的价态,样品的红外光吸收谱也被测量。结果显示,当B掺杂达到2.0at%时,V1-xBxO2(M)相的转变温度升高到75.03℃。这个升高的相转变温度可归因于B3+替代V4+引起VO6八面体的晶格畸变,以及局域晶格电子密度的降低。     

Crystal Structures,Terahertz Spectra and Dye Adsorption Performance of Three Lanthanide-bisphosphonate Complexes Containing Keggin Polyoxometalates

Three lanthanide complexes[LnL3(H2O)]PMo12O40·CH3CN(Ln = Dy3+for 1,Ln = Ho3+for 2,Ln= Lu3+for 3,L = tetraethyl ethylenediphosphonate)have been synthesized,and c...     

李代数的Poisson代数结构Ⅱ

本文研究民具有无限维中心的Toroidal李代数.通过利用其明确的生成元,确定了其上所有的非交换Poisson代数结构,从而推广了有限维中心的情形.     

PLS分析与RBF神经网络耦合环境模型

鉴于城市大气环境质量受到诸多复杂因素影响,且各因素间存在多重相关性,本文将偏最小二乘(PLS)分析与人工神经网络径向基网络(RBF)耦合,建立偏最小二乘径向基神经网络模型(PLSRBF),应用于贵阳大气环境质量的检验和预测。实例表明:PLSRBF模型可对原多自变量模型进行降维简化,并可有效提取解释变量信息,防止信息丢失,且具有较强的拟合能力。     

MILD煤粉燃烧湍流与化学反应相互作用的数值分析

采用计算流体动力学(CFD)数值模拟方法分析了湍流与化学反应相互作用下MILD煤粉燃烧的微观特征。比较了涡耗散模型(EDM模型)和涡耗散概念模型(EDC模型)对MILD煤粉燃烧的影响,两者得到的速度场、温度场、烟气成分等结果与实验结果符合较好.在此基础上分析了MILD煤粉燃烧湍流和化学反应的微观特征尺度,发现采用EDC模型能更准确地反映MILD煤粉燃烧的微观特征,即山于强烈的烟气内部再循环导致的高湍流混合和烟气稀释后低氧浓度下的缓慢化学反应.     

Trace Distance of Remote State Preparation Through Noisy Channels

In this paper, we study remote state preparation (RSP) by w state through noisy channels. The trace distance is used to describe how close the original state is to the output state. Studies show the trace distance is a function of decohenrence rates and angles of the state to be prepared. At the same time, we investigate the influence of different types of noises on the trace distance and find the various types of noises have different degrees of influence on the trace distance for a definite qubit. We also study changes of the trace distance against polar and azimuthal angles.     

半群OCK_n的理想的极大子半群

设X_n={1,2,…,n}并赋予自然数序,OCK_n是X_n上的具有核连续的保序变换半群.将考虑OCK_n的理想OCK(n,r)={α∈OCK_n:|imα|≤r}(3≤r≤n-1),并得到了OCK(n,r)的极大子半群的完全分类.     

Multi-granularities capture interaction information for text matching accuracy enhancement

Modeling and Matching texts is a critical issue in natural language processing (NLP) tasks. In order to improve the accuracy of text matching, multi-granularities capture matching features (MG-CMF) model was proposed. The proposed model used convolution operations to construct the representation of text under multiple granularities, used max-pooling operations to filter more reasonable text representations and built a matching matrix at different granularities. Then, the convolution neural network (CNN) was used to capture the matching information in each granularity. Finally, the captured matching features were input into the fully connected neural network to obtain the matching similarity. By making some experiments, the results indicate that the MG-CMF model not only gets multiple granularity representations of sentences but also can obtain matching information from multiple granularities of sentences better than the other text matching models.     

(HAlNH)n(n=1～6)簇的结构、红外光谱和热力学性质的研究

用自洽场理论(HF)和密度泛函理论(DFT)的B3LYP方法,在6-31G水平上研究了HAlNH的低聚物(HAlNH)~n(n=1～6)簇的几何构型、电子结构、红外光谱和化学热力学性质,并比较了(HAlNH)~n和(ClAlNH)~n两种低聚物对应结构中化学键强弱,分析了引起(AlN)~n骨架结构发生变化的原因。结果表明,(HAlNH)~n簇的基态结构为C~s(n=1),D~2~h(n=2),D~3~h(n=3),T~d(n=4),C~s(n=5)和D~3~d(n=6)对称点群。HAlNH基态结构中,Al-N键是三重键。在D~2~h(n=2)和D~3~h(n=3)结构中,所有Al-N键均为二重键。在T~d(n=4)和D~3~d(n=6)中,Al-N键为正常单键,而在C~s(n=5)结构中含有三种Al-N键：单键、双键和混合键。振动频率计算表明,结构a～f均为基态稳定结构。热力学计算给出的稳定性顺序为：f>d>e>c>b>a。