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本文利用红外光解离光谱研究了第三族金属氧化物离子对二氧化碳分子的转化机制. 研究表明,对于[ScO(CO2)n]+体系,在n≤4时,形成了溶剂化结构;在n=5时,形成了碳酸盐结构,实现了二氧化碳的转化. 对于[YO(CO2)n]+体系,需要4个二氧化碳分子就可以实现二氧化碳的转化. 而在[YO(CO2)n]+体系中,只发现了溶剂化结构,没有观察到碳酸盐结构. 理论计算表明,[YO(CO2)n]+体系拥有最小的溶剂化结构向碳酸盐结构转化能垒,[LaO(CO2)n]+体系拥有最大的溶剂化结构向碳酸盐结构转化能垒. 本文从分子水平揭示了不同金属氧化物离子对二氧化碳分子转化的影响规律. 相似文献
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Motoyoshi Nakano Yudai Ishimur Riki Hott Daiki Hebiguchi Toshiaki Nagat Fuminori Misaizu 《化学物理学报》2019,32(2):193-199
本文通过离子迁移质谱法研究了氧化钠团簇阳离子(NanOm+,n≤11)的稳定结构. 质谱结果表明化学计量组成Na(Na2O)(n-1)/2+ (n=3、5、7、9和11)系列是稳定的,并且NaO(Na2O)(n-1)/2+ (n=5、7、9和11)系列作为二级稳定系列. 为了获得这些团簇离子的结构,通过离子迁移率测量实验测定离子和氦缓冲气体之间的碰撞截面. 同时计算了这些组合物优化结构的理论碰撞截面. 结果表明,Na(Na2O)(n-1)/2+和NaO(Na2O)(n-1)/2+的结构除了n=9之外,其它具有相似结构框架. Na(Na2O)(n-1)/2+所有的化合键位于钠和氧之间. 另一方面,NaO(Na2O)(n-1)/2+中除了Na-O键之外,还存在一个O-O氧键,表明NaO(Na2O)(n-1)/2+具有过氧化物离子(O22-)作为Na(Na2O)(n-1)/2+的氧化物离子(O2-) 的替代物. Na(Na2O)(n-1)/2+和NaO(Na2O)(n-1)/2+两种稳定系列都是闭壳组合物. 这些闭壳特征对氧化钠簇阳离子的稳定性具有强烈影响. 相似文献
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本文利用红外光解离光谱研究了一价钴阳离子与二氧化碳之间的相互作用. 通过密度泛函理论计算得到[Co(CO2)n]+团簇的几何结构,并且模拟了它们的振动光谱与实验数值进行比较. 研究结果表明,在[Co(CO2)n]+(n=2∽6)团簇中,钴阳离子通过电四极矩静电作用以端点结合的方式与二氧化碳中的氧原子结合在一起. 团簇的红外光谱都集中在二氧化碳反对称伸缩的波数附近,并且随着团簇尺寸的变化出现蓝移,最后把[Co(CO2)n]+的红外光解离光谱与稀有气体贴附的[Co(CO2)n]+-Ar的红外光解离光谱进行了比较. 相似文献
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本文利用激光诱导荧光技术对AgO分子C2∏-X2∏(0,0)带光谱在∽0.02 cm-1分辨率水平开展了高分辨研究. 在超声射流条件下利用银针电极对O2/Ar混合气高压放电制备AgO分子,利用自行研制的窄线宽单纵模光参量振荡器作为可调谐激光光源,实验记录了同位素分辨的107Ag16O和109Ag16O分子C2∏-X2∏(0,0)带的高分辨光谱. 通过对实验光谱的转动分析获得了两个同位素分子的精确光谱常数,其中107Ag16O分子C2∏态常数为首次实验测定. 结合文献和理论计算,实验观测的C2∏态自旋-轨道耦合效应很可能来自于与四重解离态4Σ-或4∏的态混合. 相似文献
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MgF自由基被认为是适用于直接激光冷却的候选分子之一. 本文利用激光诱导荧光技术研究了MgF A2π-X2Σ+电子跃迁系统的转动分辨光谱. 在超声射流膨胀条件下利用两个镁针对SF6/Ar气体混合放电产生MgF自由基. 在348∽370 nm范围内,实验记录了属于Δv=0,±1三个序的19个振动带. 通过对实验光谱的转动分析,确定了X2Σ+和A2π态的精确光谱常数. 利用实验结果结合和Rydberg-klein-rees方法计算了包括Franck-Condon因子(FCFs)在内的光谱常数. 实验结果和理论计算的FCFs之间存在显著差异,表明FCFs几乎不依赖于A2π态自旋-轨道耦合效应. 本文确定的势能曲线和FCFs为MgF分子激光冷却方案的理论模拟提供了必要的光谱数据. 相似文献
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综合利用拉曼光谱和密度泛函理论研究了乙醇在四氯化碳、二硫化碳溶液中乙醇构象异构体的布居. 首先确定了trans和gauche构象乙醇在OH伸缩振动拉曼光谱中的归属,然后结合理论计算的拉曼散射截面估计了两个异构体的能级差。 可以看出在四氯化碳和二硫化碳中trans乙醇更稳定。通过分析不同温度的拉曼光谱,发现范霍夫方程在这里并不适用. 利用玻尔兹曼分布律和理论拉曼散射截面,发现了两个异构体的能级差随着温度升高而增大,这反映了溶剂与乙醇之间越弱的分子间相互作用更有利于trans构象乙醇的布居。 相似文献
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《化学物理学报》2018,(4)
分子动力学(MD)模拟可以很好地用于揭示蛋白质等生物大分子体系在原子尺度的结构及功能的关系.分子动力学模拟通常产生海量的描述分子在模拟中运动的数据,包含很多模拟轨迹以及随时间演化的各个原子的坐标和速度等.为了从这些海量数据中获得体系的分子机制,需要发展并利用聚类算法来将这些海量数据进行归类,聚类算法通常将具有某些相似度的构象聚成一类,这些相似度可以分为两类,几何相似度以及动力学相似度.对应地,用于分析分子动力学模拟的聚类算法通常可以分为两大类:几何聚类及动力学聚类.本文列举了一系列常用的用于分子动力学模拟的聚类算法包括分裂算法,凝聚算法(单连锁,完全连锁,平均连锁,质心连锁以及Ward连锁),中心算法(K-Means,KMedoids,K-Centers及APM),密度算法(邻居算法,DBSCAN,密度-峰及Robust-DB算法),谱算法(PCCA, PCCA+)等.本文讨论了几何分类和动力学分类的不同点以及不同算法的性能.另外注意到并不存在某一个适用于所有MD数据的聚类算法.对于某个特定体系,选择一个合适的聚类算法取决于聚类的目的,MD构象系综的内在性质等.因此,本文的一个要点也在于介绍每个聚类算法的优缺点.期望通过本文,能够指导读者在MD模拟中选择一个合适的聚类算法. 相似文献
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We proposed a method to find the community structure in a complex network by density-based clustering. Physical topological distance is introduced in density-based clustering for determining a distance function of specific influence functions. According to the distribution of the data, the community structures are uncovered. The method keeps a better connection mode of the community structure than the existing algorithms in terms of modularity, which can be viewed as a basic characteristic of community detection in the future. Moreover, experimental results indicate that the proposed method is efficient and effective to be used for community detection of medium and large networks. 相似文献
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In practical engineering applications, the vibration signals collected by sensors often contain outliers, resulting in the separation accuracy of source signals from the observed signals being seriously affected. The mixing matrix estimation is crucial to the underdetermined blind source separation (UBSS), determining the accuracy level of the source signals recovery. Therefore, a two-stage clustering method is proposed by combining hierarchical clustering and K-means to improve the reliability of the estimated mixing matrix in this paper. The proposed method is used to solve the two major problems in the K-means algorithm: the random selection of initial cluster centers and the sensitivity of the algorithm to outliers. Firstly, the observed signals are clustered by hierarchical clustering to get the cluster centers. Secondly, the cosine distance is used to eliminate the outliers deviating from cluster centers. Then, the initial cluster centers are obtained by calculating the mean value of each remaining cluster. Finally, the mixing matrix is estimated with the improved K-means, and the sources are recovered using the least square method. Simulation and the reciprocating compressor fault experiments demonstrate the effectiveness of the proposed method. 相似文献
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Grouping the objects based on their similarities is an important common task in machine learning applications. Many clustering methods have been developed, among them k-means based clustering methods have been broadly used and several extensions have been developed to improve the original k-means clustering method such as k-means ++ and kernel k-means. K-means is a linear clustering method; that is, it divides the objects into linearly separable groups, while kernel k-means is a non-linear technique. Kernel k-means projects the elements to a higher dimensional feature space using a kernel function, and then groups them. Different kernel functions may not perform similarly in clustering of a data set and, in turn, choosing the right kernel for an application could be challenging. In our previous work, we introduced a weighted majority voting method for clustering based on normalized mutual information (NMI). NMI is a supervised method where the true labels for a training set are required to calculate NMI. In this study, we extend our previous work of aggregating the clustering results to develop an unsupervised weighting function where a training set is not available. The proposed weighting function here is based on Silhouette index, as an unsupervised criterion. As a result, a training set is not required to calculate Silhouette index. This makes our new method more sensible in terms of clustering concept. 相似文献
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ABSTRACTIt is essential to understand the intrinsic stability of the gold-thiolate clusters, which present extensive potential applications in many fields such as the catalysis, biomedicines and molecular machines. The electronic structures and aromaticity indexes of a series of Aum(SH)n (m, n?=?5–12) were comprehensively investigated through energetic, vibrational, magnetic, and electronic density properties, which are highly sensitive to the size and topological structure of the cluster. Generally, computational results of energy gap between the frontier molecular orbitals, normalized atomization energy (NAE), and electron localization function (ELF)-σ values exhibit the odd-even effect, in which clusters with the even number of free valence electrons, being reflected by the value of (m–n), possess relatively higher stability than the odd one. However, it is difficult to describe the stability of cluster with the sophisticated three-dimensional structure through one single aromaticity index such as the nucleus-independent chemical shift (NICS) value. Principal component analysis and clustering analysis of the calculation results of Aum(SR)n clusters suggest that the value of (m–n) and the Au4 unit are important for predicting the stability of the Au clusters. 相似文献
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In many cell types, calcium is released from internal stores through calcium release channels upon external stimulation (e.g., pressure or receptor binding). These channels are clustered with a typical cluster size of about 20 channels, generating stochastic calcium puffs. We find that the clustering of the release channels in small clusters increases the sensitivity of the calcium response, allowing for coherent calcium responses at signals to which homogeneously distributed channels would not respond. 相似文献
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提出了结合稀疏编码和空间约束的红外图像聚类分割新算法, 在稀疏编码的基础上融合聚类算法, 扩展了传统的基于K-means聚类的图像分割方法. 结合稀疏编码的聚类分割算法能有效融合图像的局部信息, 便于利用像素之间的内在相关性, 但是对于分割会出现过分割和像素难以归类的问题.为此, 在字典的学习过程中, 将原子的聚类算法引入其中, 有助于缩减字典中原子所属类别的数目, 防止出现过分割; 考虑到像素及其邻域像素具有类别属性一致性的特点, 引入了空间类别属性约束信息, 并给出了一种交替优化算法. 联合学习字典、稀疏系数、聚类中心和隶属度, 将稀疏编码系数同原子对聚类中心的隶属程度相结合, 构造像素归属度来判断像素所属的类别. 实验结果表明, 该方法能够有效提高红外图像重要区域的分割效果, 具有较好的鲁棒性.
关键词:
图像分割
稀疏编码
聚类
空间约束 相似文献
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在传统遗传算法的基础上提出了单母体遗传算法(single-parent genetic algorithm, SPGA),通过对母体团簇实施两种不同的变异操作对结构进行优化,给出了分子团簇结构优化的算法实现. 结合TIP3P模型势函数,研究了水分子团簇(H2O)n(n≤14)的稳定结构. 优化结构和已有理论及实验结果一致. 计算结果表明当n<8时,平均结合能随n增加较快;当n≥8时有小的起伏. n=4,8,10,12的团簇结构具有较高对称性,比较稳定.
关键词:
单母体遗传算法
水分子团簇
结构优化 相似文献