【作者】 林伟琦；

【导师】 俞汝勤； 沈国励；

【作者基本信息】 湖南大学 ， 分析化学， 2006， 博士

【摘要】 本论文通过对多变量图像解析和定量结构与活性相关性研究这两个领域中的一些难点问题的研究,提出了几种新型的化学计量学算法。1.提出了一种结合空间相关性的多变量图像分割新方法——空间导向凝聚法。该方法核心思想在于将光谱相似性较大且空间最相近的点分割为一个聚类,同时引进了一个F统计量作为空间导向凝聚聚类的终止准则,从而可逐步实现全图像的分割。而且,该算法可以自动鉴定多变量图像中的聚类数及异常点。运用该方法成功处理了棕榈氯霉素I、II晶型混合物药片激光共聚焦拉曼成像分析数据。结果表明,即使在棕榈氯霉素I、II晶型拉曼光谱差别极为细微的情况下,该多变量图像分割方法仍可以有效鉴定棕榈氯霉素I、II晶型的分布与含量。这表明该方法可望为药剂的同质多晶分析、配方分析提供一个新的有效工具。2.基于纯变量分辨算法的多变量图像分割与拉曼成像技术相结合,对磺胺类药物的实验室制药片与成品药片进行了分析。实验结果表明,所提出的技术可以明确辨别药片中的每种有效成分,并能定量可视化这些有效成分的空间分布。这项技术有望为药品的生产过程提供快速的无损分析,如提高药品质量,进行更好的配方设计和更好的了解药品的制造过程。3.将基于空间导向凝聚法的多变量图像分割新方法与拉曼成像分析相结合用于分析各种不同组成比例的可互容和不可互容高密度聚乙烯(HDPE)和聚邻苯二甲酸乙二醇酯(PET)共混聚合物的两组分空间非均相性分布情况,并通过扫描电镜验证了分析结果。分析结果说明了马来酸酐能够显著改善HDPE/PET的共混物组分间的分散度和粘度。加入仅仅0.5 wt%的马来酸酐,就能获得可互容的HDPE/PET共混物,其亚相比不互容共混物要小得多,而相界面变得更加模糊。这都表明马来酸酐的加入产生了可互容共混物,其化学组成上的均相性程度大大提高了。4.提出了变量分区组合算法,该算法是目前化学计量学研究中处于主导地位的隐变量方法的进一步推广。它利用模型的优良性,结合离散粒子群算法进行变量分区,在多个优化的变量子集中分别提取PLS成分,同区变量所提取的隐变量进一步建立相关的隐变量模型,再通过组合各子集的模型获得稳定的QSAR模型。而且,建立了一个新的F统计量用于确定偏最小二乘模型的维数。该算法可有效改善传统隐变量算法欠拟合问题,同时避免模型的过拟合,为复杂数据解析提供了新工具。与逐步回归相比,实验结果显示所提出方法的良好的性能。5.QSAR中,由于存在多个先导化合物模板,无法运用单一模型解释构效关更多还原

【Abstract】 The research work in this thesis focuses on the multivariate image analysis and QSAR studies and the design of some new chemometric algorithms used in these two fields.Chemical imaging analysis holds great potential in probing the chemical heterogeneity of samples with high spatial resolution and molecular specificity. This thesis demonstrates the implementation of Raman mapping for microscopic characterization of tablets containing chloramphenicol palmitate polymorphs with the aid of a new multivariate image segmentation approach based on spatial directed agglomeration clustering. This approach performs the agglomeration clustering by stepwise merging the pixels possessing both spatial closeness and spectral similarity into clusters that define the image segmentation. Additionally, the stepwise merging of clusters offers an F-statistics based procedure to automatically ascertain the number of image segments. Raman mapping analysis of tablets containing two polymorphs of chloramphenicol palmitate followed by multivariate image segmentation reveals that the proposed technique offers the identification of each polymorph and a quantitative visualization of the spatial distribution of the polymorphs identified. This technique holds promise in rapid, noninvasive and quantitative polymorph analysis for pharmaceutical production processes.A pure variable resolution algorithm coupled with Raman mapping technique is applied to identify pure spectral profiles of the ingredients in sulfa drug tablets. With the spectral data matrix obtained by Raman mapping and the identified pure spectral variables, one can obtain the matrix of the concentration profiles. Then concentration distribution maps are constructed using the concentration profiles at all pixels. The results obtained with laboratory-manufactured mixtures and commercial pharmaceutical formulations reveal that the proposed technique offers the identification of the two effective ingredients and a qualitative visualization of the spatial distribution of the ingredient identified. This approach was expected to be a promising tool in rapid noninvasive analysis for pharmaceutical production processes such as monitoring the distribution of effective ingredients as well as visualizing the pharmaceutical formulations.Morphology, chemical distribution and domain size in high-density polyethylene/ polyethylene terephthalate (HDPE/PET) polymer blends of various ratios prepared更多还原