ITR/AP(CHE):Characterization of Complex Polymeric Materials using Visualization of Multidimensional Data Sets from Multiple Analytical Technique Fusion

肯特州立大学的Julia Fulghum和Javed Khan得到了信息技术研究（ITR）项目化学系的支持，为非均相固体聚合物材料的非破坏性三维表征创造了新方法。数据将从越来越复杂的聚合物样品中获取，使用各种分析技术，包括x射线光电子能谱、飞行时间二次离子质谱和傅里叶变换红外光谱。所有这些方法都可以从不同的样品体积中获得化学信息，并生成多维数据集。多元统计分析和分类方法将用于增强对所获取数据集的解释，最终能够创建一个统一的聚合物框架，称为主动知识网格。该组合系统将在大型和复杂的信息空间探索中创造计算机和用户之间的协同作用，为多模态数据分析及其多视角可视化提出有趣的挑战。聚合物广泛应用于各种高科技应用中。例如，许多当前和拟议的生物材料是聚合物，聚合物也包含在用于轻型飞机和汽车的复合材料中。商业上重要的材料通常涉及分子复杂的聚合物混合物，其表面化学和结构分析特别具有挑战性。该项目的成果有望提高对复杂聚合物共混特性的理解和评估，并最终增强对技术上重要材料特性的控制。

Julia Fulghum and Javed Khan of Kent State University are supported by the Division of Chemistry under the Information Technology Research (ITR) program to create new methods for the non-destructive, three-dimensional characterization of heterogeneous, solid polymeric materials. Data will be acquired from polymer samples of increasing complexity using a variety of analytical techniques, including x-ray photoelectron spectroscopy, time-of-flight secondary ion mass spectrometry, and Fourier transform infrared spectroscopy. All of these methods can be used to obtain chemical information from different sample volumes, and to generate multidimensional data sets. Multivariate statistical analysis and classification methods will be used to enhance interpretation of the acquired data sets, ultimately enabling creation of a unified polymer framework, called an active knowledge mesh. The combined system will create synergy between the computer and the user in large and complex information space exploration, posing interesting challenges for multi-modal data analysis and its multi-perspective visualization.Polymers are widely used in a variety of high technology applications. For example, many current and proposed biomaterials are polymers, and polymers are contained as well in composites used for a light aircraft and automobiles. Commercially important materials often involve molecularly complex polymer blends whose surface chemistry and structure are particularly challenging to analyze. Outcomes from this project are expected to improve the understanding and evaluation of complex polymer blend characteristics, and ultimately enable enhanced control of technologically important materials properties.