A scattered data approximation tool to map carbon nanotube dispersion to the processing parameters in polymer nanocomposites

[摘要] The relationship of nanocomposite dispersion was studied with the variation of dispersion techniques and other processing parameters. Examining all permutations of the various factors in the laboratory is a challenging task. In this thesis, we propose to map a correlation between inputs and output via a self-adaptive scattered data approximation method. The proposed greedy algorithm, Sequential Function Approximation (SFA), reveals the multidimensional behavior of the system, provides the sensitivity of each input, and presents the combination of inputs that is most suitable for a specific output. In this research, we have collected data from various research institutions and applied it to SFA. The results show that CNT weight percent, sonication time, CNT modification, and high shear mixing time are key factors that affect the dispersion. This thesis discusses SFA, the data, and the results in detail. This work serves as a proof of concept and recommended future work is discussed.

[发布机构] Rice University

[效力级别] engineering