| Summary: | 碩士 === 國立清華大學 === 化學工程學系 === 104 === Polybutylene terephthalate (PBT) is a thermoplastic engineering polymer that is used as an insulator in the electrical and electronics industries. The quality of PBT mainly refers to its content of A. However, synthesis of PBT by terephthalic acid (TPA) process always accompanies the generation of A by-product, especially, the excessive A content will downgrade the commercial value of PBT.
The main purpose of this research project is to improve the manufactoring technologies of PBT process. In first part, we have been established a new measurement method for determining A and B content in PBT product. The A measurements were performed on a gas chromatography (GC). We can use the calibration curve to estimate the amount of that analysis in a sample of unknown A concentration. The B content of the reaction mixtures was determined by liquid chromatography–mass spectrometry (LCMS). We use three PBT products from company to measure quality.
In second part, we aim to use principal component analysis (PCA) for enhancing the quality of PBT. PCA is a technique used to emphasize variation and bring out strong patterns in a dataset. It's often used to make data easy to explore and visualize. PCA is a statistical procedure for identifying a smaller number of uncorrelated variables, called principal components. The goal of principal components analysis is to explain the maximum amount of variance with the fewest number of principal components. PCA is commonly used in the social sciences, market research, and other industries that use large data sets. Based on PCA, we attempt to develop analysis for reducing amount of A generation and amount of B generation during the PBT process.
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