A data mining method from pyrolyzed products: Pyrolysis-gas chromatography-photoionization-high resolution time-of-flight mass spectrometry and kendrick mass defect analysis for polymer semiconductor poly(3-hexylthiophene)

Abstract Structural analysis of polymer semiconductors is important to improve their properties but applicable method is limited due to insolubility. Here an efficient and comprehensive data mining method for such materials is developed by using pyrolysis-gas chromatography- high resolution mass spectrometry (Py-GC-HRMS). Py-GC-HRMS analysis of a polymer semiconductor poly(3-hexylthiophene) (P3HT) was performed and pyrogram with vast number of peaks was obtained. Normally in analysis of Py-GC-HRMS results, a mass spectrum is obtained for one peak in chromatogram. In one of our techniques, the mass spectra in wide time range were integrated to one mass spectrum including the information of over 300 compounds. Analysis of the mass spectrum could be using Kendrick mass defect (KMD) analysis. By making KMD plots, the compounds categorized into 29 groups depending on the structures of thiophene derivative moieties. As a result, chemical composition analysis for 29 compounds lead to peak assignment for 277 compounds in short time. Furthermore, these compounds could be categorized depending on different structural features (e.g., number of sulfur atoms, degree of unsaturation) by using appropriate divisors, leading to understanding of relationship between structural features of compounds and their retention time. The measurement without GC column provided the similar information about compounds, although the information of the retention time was lost. These methods can be one of key analysis method for insoluble polymer materials.