ポスター発表
- 第2日 5月16日（火） P会場（ホワイエ，会議室1004-1007）
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2P-30 PDF
Py-GC-TOFMSと機械学習を用いた高分子材料熱分解生成物の構造解析
In gas chromatography-mass spectrometry (GC-MS), compounds can be identified by comparing electron ionization (EI) mass spectra to a database of known compounds. However, this method is limited by the EI mass spectra registered in the library, and so only compounds found in these databases can be identified. That means there are many compounds that will not only remain unidentified by conventional library searching, but may also result in false positives. We have developed a machine-learning model that can predict EI mass spectra from chemical structures. This allowed the creation of a database containing the predicted EI mass spectra of over 100 million chemical compounds found in PubChem. A library search method for increased accuracy and efficiency was also developed.