다중분광기법 기반 미지화학물질 구조 해석 연구

초록

With the emergence of novel narcotics and chemical warfare agents, structural elucidation of unknown chemical substances is essential for chemical incident response. Field detection equipment provides rapid alerts but faces false positive issues, necessitating robust verification. This study examines an integrated strategy combining infrared (IR), Raman, and nuclear magnetic resonance (NMR) spectroscopy with density functional theory (DFT)-based computational predictions. IR provides functional group information, Raman reveals molecular backbone vibrations, and NMR offers bonding relationships. Since spectral variations occur depending on experimental conditions and computational settings , applying scaling factors can reduce average errors. This study presents a systematic procedure for evaluating relative suitability among structural candidates by connecting IR-Raman-NMR results and utilizing DFT predictions as comparative references. Integrating multi-spectroscopic data and cross-validating with computational predictions effectively reduces errors caused by relying solely on individual methods. The proposed procedure will serve as a practical reference standard in the structural verification of unknown compounds.

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