Speaker
Description
Abubakar, S.
Zamfara State College of Education Maru
bukarsaif@gmail.com
Track: AI, Emerging Technologies and Future Learning
Saifullah Abubakar 1 & N. A Sani2
1Department of Chemistry, Zamfara State College of Education, Maru
2Department of Chemistry, Federal University, Gusau
Email address of corresponding Author:- bukarsaif@gmail.com
Nuclear magnetic resonance (NMR) spectroscopy is an essential analytical technique used in determining the structure of organic compounds. However, traditional method of interpreting NMR spectra remains a labor-intensive and expertise-dependent process, mostly for complex or novel compounds. Consequently, to address these challenges, advanced computational approaches have demonstrated significant potential in addressing these tasks. Therefore, coupling artificial intelligence (AI) with NMR had accelerated the structural elucidation of organic compounds compared to traditional method. Specifically, AI as an emerging field that evolved as a transformative tool in this field, significantly enhances the speed, efficiency, and accuracy of structural elucidation via processing complex spectral data, predicting chemical shifts, and automating the correlation between experimental and calculated data, leading to faster and more accurate structural determination of unknown compounds. This mini review aims to explore the application of AI in structural elucidation of organic compounds such as natural products, particularly due to their specific features in terms of structural complexity and scaffold diversity compared to synthetic analogs.
Key words: NMR, AI, structural elucidation, Organic compounds, spectra