School of Mathematical and Statistical Sciences Faculty Publications and Presentations
Document Type
Article
Publication Date
Fall 2024
Abstract
ChatGPT has emerged as a tool for predicting Hydrogen-1 Nuclear Magnetic Resonance (1HNMR), Infrared (IR), and Mass Spectrometry (MS) spectra. In order to rely on ChatGPT as a tool, a proof of concept for its application was essential. Having the ChatGPT outputs be validated by experimental data and databases (SDBS) has proven valuable for future uses. By inference, ChatGPT spectra output can be used to design problems without interference of copyright infringement of existing databases.
Recommended Citation
Fraiman, A., Barron, P., Dorsey, B., Delgado, S.A., & Sanchez, E. (2024). Testing the reliability of ChatGPT in providing spectral information of organic molecules. Advances in Peer-Led Learning, 4, 69-108. https://doi.org/10.54935/apll2024-01-07-69
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
First Page
69
Last Page
108
Publication Title
Advances in Peer-Led Learning
DOI
10.54935/apll2024-01-07-69
Comments
Student publication. This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.