Analysis of Large Data Sets in a Physical Chemistry Laboratory NMR Experiment Using Python
We describe an update to an experiment demonstrating low-field NMR spectroscopy in the undergraduate physical chemistry laboratory. A Python-based data processing and analysis protocol is developed for this experiment. The Python language is used in fillable worksheets in the notebook software JupyterLab, providing an interactive means for students to work with the measured data step by step. The protocol teaches methods for the analysis of large data sets in science or engineering, a topic that is absent from traditional chemistry curricula. Python is among the most widely used modern tools for data analysis. In addition, its open-source nature reduces the barriers for adoption in an educational laboratory.
Reference
Zefan Zhang, Anshul Gautam, Soon-Mi Lim, and Christian Hilty, Journal of Chemical Education Article ASAP
DOI 10.1021/acs.jchemed.3c00586 KEYWORDS: Upper-Division Undergraduate, Physical Chemistry, Inquiry-Based/Discovery Learning, Computer-Based Learning, NMR