The practice of spectroscopy today requires researchers, as well as students, to have strong data analysis and visualization skills. I describe an approach to targeting these skills as learning objectives in a unit on spectroscopy in a 300-level majors’ course at a primarily undergraduate institution. In an adaptation of a lesson on the Beer-Lambert Law, students engage in hands-on work both with instrumentation in the lab, and on the computer in MATLAB. A real-world connection between molar absorptivity and popular beverages is made, as students construct calibration curves and measure the absorbance of Mtn Dew Kickstart to infer Red Dye #40 (Allura Red) concentration. Basis spectra of a blue and yellow food dye are then used to demonstrate the need for multivariate analysis for better accuracy, and help students understand basic color mixing in the context of transmittance. With very limited prior exposure to programming, students are guided through linear regression, multivariate analysis, and plotting in MATLAB to produce high quality figures. An accompanying lecture on data visualization with an active-learning component prompts students to engage with the importance of data presentation and best practices for visualization of results.

Kickstarting spectroscopic data analysis and visualization in an undergraduate chemistry course

Where thousands of chemistry professionals meet to share ideas and advance scientific and technical knowledge. Spring 2023 abstracts, posters, and presentations will launch at the end of March.

ACS Spring 2023

The official archive and repository for all ACS Meetings & Expositions abstracts and select posters or presentations.