2020/03/04 by Michael Green, Xiaobo Chen · 16 citations
Chemistry · Engineering · Materials Science · Psychology · #Computer science #Curriculum #Data science #Information retrieval #Mathematics education #Merge (version control) #Mesoporous Materials and Catalysis #Microfluidic and Capillary Electrophoresis Applications #Pedagogy #Programming language #Psychology #Python (programming language) #Raw data #Software engineering #Zeolite Catalysis and Synthesis
paper · pdf · doi:10.1021/acs.jchemed.9b00818
published in Journal of Chemical Education 97(4), 1172-1175 (American Chemical Society)
openalex publication_date 2020/03/04 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/01
High Resolution Image Download MS PowerPoint Slide For undergraduate students to be prepared for graduate school and industry, it is imperative that they understand how to merge the theoretical insights gleaned through their undergraduate education with the raw data sets acquired through materials analysis. Thus, the ability to implement data analysis is a vital skill that students should develop. Furthermore, students should be fluent in methodologies that can translate to domains beyond their undergraduate curriculum. In this technology report, we demonstrate data functionalization in the Python programming language via data derived from gas chromatography. The programming approach to data analysis is designed to be flexible in order to allow students to take the lessons learned herein and apply them to novel systems outside of the experiment and outside of the academy.