OSC-talk.pdf

Title: Engaging Undergraduates in a Search for Environmentally Relevant Quantum Chemical Descriptors of Polyfluoroalkyl Substances (PFAS)
Coauthors: C. Morales*, D. Snyder
Affiliation: University of Mount Union, Alliance, OH, USA, 44601
Per- and polyfluoroalkyl substances (PFAS) are widespread and gaining importance as their environmental persistence and distribution leads to bioaccumulation throughout the food chain. Thousands of PFAS are now widely used and the data on their persistence and environmental distribution are incomplete. Here, established computational chemistry methods were applied to investigate new, shorter-chain PFAS by calculating quantum chemical descriptors and applying big data analysis methods to assess their impact on environmentally relevant properties. The ultimate goal is to evaluate whether these can be used to improve upon existing cheminformatics models such as OPERA that do not include any quantum chemical descriptors. Faculty and students in Ohio have access to the Ohio Supercomputing Center, a statewide high-performance computing (HPC) center. In particular, the WebMO graphical user interface at OSC was used to rapidly calculate quantum chemical descriptors and to export all data in JSON and/or CSV format. To analyze these data, standard Python libraries were used within the user-friendly Jupyter notebook interface through OSC OnDemand. Due to the ease of use and accessibility of OSC resources, an undergraduate student without prior experience successfully completed a senior capstone research project in one semester while breaking new ground and establishing the foundation for this new computational chemistry research project.