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Cencer, Morgan M.

Publications and source records attributed to Cencer, Morgan M..

Probing Electrolyte Influence on CO 2 Reduction in Aprotic Solvents

Selective CO 2 capture and electrochemical conversion are important tools in the fight against climate change. Industrially, CO 2 is captured using a variety of aprotic solvents due to their high CO 2 solubility. However, most research efforts on electrochemical CO 2 conversion use aqueous media and are plagued by competing hydrogen evolution reaction (HER) from water breakdown. Fortunately, aprotic solvents can circumvent HER, making it important to develop strategies that enable integrated CO 2 capture and conversion. However, the influence of ion solvation and solvent selection within nonaqueous electrolytes for efficient and selective CO 2 reduction is unclear. In this work, we show that the bulk solvation behavior within the nonaqueous electrolyte can control the CO2 reduction reaction and product distribution occurring at the catalyst-electrolyte interface. We study different tetrabutylammonium (TBA) salts in two electrolyte systems with glyme ethers (e.g., 1,2 dimethoxyethane or DME) and dimethyl sulfoxide (DMSO) as a low and high dielectric constant medium, respectively. Using spectroscopic tools, we quantify the fraction of ion pairs that forms within the electrolyte. Also, we show how ion pair formation is prevalent in DME and is dependent on the anion type. More importantly, we show that as ion pair formation decreases within the electrolyte, CO 2 current densities increase, and a higher CO Faradaic efficiency is observed at low overpotentials. Meanwhile, in an electrolyte medium where the ion pair fraction does not change with the anion type (such as in DMSO), a smaller influence of solvation is observed on CO 2 current densities and product distribution. By directly coupling bulk solvation to interfacial reactions and product distribution, we showcase the importance and utility of controlling the reaction microenvironment in tuning the electrocatalytic reaction pathways. Insights gained from this work will enable novel electrolyte designs for efficient and selective CO 2 conversion to desired fuels and chemicals.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Machine learning for polymeric materials: an introduction

We report that Polymers are incredibly versatile materials and have become ubiquitous. Increasingly, researchers are using data science and polymer informatics to design new materials and understand their structure-property relationships. Polymer informatics is an emerging field. While there are many useful tools and databases available, many are not widely utilized. Herein, we introduce the field of polymer informatics and discuss some of the available databases and tools. We cover how to share polymer data, approaches for preparing a dataset for machine learning and recent applications of machine learning to polymer property prediction and polymer synthesis.

36 MATERIALS SCIENCE↗