Coupling Simulation and Experimental Approaches for CO2 Reduction to Multi-Carbon Compounds

• Grant number: 23/16349-4
• Support Opportunities: Scholarships abroad - Research Internship - Doctorate
• Start date: February 29, 2024
• End date: June 30, 2024
• Field of knowledge: Physical Sciences and Mathematics - Chemistry - Physical-Chemistry
• Principal Investigator: Ernesto Chaves Pereira de Souza
• Grantee: Eryka Thamyris Damascena Nobrega Cavalcanti
• Supervisor: Thomas Edward Rufford
• Host Institution: Centro de Ciências Exatas e de Tecnologia (CCET). Universidade Federal de São Carlos (UFSCAR). São Carlos , SP, Brazil
• Institution abroad: University of Queensland, Brisbane (UQ), Australia
• Associated to the scholarship: 22/05254-0 - Carbon dioxide electrochemical reduction to polymeric precursors, BP.DR

Abstract

The integration of computational methods into general science presents numerous advantages, such as accessibility and relatively low cost. In recent decades, there has been a significant research effort dedicated to developing and adapting numerical methods for addressing electrochemical problems. One potential application involves analyzing local factors in CO2 electrolysis. The application of Computational fluid dynamics in this domain enables a detailed simulation of fluid flow, heat transfer, and electrochemical properties within the electrolyzer. In this perspective, the project centers on a thorough investigation of the electrochemical reduction of CO2 on gas diffusion electrodes and flow reactors. The study adopts a dual approach, integrating experimental techniques with simulation methods, specifically employing the finite element approach and chemometrics analysis. The primary objective is to synthesize multicarbon products with high added value. Specific objectives include evaluating the impact of controllable wettability on the electroreduction performance of CO2, understanding the influence of key variables in flow reactor systems, validating the model through experiments using CO2 electrolysis, and optimizing experimental conditions using statistical tools. The ultimate goal is to propose innovative conditions that can enhance the efficiency of the electrochemical reduction process.