High-throughput Synthesis of Cu-based Electrocatalysts for Carbon Dioxide Reduction using Multimodal Robotic Platforms

Efficient and low-cost electrocatalysts are crucial for numerous industrial clean energy applications. However, the traditional catalyst discovery framework is constrained by the lengthy duration required for synthesizing and testing one single catalyst, as well as the human error introduced that compromises experimental repeatability. This project will redefine the catalyst development pattern by employing a streamlined, multimodal robotic platform for the high-throughput synthesis, screening and validating of a library of electrocatalyst in a matter of hours to a few days. Using the Carbon Dioxide Reduction Reaction to Ethanol production as a model reaction, we will focus on copper catalyst, leveraging the automated platform to systematically tailor element types and concentrations to achieve highly selective production of ethanol with a target selectivity > 80%. The successful outcomes of this study will provide Canadian institutions, organizations and companies with accelerated pathways to identify high-performance clean energy materials, significantly contributing to the goal of achieving net-zero carbon emissions by 2050 and strengthening its competitiveness in the critical clean energy sector.

Faculty Supervisor:

Drew Higgins

Student:

Partner:

Massachusetts Institute of Technology

Discipline:

Engineering

Sector:

Education

University:

McMaster University

Program: