Jehad is a Vanier doctoral researcher at the Sargent group – University of Toronto. He is leading the Alliance of AI-Accelerated Material Discovery (A3MD) efforts to accelerate the discovery of materials for efficient and durable electrocatalysis with the help of automation and data-driven experimentations. Jehad’s interests lie at the interface of material science, chemistry, and data science; he employs high-throughput experimentation, machine learning, and operando characterization to develop novel catalysts for a green and sustainable economy. Jehad is also passionate about transferring technology from the lab to industry; he was a finalist in the Carbon XPRIZE, where the team was able to upscale CO2 conversion into value-added products.
Ph.D. Thesis Abstract:
With the large, anticipated penetration of low-cost renewable electricity into the power grid comes the need for cost-effective, carbon-neutral, and large-scale storage. Water splitting and CO2 reduction (CO2R) can store electricity in the form of stable chemical bonds in synthetic fuel and chemical feedstocks, mitigating the variability challenge of renewable energy. However, the energy efficiency of these electrocatalytic systems is limited by the sluggish kinetics and high overpotentials at the anode imposed by the oxygen evolution reaction (OER). A relatively small selection of OER electrocatalysts meet the requirements for industrial electrocatalysis: low OER overpotentials (<300 mV) at high current densities (>500 mA·cm-2) for long-term operation (>60,000 h). Identifying durable and efficient OER electrocatalysts is urgently needed to enable large-scale industrial implementation of important electrocatalytic technologies such as water splitting and CO2R.