Zeeshan Ahmad has been selected to receive the Samsung Global Research Outreach (GRO) grant

Zeeshan Ahmad, an assistant professor in the Department of Mechanical Engineering at Texas Tech University, has been selected as one of only 20 researchers worldwide to receive the Samsung Global Research Outreach (GRO) grant.

Ahmad’s winning proposal, titled “Long-Range Equivariant Machine Learning Interatomic Potentials for Simulating Charge Transfer,” aims to harness artificial intelligence to develop advanced atomistic simulations for large-scale systems, a capability not possible with current computational methods. The project addresses a critical stage in semiconductor manufacturing, known as chemical mechanical planarization (CMP), an essential process in fabricating advanced microchips.

Corrosion inhibition plays a vital role in CMP and in protecting metal surfaces across industrial applications. Although organic molecule-based inhibitors such as BTA have been used for more than 60 years, progress in developing new inhibitors has been slow due to limited understanding of the corrosion process at the atomic level under realistic conditions like solvent environments and surface dynamics.

Traditional first-principles simulations, including density functional theory (DFT), can provide valuable atomic-scale insights but are typically restricted to small systems due to their high computational cost. Ahmad’s research will employ AI-driven simulations to uncover the mechanisms by which organic molecules inhibit copper corrosion on wafer surfaces. These findings are expected to guide the design of next-generation corrosion inhibitors, addressing a long-standing challenge in the semiconductor industry.

Through the GRO grant, Ahmad will collaborate closely with researchers at Samsung, advancing both scientific discovery and workforce development. The project will also provide hands-on training for Ph.D. students, preparing them with high-demand expertise in AI, materials science, semiconductor manufacturing, and computational simulation.