Research Projects

Green Hydrogen

Researchers at the Water and Environmental Research Lab, guided by Dr. Abdel-Wahab, are working on water electrolysis, a process to turn surplus renewable electricity into hydrogen. This process typically relies on expensive materials; the so-called platinum-group-metals (PGMs).

The research team used the raad2 supercomputer to help them design an alternative material, made of cobalt copper (CoCu) alloyed nanoclusters grown atop carbon nanowires, which turns out to be cheaper than PGMs.

The showcased material was experimentally fabricated, electrochemically tested, and results were published in Elsevier’s Journal of Industrial and Engineering Chemistry.

Molecular Design of Metal-Organic Frameworks for Gas Separation

Metal-organic frameworks (MOFs) and their sub-family of zeolitic-imidazolate frameworks (ZIFs) are fascinating materials as they could help solve environmental problems in the form of storage materials, catalysts, and membranes in industrial processes. They can be customized at the atomic scale to have special properties, but implementing such customizations in the lab is a challenging endeavor.

Since 2014, TAMUQ researchers have been developing better materials for cleaner and cheaper gas separation processes. Towards this end, they have created a computational model to predict how gases move through such materials based on their internal structure.

The raad2 supercomputer has been central to this work as various relevant “experiments” are done via computational modeling rather than in a conventional laboratory. These investigations require significant computational power and cannot otherwise be performed on desktop workstations.

Smart Grid

TAMUQ researchers have used big data and machine learning (ML) to make energy grids smarter and more reliable. They are developing a platform that can analyze massive amounts of data from electrical grids in real-time, not only to predict problems but also to improve energy consumption forecasts. The raad2 supercomputer allowed researchers to train their ML models on grid generated data, benefiting from its massively parallel architecture and computational capacity. The Hadoop framework was used to make this research possible. It is expected to lead to a dynamic energy management system that optimizes energy use and load management both for efficiency and real-time demand-response programs.

Greenhouse Gas Recycling

The raad2 supercomputer, along with technical contributions from the RC team lead by Dr. Bouhali, played a vital role in two projects by Professor Nimir Elbashir's research group.

In the first project, researchers optimized catalyst materials to convert greenhouse gases into valuable syngas that could be used to synthetize ultra clean fuel, resulting in three journal articles and a patent application. And in the second project, they explored turning CO2 into useful formic acid, leading to a significant journal publication.

Thanks to the use of raad2, the research team not only made important discoveries contributing to greener energy and chemical production processes but also trained several students and researchers in this domain.