Energy Institute Researchers Publish CCS Safety Review Article
A group of researchers from the Texas A&M Energy Institute and the Mary Kay O’Connor Process Safety Center has recently published an article titled “Rethinking Safety in Carbon Capture and Storage (CCS) Systems,” in Chemical Engineering Progress (CEP), the flagship magazine of the American Institute of Chemical Engineers. This article, made possible through strong industry–academia collaborations, challenges conventional […]
Energy Institute Partners with the Mosbacher Institute for Trade, Economics, and Public Policy
The Texas A&M Energy Institute and the Mosbacher Institute for Trade, Economics, and Public Policy signed a formal agreement on January 20, 2026 at the Texas A&M Energy Institute to identify, pursue, and capitalize upon collaborative, complementary, and novel efforts in relevant research, education, and training.
Meeting Rising U.S. Electricity Demand from AI and Data Centers: An Integrated Technical and Policy Perspective
As a part of the Mosbacher Institute White Papers series, several Texas A&M Energy Institute researchers have published an article on meeting rising demand from AI and data centers. This article examines the causes of the emerging electricity crisis in the United States amid rapid growing demand given the expansion of Artificial Intelligence (AI).
Lighting the Way: Texas A&M Energy Institute sponsors streetlights to enhance safety and opportunity in Goma, DRC
The Texas A&M Energy Institute, driven by a deep commitment to global impact, recently sponsored the installation of 54 solar-powered streetlights in neighborhoods in Goma, Democratic Republic of Congo (DRC), a region grappling with significant security and humanitarian challenges.
Daher Publishes Paper on Simplexity in Nature Sustainability
A new World View article in Nature Sustainability by Dr. Bassel Daher, Assistant Director for Sustainable Development at the Texas A&M Energy Institute, argues that solving today’s intertwined sustainability challenges demands more than bigger models and more data. It requires mastering “simplexity”, the art and science of translating complexity into actionable insight without losing nuance.