A GPU supercomputer for quantum- and AI-driven chemistry and materials research — NSF AI grant $1.4M (University of New Mexico, MRI)

The NSF awarded about $1,399,999 to the University of New Mexico (UNM) as a Major Research Instrumentation (MRI) grant to acquire a GPU supercomputer for quantum- and AI-driven chemistry and materials research (NSF Award 2511915).

1A resource for AI- and quantum-driven chemistry

Per the abstract, the project supports acquisition and operation of a dedicated GPU-based, large-memory, parallel high-performance supercomputing cluster as a state-of-the-art resource for AI- and quantum-driven chemistry and materials research at UNM. The resource enables simulations and algorithm development by faculty and researchers from chemistry, physics, and engineering, affiliated through the Center for Computational Chemistry (C^3) and the Center for Quantum Information and Control (an NSF Focused Research Hub in Theoretical Physics).

2Deepening understanding of many-body systems

The system advances understanding of the complex quantum phenomena underlying the computational design of new chemicals, biomolecules, reactions, and materials, and the development of novel quantum-computing algorithms for simulating complex many-body systems.

Broader impact comes through education and training of the next generation of interdisciplinary chemistry, chemical-biology, and materials researchers via the NSF Research Traineeship (NRT) Quantum Photonics and Quantum Technology (QPAQT) graduate program, the Quantum Undergraduate Research Experience (QU-REACH) summer program, and new computationally driven courses.

3By state totals the gap widens further

Summing obligations by the state of the receiving institution across the 120 NSF AI-related awards this site holds as of 2026-09-01, California leads at about $72.26 million, then Texas at about $38.24 million, Massachusetts at about $18.21 million and Illinois at about $16.95 million.

California holds a fifth of the awards by count and rather more than a fifth by amount. States such as Wisconsin reach the upper ranks on total while holding few awards, because one large award moves a state's position. Which measure is used changes the colours on the map.