DOE Funds Duke-Led AI Platform to Design Transformative DNA-Based Materials

A team of researchers led by engineers at Duke University have been awarded a Phase 1 Genesis grant from the Department of Energy to develop an AI platform to accelerate the design of hierarchically ordered DNA-based materials with critical applications in photonic, electronic and catalytic systems.

The research project is led by Gaurav Arya, professor of mechanical engineering and materials science at Duke, and also includes Stefan Zauscher, professor of mechanical engineering and materials science at Duke; Yonggang Ke, associate professor of biomedical engineering at Georgia Tech and Emory University; and Stephen Whitelam, staff scientist focusing on the theory of nanostructured materials at Lawrence Berkeley National Laboratory.

“Although individual DNA origami structures have enabled important advances in areas such as drug delivery, biosensing and nanophotonics, their small size fundamentally limits many emerging applications,” Arya said. “Scaling these nanoscale building blocks into programmable, large periodic lattices of the origami structures would unlock a new class of functional biomolecular materials.”

Most people are familiar with the DNA double-helix. Its twisted ladder shape forms because the long pieces of DNA that make up our genome are exactly complementary—every adenine paired to a thymine, and every cytosine paired to a guanine. Sequences of these four nucleotides hold the information needed to build the proteins in our bodies, but they also encode their own helical structure.

Since the 1980s, scientists have hijacked these pairing rules to build structures other than double helices. This field is called DNA nanotechnology, and its most popular implementation, DNA origami, lets researchers fold DNA into any shape, providing a powerful approach for building nanoscale devices and machines as well as designing new types of biomaterials.

While the fabrication of individual DNA origami nanostructures, typically smaller than 100 nanometers, is now well established, programming these building blocks to spontaneously self-assemble into much larger, highly ordered architectures spanning tens of micrometers or beyond remains a major challenge. An even greater challenge is the inverse design problem: determining the geometry and interaction patterns of DNA origami building blocks that will reliably self-assemble into a user-specified target architecture.

Solving this problem is the central objective of the new Genesis Project grant. The research effort will develop an AI framework that automatically designs DNA origami building blocks to assemble into user-specified superlattice architectures.

To train the AI models, the researchers will combine large-scale computer simulations, high-throughput experiments and machine learning to uncover the relationships between building block design and self-assembled structure. Starting with 2D DNA origami tiles, the framework will eventually be expanded to include 3D, multicomponent assemblies with tailored structural and functional properties.

“By dramatically accelerating the discovery of programmable nanostructured materials, this project will enable new approaches for designing energy-relevant photonic, plasmonic, electronic and catalytic materials,” Arya said. “We’re just beginning to tap into this enormous design space, and we expect the novel materials that result from this effort will greatly impact industries such as energy production, chemical manufacturing and even quantum computing.”

The Genesis Mission is a historic national initiative led by the U.S. Department of Energy, which is building the world’s most powerful integrated science discovery platform. By uniting government, industry, academia and philanthropy, it is accelerating breakthroughs in energy, scientific discovery and national security through a new platform that combines AI, supercomputing, quantum systems and advanced scientific instruments.

The goal of the Phase I awards is to identify promising pathways toward transformative scientific capabilities and establish a foundation for future investment and scale. Project teams will design and demonstrate research workflows that integrate AI with scientific investigation, while rigorously evaluating whether those approaches can accelerate discovery, improve predictive capabilities, enhance experimentation or generate new scientific insights.

Phase I awards range from $500,000 to $750,000 and support projects for nine months. Phase II awards range from $6 million to $15 million over a three-year project period.