The exponential growth of worldwide data coincides with the recent end of Moore’s Law and therefore calls for alternative, new forms of large-scale data storage and computation that go beyond conventional silicon-based devices. While DNA is commonly known as the material that is the blueprint for all life on earth, as a synthetic material it also offers an extraordinarily dense information-storage medium and highly parallel computing capabilities. In the current award, the investigator studies the use of DNA for ultra-high-density data storage and computing. DNA data files are encapsulated within nanometer-scale packets to investigate how to enable random-access memory and highly parallel computation within the same molecular file system. DNA will also be structured into 2D supra-molecular assemblies to explore spatial patterning for ultra-dense data storage and retrieval. These data-storage and computing architectures will be used to mimic neural networks commonly found in conventional silicon-based computing. Results of this project will lead to fundamental understanding that will guide next-generation information-storage and -retrieval systems that far exceed current capabilities of solid-state devices. Graduate students are being trained in an interdisciplinary manner integrating computer science, chemistry, and DNA nanotechnology. The investigator is hosting host under-represented minorities and women from local and national colleges to help nurture a diverse set of next-generation computer scientists and engineers. Results of this work are being distributed through established protocols and open source software tools disseminated online.
In the present award, DNA nanotechnology and DNA origami are used for data storage and computing. DNA files are encapsulated within silica nanoparticles for information encoding and barcoding, offering both random-access memory and highly parallel computation in solution. In parallel, 2D DNA origami superstructures are used as self-assembly blocks to organize and address information stored spatially, with DNA origami serving as memory blocks labeled with “QR codes†implemented using dyes, nanoparticles, and quantum dots. Extensive hybridization between single-stranded DNA barcodes and labels are used in both silica nanoparticles and DNA origami to explore molecular computing algorithms for associative memory and data sorting. Associative interaction maps are explored in hybridization space correlated with associative information. Together, these solution-based and structured 2D DNA memory systems offer unique opportunities for developing new DNA-based information storage architectures that mimic neural networks using associative molecular computation. Results of this award will lead to fundamental principles of hierarchical DNA-based memory systems for next-generation information storage and retrieval.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
