Non-volatile memory (NVM) devices are used to store data in smartphones, tablets, computers, hardware for Internet of Things, wireless routers and communication systems, and other electronic devices. In addition, NVMs also have applications in computing hardware to accelerate Artificial Intelligence and Machine Learning algorithms. However, currently available memory devices have limitations and novel techniques for storing tremendous amount of data that can surpass the density of data storage by a thousand-fold or more needs investigation. Storing data in synthetic-DNA is a promising route as it is the densest known storage medium with the information encoded lasting forever in a conducive environment. However, purely DNA-storage is based on a chemical nature that imposes its own set of challenges such as high-cost, read error, and incompatibility with Complementary Metal Oxide Semiconductor (CMOS) integrated circuits (ICs). The bottleneck with DNA-storage is its efficiency, as it is million times slower than the timescales in a silicon memory chip. Considering the time- & effort-consuming coding/decoding process for typical DNA molecular memory, as well as its volatile nature due to polymerization-based sequencing-identified coding mechanism, simply using DNA as a medium for information coding remains technically inefficient. The issues limiting DNA usage for data storage can be addressed if an appropriate medium to host synthetic-DNA can be synergistically designed to control subtle inter-molecular interaction to generate multiple states and the devices based on this biomaterial can be integrated with CMOS ICs. Organometallic halide perovskite (OHP) semiconductors provide a promising host material to support DNA due to process compatibility leading to the development of novel OHP-DNA-biomaterials based high-density memory arrays. This research will address grand-challenges of exploring novel concepts of integrating DNA-Semiconductor biomolecular complexes for high-density data storage on traditional semiconductor platforms. The project will provide significant opportunities for multi-disciplinary training of graduate and undergraduate students from diverse backgrounds by developing a new course to be offered at University of Cincinnati (UC) and Penn State University (PSU) for advancing the next generation of computing based on biomolecular complexes beyond just traditional semiconductors. Existing University programs like G-FEST and NERDS will be leveraged to support high-school and middle school outreach efforts at UC and PSU. The objective of this proposal is to develop high-density memory devices based on hybrid OHP and synthetic-DNA biomaterials and demonstrate its application for data-storage and In-Memory Computing (IMC) in integrated optoelectronic systems with CMOS-back-end. DNA provides tremendous opportunities to tune its properties by modifying the parameters such as base-pairs, sequence, length, rotation, and crystallinity for electrical and optical properties in a hybrid OHP-DNA memory device. Specific aims of the project include: 1. Modeling, design, and synthesis of specific DNA sequences for integration with OHP semiconductor; 2. Development of OHP-DNA biomaterials and characterization; 3. Development of OHP-DNA-based high-density memory devices and integration with OHP-optoelectronic systems and CMOS Back-End of Line (BEOL). Collaborative team between the University of Cincinnati (UC) and Penn State University (PSU) has expertise and state of the art resources necessary to successfully complete the proposed aims. A successful completion will lead to (i) fundamental understanding of communications between synthetic-DNA and OHP and methods for tailoring OHP in conjunction with DNA engineering to achieve high-density multi-state NVMs, (ii) routes to synthesize OHP-DNA biomaterials capable of data storage, (iii) ICs with integrated OHP-DNA memory devices with CMOS in back-end and approaches for computing and data-storage. These results will have transformative impacts on providing novel DNA-based technologies for future data storage needs.This project has been jointly funded by Division of Molecular and Cellular Biosciences (MCB) in the Directorate for Biological Sciences (BIO), Division of Computing and Communication Foundations (CCF) in the Directorate for Computer and Information Science and Engineering (CISE), Division of Electrical, Communications and Cyber Systems (ECCS) in the Directorate for Engineering (ENG), and the Division of Materials Research (DMR) in the Directorate for Mathematical and Physical Sciences (MPS).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.
|Effective start/end date
|8/1/22 → 7/31/25
- National Science Foundation: $1,408,548.00
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