CAREER: Scalable monolithic integration of Graphene/MoS2/Graphene artificial neurons and synapses for accelerated machine learning

Nontechnical:

Development of integrated circuits was a milestone in the golden age of electronics. That feat will be replicated by this project through the development of both artificial neurons and synapses on the same materials platform. This will allow us to create systems that can emulate the capacity and speed of the human brain for pattern matching, beating current systems that are bulkier, slower and more power hungry.

This will revolutionize the field of machine learning and create devices where the machine-learning hardware is close to the sensor, giving rise to systems that are currently impossible to create. Neuromorphic circuits based on these devices include smart wearables that can monitor health biometrics and issue first level triage for elderly people alone at home.

They can improve autonomous driving for terrestrial vehicles. These circuits will be especially useful for spacecrafts and space rovers because these ultra-light circuits will not be a bottleneck to the rocket's payload. Fast pattern recognition abilities through these deep neural networks will enhance speech recognition in portable electronics and improve traffic analysis and control systems.

In collaboration with Central Florida STEM Alliance (CFSA) program, underrepresented minorities from local community colleges will be provided hands-on research opportunities in the lab of the PI. Regular video lab tours to underrepresented K-12 students and week-long lab experience for two selected K-12 students annually will foster their interest in STEM education.

Banners highlighting key aspects of this research will be displayed at the Orlando Science Center for general public awareness. These efforts will lead the electronics industry to invest in Florida through the Florida High Technology Corridor, creating opportunities for engineers in the state. Technical:

The objective of this proposal is to develop scalable monolithically integrated artificial neurons and synapses using all-two-dimensional (all-2D) graphene/MoS2/graphene memristive heterostructures for neuromorphic computing. In these heterostructures graphene acts as the electrodes and MoS2 as the switching medium. Volatile resistive switching observed in vertically-standing sheets of MoS2 will be harnessed to realize integrate-and-fire (IF) neurons, and the stochastic nature of their firing will be investigated.

Artificial synapses with sub-picojoules of energy requirement per switching event will be developed using the multi-level non-volatile switching in horizontal MoS2 sheets. The mechanisms behind this intriguing phenomenon of volatile resistive switching in vertical MoS2 sheets versus non-volatile switching in horizontal MoS2 sheets will be investigated using electrical and materials characterization techniques.

The necessity of graphene electrodes in the heterostructure will be justified. Through engineering of the heterostructure design, the performance of the artificial neurons and synapses will be optimized to create stochastic resistive-switching IF neurons and low-power synapses which will be integrated monolithically. The advantage of mechanical flexibility of graphene and MoS2 will be exploited to fabricate and test these neuromorphic devices on a flexible platform.

The proposed research program aims at bringing together two emerging research areas cohesively into a cutting edge technology. While 2D materials have immense prospects in succeeding silicon within the von Neumann paradigm, non-von Neumann approaches have always dealt with conventional materials. This transformative research would bring together the best of both these worlds.

The use of large-area 2D materials will enhance the practical realization of these exotic devices. Ultra-low power operation of graphene/MoS2/graphene artificial synapses with sparse firing graphene/MoS2/graphene artificial neurons will provide for energy-efficient neuromorphic computing.

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.