journal article·2024-09-12

Photoinduced Negative Differential Resistance at a Graphene/Silicon Interface: A Nonadiabatic Quantum Molecular Dynamics Study

Hinata Hokyo, Kai Ito, Rajiv K. Kalia, Rehan Kapadia, Aiichiro Nakano, Kohei Shimamura, Fuyuki Shimojo, Priya Vashishta

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Abstract

The oscillatory retinal neuron (ORN) is a promising technology for achieving in-sensor cognitive image computing without external power. While its operation is based on photoinduced negative differential resistance (NDR) at a graphene/silicon interface to directly convert the incident optical signal into voltage oscillations, the optoelectronic mechanism of the NDR remains elusive. Here, nonadiabatic quantum molecular dynamics simulations show that the interplay of band alignment and charge transfer rates of photoexcited carriers at varying applied voltages gives rise to NDR at a graphene/silicon interface under illumination. Such intrinsic NDR at an interface, along with extrinsic circuit-level factors, could enable the much needed rational design of desired image computing functionality of ORN devices in the era of ubiquitous AI on edge devices.
Source: openalex_inverted_index · Quality: baseline

Research context

OpenAlex topics: Photoreceptor and optogenetics research · Advanced Memory and Neural Computing · Neural Networks and Reservoir Computing

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Collaboratory for Advanced Computing and Simulation, University of Southern California, Los Angeles, California 90089-0242, United States

Department of Physics, Kumamoto University, Kumamoto 860-8555, Japan

Department of Electrical and Computer Engineering, University of Southern California, Los Angeles, California 90089-2560, United States

Funding

Division of Electrical, Communications and Cyber Systems · Division of Civil, Mechanical and Manufacturing Innovation

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