Low-Power Artificial Neural Network Perceptron Based on Monolayer MoS₂.

ABSTRACT: Machine learning and signal processing on the edge are poised to influence our everyday lives with devices that will learn and infer from data generated by smart sensors and other devices for the Internet of Things. The next leap toward ubiquitous electronics requires increased energy efficiency of processors for specialized data-driven applications. Here, we show how an in-memory processor fabricated using a two-dimensional materials platform can potentially outperform its silicon counterparts in both standard and nontraditional Von Neumann architectures for artificial neural networks. We have fabricated a flash memory array with a two-dimensional channel using wafer-scale MoS₂. Simulations and experiments show that the device can be scaled down to sub-micrometer channel length

SUBMITTER: Migliato Marega G 

PROVIDER: S-EPMC8945700 | biostudies-literature | 2022 Mar

REPOSITORIES: biostudies-literature