Two-dimensional materials based two-transistor-two-resistor synaptic kernel for efficient neuromorphic computing.

ABSTRACT: Neuromorphic computing based on two-dimensional materials represents a promising hardware approach for data-intensive applications. Central to this new paradigm are memristive devices, which serve as the essential components in synaptic kernels. However, large-scale implementation of synaptic matrix using two-dimensional materials is hindered by challenges related to random component variation and array-level integration. Here, we develop a 16 × 16 computing kernel based on two-transistor-two-resistor unit with three-dimensional heterogeneous integration compatibility to boost energy efficiency and computing performance. We demonstrate the 4-bit weight characteristics of artificial synapses with low stochasticity. The synaptic array demonstration validates the practicality of utilizing eme

SUBMITTER: He Q 

PROVIDER: S-EPMC12064777 | biostudies-literature | 2025 May

REPOSITORIES: biostudies-literature