Large-scale crossbar arrays based on three-terminal MoS₂ memtransistors.

ABSTRACT: Memristive crossbar architectures are promising as efficient, low-power inference engines for edge AI applications. However, inputs with minor differences often yield similar outputs, requiring additional processing methods such as confidence scoring, feedback mechanisms, crossbar redundancy, or hybrid analog-digital approaches to resolve. These methods can be impractical for resource-limited edge devices. In contrast, three-terminal memtransistors can dynamically tune conductance via gate control, effectively resolving similar outputs and enhancing separability without retraining. Here, we present dense, large-scale crossbar array architectures incorporating up to 2048 MoS₂ memtransistors per array, achieving >92% yield across multiple arrays while individual memtransistors exh

SUBMITTER: Schranghamer TF 

PROVIDER: S-EPMC12569200 | biostudies-literature | 2025 Oct

REPOSITORIES: biostudies-literature