Optoelectronic polymer memristors with dynamic control for power-efficient in-sensor edge computing.

ABSTRACT: As the demand for edge platforms in artificial intelligence increases, including mobile devices and security applications, the surge in data influx into edge devices often triggers interference and suboptimal decision-making. There is a pressing need for solutions emphasizing low power consumption and cost-effectiveness. In-sensor computing systems employing memristors face challenges in optimizing energy efficiency and streamlining manufacturing due to the necessity for multiple physical processing components. Here, we introduce low-power organic optoelectronic memristors with synergistic optical and mV-level electrical tunable operation for a dynamic "control-on-demand" architecture. Integrating signal sensing, featuring, and processing within the same memristors enables the realization

SUBMITTER: Zhou J 

PROVIDER: S-EPMC12420826 | biostudies-literature | 2025 Sep

REPOSITORIES: biostudies-literature