Self-Powered Phototriggered Memristor Array with pW-Level Computing for Monolithic in-Sensor Vision.
basic_science · Level V
Where this comes from
- Record sourced from PubMed, PMID 41721621.
- Also identified by DOI 10.1002/adma.202523017.
- No licence information is recorded for this record.
- Because redistribution is not established, this page shows the abstract only. Follow the links below for the full text.
Abstract
2D Ruddlesden-Popper (RP) hybrid perovskites are widely used in the field of optoelectronic devices due to their high carrier mobility and absorption coefficient. Herein, BA<sub>2</sub>MAPb<sub>2</sub>Br<sub>7</sub> (BMPB) single crystals were synthesized via the quasi-static cooling method, with a thorough investigation of the nucleation mechanism and the intrinsic relationship between rectangular and hexagonal morphologies. Remarkably, BMPB exhibits outstanding memristive performance, featuring an ultrahigh on/off ratio (∼10<sup>5</sup>), ultralow power consumption of ∼82.8 pW, and a long retention time (>22 000 s). Leveraging its inherent ferroelectric polarization and optoelectronic properties, we demonstrate a monolithic 5×5 optoelectronic memristor array that unifies sensing, memory, and computing functions. The array device exhibits self-powered performance under 410 nm illumination, with responsivity of 0.96 A/W and detectivity of 2.89×10<sup>8</sup> Jones. Through digital logic circuit design and Vivado verification, we successfully implement solar-tracking time prediction and sunflower growth-stage monitoring. Critically, this integrated architecture enables hardware-level in-sensor computing for real-time applications. Our work provides valuable insights for next-generation in-sensor computing devices, providing a material-level solution based on 2D RP perovskites for energy-efficient AI and IoT systems.