Self‐Powered Phototriggered Memristor Array with pW‐Level Computing for Monolithic in‐Sensor Vision

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.

Authors

Institutions

Publication Details

Journal
Advanced Materials
Published
2026-02-21
DOI
https://doi.org/10.1002/adma.202523017
Primary Topic
Perovskite Materials and Applications
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Self‐Powered Phototriggered Memristor Array with pW‐Level Computing for Monolithic in‐Sensor Vision

Yiyun Luo, Ming Deng, Xiaojun Tan, Xiangyu Zhang et al.
Advanced Materials
Perovskite Materials and Applications
article

Self‐Powered Phototriggered Memristor Array with pW‐Level Computing for Monolithic in‐Sensor Vision

Yiyun Luo, Ming Deng, Xiaojun Tan, Xiangyu Zhang, Xu Fang, Zijin Zhao
article en

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.

Advanced MaterialsVol. 38(17)
Shaoxing University (CN), Fudan University (CN)
National Natural Science Foundation of China
Affordable and clean energy
Openalex Percentile: Top 48%
Perovskite Materials and Applications
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Self‐Powered Phototriggered Memristor Array with pW‐Level Computing for Monolithic in‐Sensor Vision — Yiyun Luo, Ming Deng, et al. · Advanced Materials (2026) | TGRS Research Map | TGRS