High‐Performance Self‐Powered Organic Photodetectors for Near‐Infrared Weak Light Detection

Near-infrared (NIR) organic photodetectors (OPDs) have significant potential in the development of night vision, optical communication, and image-sensing systems. However, most of them require external energy consumption, and particularly the investigation focuses on weak light detection in the NIR region at or beyond 1000 nm remains limited. In this study, self-powered OPDs with a PCE10:COTIC-4F organic bulk heterojunction as the photoactive layer are designed, which are capable of responding to an ultra-weak light signal of 6.3 pW cm<sup>-2</sup> at 1000 nm, demonstrating a significantly low level in comparison to currently reported OPDs. In addition, the OPDs also exhibit other outstanding photodetection performance, including large I<sub>light</sub>/I<sub>dark</sub> ratio of 3.47 × 10<sup>6</sup>, high responsivity of 1.50 A W<sup>-1</sup>, and detectivity of 3.17 × 10<sup>13</sup>/1.80 × 10<sup>11</sup> Jones (evaluated by dark/noise current methods). Furthermore, the unencapsulated OPDs demonstrate almost no obvious attenuation in the air during a 224-day test and in the aging environment during a 67-day test. More importantly, the self-powered OPDs demonstrate the potential for flexible electronics, NIR imaging, and NIR selectivity with visible-blind characteristic. The development of self-powered OPDs provides an accessible and viable route for advancing weak NIR detection.

Authors

Institutions

Publication Details

Journal
Small
Published
2025-04-03
DOI
https://doi.org/10.1002/smll.202501140
Citations
8
Primary Topic
Conducting polymers and applications
Type
article
Field-Weighted Citation Impact
4.85

Funders

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

High‐Performance Self‐Powered Organic Photodetectors for Near‐Infrared Weak Light Detection

Xinglei Zhao, Jia Dong Huang, Xu Liu, Junyao Zhang et al.
8 citations
Small
Conducting polymers and applications
4.85
article

High‐Performance Self‐Powered Organic Photodetectors for Near‐Infrared Weak Light Detection

Xinglei Zhao, Jia Dong Huang, Xu Liu, Junyao Zhang, Yi Ye, Haixia Liang, Gonghai Yang, Li Li
article en
8 citations

Abstract

Near-infrared (NIR) organic photodetectors (OPDs) have significant potential in the development of night vision, optical communication, and image-sensing systems. However, most of them require external energy consumption, and particularly the investigation focuses on weak light detection in the NIR region at or beyond 1000 nm remains limited. In this study, self-powered OPDs with a PCE10:COTIC-4F organic bulk heterojunction as the photoactive layer are designed, which are capable of responding to an ultra-weak light signal of 6.3 pW cm<sup>-2</sup> at 1000 nm, demonstrating a significantly low level in comparison to currently reported OPDs. In addition, the OPDs also exhibit other outstanding photodetection performance, including large I<sub>light</sub>/I<sub>dark</sub> ratio of 3.47 × 10<sup>6</sup>, high responsivity of 1.50 A W<sup>-1</sup>, and detectivity of 3.17 × 10<sup>13</sup>/1.80 × 10<sup>11</sup> Jones (evaluated by dark/noise current methods). Furthermore, the unencapsulated OPDs demonstrate almost no obvious attenuation in the air during a 224-day test and in the aging environment during a 67-day test. More importantly, the self-powered OPDs demonstrate the potential for flexible electronics, NIR imaging, and NIR selectivity with visible-blind characteristic. The development of self-powered OPDs provides an accessible and viable route for advancing weak NIR detection.

SmallVol. 21(21)
Tongji University (CN), China National Petroleum Corporation (China) (CN)
National Natural Science Foundation of China, National Key Research and Development Program of China
Affordable and clean energy
Openalex Percentile: Top 5%
Conducting polymers and applications
4.85
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.