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Lateral Heterostructured Vis–NIR Photodetectors with Multimodal Detection for Rapid and Precise Classification of Glioma

Authors :
Xie, Hongfei
Pan, Qi
Wu, Dongdong
Qin, Feifei
Chen, Shuoran
Sun, Wei
Yang, Xu
Chen, Sisi
Wu, Tingqing
Chi, Jimei
Huang, Zengqi
Wang, Huadong
Zhang, Zeying
Chen, Bingda
Carmeliet, Jan
Su, Meng
Song, Yanlin
Source :
ACS Nano; October 2022, Vol. 16 Issue: 10 p16563-16573, 11p
Publication Year :
2022

Abstract

Precise diagnosis of the boundary and grade of tumors is especially important for surgical dissection. Recently, visible and near-infrared (Vis–NIR) absorption differences of tumors are demonstrated for a precise tumor diagnosis. Here, a template-assisted sequential printing strategy is investigated to construct lateral heterostructured Vis–NIR photodetectors, relying on the up-conversion nanoparticles (UCNPs)/perovskite arrays. Under the sequential printing process, the synergistic effect and co-confinement are demonstrated to induce the UCNPs to cover both sides of the perovskite microwire. The side-wrapped lateral heterogeneous UCNPs/perovskite structure exhibits more satisfactory responsiveness to Vis–NIR light than the common fully wrapped structure, due to sufficient visible-light-harvesting ability. The Vis–NIR photodetectors with Rreaching 150 mA W–1at 980 nm and 1084 A W–1at 450 nm are employed for the rapid classification of glioma. The detection accuracy rate of 99.3% is achieved through a multimodal analysis covering the Vis–NIR light, which provides a reliable basis for glioma grade diagnosis. This work provides a concrete example for the application of photodetectors in tumor detection and surgical diagnosis.

Details

Language :
English
ISSN :
19360851 and 1936086X
Volume :
16
Issue :
10
Database :
Supplemental Index
Journal :
ACS Nano
Publication Type :
Periodical
Accession number :
ejs60960625
Full Text :
https://doi.org/10.1021/acsnano.2c06004