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Stretchable colour-sensitive quantum dot nanocomposites for shape-tunable multiplexed phototransistor arrays

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Abstract
High-performance photodetecting materials with intrinsic stretchability and colour sensitivity are key requirements for the development of shape-tunable phototransistor arrays. Another challenge is the proper compensation of optical aberrations and noises generated by mechanical deformation and fatigue accumulation in a shape-tunable phototransistor array. Here we report rational material design and device fabrication strategies for an intrinsically stretchable, multispectral and multiplexed 5 x 5 x 3 phototransistor array. Specifically, a unique spatial distribution of size-tuned quantum dots, blended in a semiconducting polymer within an elastomeric matrix, was formed owing to surface energy mismatch, leading to highly efficient charge transfer. Such intrinsically stretchable quantum-dot-based semiconducting nanocomposites enable the shape-tunable and colour-sensitive capabilities of the phototransistor array. We use a deep neural network algorithm for compensating optical aberrations and noises, which aids the precise detection of specific colour patterns (for example, red, green and blue patterns) both under its flat state and hemispherically curved state (radius of curvature of 18.4 mm). Intrinsically stretchable quantum-dot-based semiconducting nanocomposites enable the realization of shape-tunable and colour-sensitive phototransistor arrays.
Author(s)
Song, Jun-KyulKim, JunheeYoon, JiyongKoo, Ja HoonJung, HyunjinKang, KyuminSunwoo, Sung-HyukYoo, SeungwonChang, HogeunJo, JinwoungBaek, WoonhyukLee, SanghwaLee, MincheolKim, Hye JinShin, MikyungYoo, Young JinSong, Young MinHyeon, TaeghwanKim, Dae-HyeongSon, Donghee
Issued Date
2022-08
Type
Article
DOI
10.1038/s41565-022-01160-x
URI
https://scholar.gist.ac.kr/handle/local/10700
Publisher
Nature Publishing Group
Citation
Nature Nanotechnology, v.17, no.8, pp.849 - 856
ISSN
1748-3387
Appears in Collections:
Department of Electrical Engineering and Computer Science > 1. Journal Articles
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