Hyperspectral quantum-dot image sensors via in-pixel reconfigurable band-alignment

TY - JOUR

T1 - Hyperspectral quantum-dot image sensors via in-pixel reconfigurable band-alignment

AU - Mu, Ge

AU - Bi, Cheng

AU - Zou, Jintao

AU - Liu, Yanfei

AU - Hao, Qun

AU - Tang, Xin

N1 - Publisher Copyright: © The Author(s), under exclusive licence to Springer Nature Limited 2026.

PY - 2026/5

Y1 - 2026/5

N2 - High-resolution short-wave infrared hyperspectral imaging enables non-destructive material identification and imaging through scattering media, paving the way for transformative applications in portable diagnostics, precision agriculture, environmental monitoring and space exploration. However, conventional hyperspectral imagers face a compromise between spatial resolution, spectral resolution and device footprint. Here we report a miniaturized hyperspectral image sensor that mitigates this trade-off by leveraging monolithically integrated, bias-reconfigurable stacked colloidal quantum dot junctions and a bias-programmable spectral reconstruction algorithm. By applying a defined sequence of single-polarity increasing bias voltages, the interfacial band alignment can be tuned, thus mediating the collection of photon-generated carriers in colloidal quantum dot layers with different energy gap. Our imager achieves spatial resolution of 1,280 × 1,024, spectral resolution of 1 nm, reconstruction accuracy of 0.055 nm, peak detectivity above 10¹³ jones and broadband coverage (400–1,700 nm), all within a compact pixel footprint of 15 × 15 µm². The high signal-to-noise ratio and spatial resolution result in accurate reconstruction of hyperspectral image information, enabling food quality monitoring, chemical solvents discrimination and materials identification.

AB - High-resolution short-wave infrared hyperspectral imaging enables non-destructive material identification and imaging through scattering media, paving the way for transformative applications in portable diagnostics, precision agriculture, environmental monitoring and space exploration. However, conventional hyperspectral imagers face a compromise between spatial resolution, spectral resolution and device footprint. Here we report a miniaturized hyperspectral image sensor that mitigates this trade-off by leveraging monolithically integrated, bias-reconfigurable stacked colloidal quantum dot junctions and a bias-programmable spectral reconstruction algorithm. By applying a defined sequence of single-polarity increasing bias voltages, the interfacial band alignment can be tuned, thus mediating the collection of photon-generated carriers in colloidal quantum dot layers with different energy gap. Our imager achieves spatial resolution of 1,280 × 1,024, spectral resolution of 1 nm, reconstruction accuracy of 0.055 nm, peak detectivity above 10¹³ jones and broadband coverage (400–1,700 nm), all within a compact pixel footprint of 15 × 15 µm². The high signal-to-noise ratio and spatial resolution result in accurate reconstruction of hyperspectral image information, enabling food quality monitoring, chemical solvents discrimination and materials identification.

UR - https://www.scopus.com/pages/publications/105033373765

U2 - 10.1038/s41566-026-01860-z

DO - 10.1038/s41566-026-01860-z

M3 - Article

AN - SCOPUS:105033373765

SN - 1749-4885

VL - 20

SP - 523

EP - 531

JO - Nature Photonics

JF - Nature Photonics

IS - 5

ER -