Ultrasensitive imaging-based sensor unlocked by differential guided-mode resonance

Zhenchao Liu, Houxin Fan, Tingbiao Guo (), Qin Tan, Zhi Zhang, Yuwei Sun, Julian Evans, Junbo Liang, Ruili Zhang and Sailing He ()
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Zhenchao Liu: Zhejiang University (ZJU)
Houxin Fan: Zhejiang University (ZJU)
Tingbiao Guo: Zhejiang University (ZJU)
Qin Tan: Zhejiang University (ZJU)
Zhi Zhang: Zhejiang University (ZJU)
Yuwei Sun: Zhejiang University (ZJU)
Julian Evans: Zhejiang University (ZJU)
Junbo Liang: Zhejiang University
Ruili Zhang: Zhejiang University
Sailing He: Zhejiang University (ZJU)

Nature Communications, 2025, vol. 16, issue 1, 1-10

Abstract: Abstract Imaging-based sensors convert physicochemical parameters of analytes into visible patterns, yet a high sensitivity remains constrained. Here, we introduce the concept of differential guided-mode resonance with thickness modulation at a tens-nanometer scale to greatly enhance the sensitivity, alleviating the sensitivity-dynamic range tradeoff. Experimental results reveal a sensitivity of up to a million-level pixels per refractive index unit (RIU), surpassing existing technologies by nearly three orders of magnitude, with a large dynamic range reconfigured by the incident angle. With the present method, a moderate value (about 100) of the Q factor suffices to make a record high sensitivity and the Figure of Merit (FOM) can reach 104 RIU−1 level. We also demonstrate a portable device, highlighting its potential for practical applications, including 2D distribution sensing. This method unlocks the potential of imaging-based sensors with both record high sensitivity and tremendous dynamic range for accurate medical diagnosis, biochemical analysis, dynamic pollution monitoring, etc.

Date: 2025
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DOI: 10.1038/s41467-025-60947-3

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