Sunday, February 9, 2025

Making Spectral Sensors Smaller And Cheaper

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Researchers at Aalto University have developed a spectral sensor small enough to fit into a smartphone or wearable device.

A schematic of optical sensor (PC: X. Cui et al.)
A schematic of optical sensor (PC: X. Cui et al.)

The human eye has limits—it cannot differentiate between normal and cancerous tissue, detect air pollutants, or identify nutrient deficiencies in crops. To address these tasks, tools like spectral sensing analyze how materials, biomarkers, or tissues interact with light, enabling identification. However, existing spectral sensing systems are complex and expensive, limiting their use to research labs and industrial settings.

Researchers at Aalto University in Finland are advancing spectral sensing technology. By combining miniaturized hardware with algorithms, they have developed a spectral sensor small enough to fit into a smartphone or wearable device. The sensor measures 5 micrometres by 5 micrometres—about 200 times smaller than the cross-section of a human hair. It distinguishes thousands of colours with a wavelength identification accuracy of 0.2 nanometers, allowing it to identify organic dyes, metals, semiconductors, and dielectrics.

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Unlike traditional spectral sensors that rely on optical components like prisms or gratings, this sensor uses electrical responses to light for spectral differentiation. This design reduces its size and cost and makes integrating everyday devices easier. The device exposes the sensor to different light colours during training, generating unique electrical fingerprints for each type of light, which algorithms decode. This eliminates the need for optical components, making the sensor suitable for portable and scalable applications.

The sensor identified unknown wavelengths in lab tests with a wavelength identification accuracy of 0.19 nanometers in free-space applications. When integrated with a silicon waveguide, its accuracy was 2.45 nanometers. The system also classified the spectral fingerprints of substances such as organic dyes, metals, and semiconductors with high certainty. While the results show promise, researchers acknowledge challenges, including electrical noise, miniaturization, and material variability, which must be addressed as the technology moves from the lab to commercial use, where consistent performance is essential.

Nidhi Agarwal
Nidhi Agarwal
Nidhi Agarwal is a Senior Technology Journalist at EFY with a deep interest in embedded systems, development boards and IoT cloud solutions.

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