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Tiny chip, big breakthrough in spectral sensing for everyday devices

The invention of a microscopic spectral sensor that can identify myriad materials with unprecedented accuracy is set to overhaul our approach to healthcare, food safety and more.
Two people in a lab working with microscopic spectral sensors, both wearing blue gloves and handling small tools.
Researchers at Aalto University hold a tiny chip, designed to accommodate hundreds of ultra-compact spectral sensors. Photo: Aalto University / Faisal Ahmed and Andreas Liapis

Imagine smartphones that can diagnose diseases, detect counterfeit drugs or warn of spoiled food. Spectral sensing is a powerful technique that identifies materials by analysing how they interact with light, revealing details far beyond what the human eye can see.  

Traditionally, this technology required bulky, expensive systems confined to laboratories and industrial applications. But what if this capability could be miniaturised to fit inside a smartphone or wearable device?

Researchers at Aalto University in Finland have combined miniaturised hardware and intelligent algorithms to create a powerful tool that is compact, cost-effective, and capable of solving real-world problems in areas like healthcare, food safety and autonomous driving.

‘It’s similar to how artists train their eyes to distinguish hundreds of subtle colours,’ explains professor and lead researcher, Zhipei Sun. ‘Our device is ‘trained’ to recognise complex light signatures that are imperceptible to the human eye, achieving a level of precision comparable to the bulky sensors typically found in laboratories.’  

Unlike traditional spectral sensors, which require large optical components like prisms or gratings, this sensor achieves spectral differentiation through its electrical responses to light, making it ideal for integration into small devices. The researchers demonstrated its capability to identify materials directly from their luminescence, including organic dyes, metals, semiconductors and dielectrics.

‘Our innovative spectral sensing approach simplifies challenges in material identification and composition analysis,’ says Xiaoqi Cui, the study’s lead author, who recently defended his doctoral thesis at Aalto University. The remarkable innovation combines tunable optoelectronic interfaces with advanced algorithms, unlocking new possibilities for applications in integrated photonics and beyond.

During its training, the device was exposed to a wide range of light colours, enabling it to "learn" and generate unique electrical fingerprints for each light type. These fingerprints are then decoded by an intelligent algorithm, empowering the sensor to accurately identify materials and analyse their properties based on their interaction with light.

Measuring just 5 micrometres by 5 micrometres –– an area 200 times smaller than the cross-section of a human hair –– the device achieves an extraordinary peak wavelength identification accuracy of ~0.2 nanometers, enabling it to distinguish thousands of colours. At the core of this sensor is a carefully designed optoelectronic interface that enables precise control of electrical flow through voltage adjustments. This exceptional tunability allows the sensor to interact with light in multiple distinct ways, producing a “multi-dimensional photoresponse”.  

‘This work is a major step forward in bringing spectroscopic identification to everyone’s fingertips,’ explains doctoral researcher and joint first author, Fedor Nigmatulin. “By integrating this ultra-compact hardware with intelligent algorithms, we’ve taken a significant step toward miniature, portable spectrometers that could one day transform consumer electronics.”

With its groundbreaking performance, tunable design and versatility, the research team hopes that this tiny sensor will soon bring the power of advanced spectroscopy into the devices we use every day.

The article was published online on 22nd January 2025.
Science Advances, DOI: doi.org/10.1126/sciadv.ado6886

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A fingertip-sized on-chip spectrometer in the foreground compared to a commercial benchtop-size spectrometer in the background. Photo: Aalto University
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