Purdue researchers unveil miniature computational spectrometer
05-17-2024
The discovery uses artificial intelligence and could revolutionize the way scientists analyze light-matter interactions
Optical spectrometers are essential tools for analyzing light-matter interactions. They are a non-invasive way to measure and study a wide range of materials using wavelengths. The setback for these instruments is that they can be complicated and bulky, and sizing down often means diminished performance. Having a miniature version would revolutionize the industry.
Researchers at Purdue University teamed up with researchers from Hong Kong Polytechnic University to unveil a miniature computational spectrometer that could revolutionize the way scientists analyze light-matter interactions. The high scalability of this technological approach may facilitate the development of high-performance miniature optical spectrometers for extensive applications.
The team, led by Guang Lin, professor of mathematics and mechanical engineering and associate dean for research and innovation in the College of Science, published its findings in Nature Communications in a May article titled, “Miniature computational spectrometry with a plasmonic nanoparticles-in-cavity microfilter array.”
“In this work, we have developed advanced AI algorithms to overcome the trade-off between miniaturizing size and retaining performance,” Lin said. “The high scalability of the technological approaches shown here may facilitate the development of high-performance miniature optical spectrometers for extensive applications.”
The team is made up of Lin and Sheng Zhang, who recently received a doctorate from Purdue University, as well as four researchers from Hong Kong Polytechnic University. The Hong Kong team conceived the plasmonic microfilter array for computational spectrometers, conducted the numerical simulation and optimization, and fabricated the plasmonic microfilter array. The Purdue team designed the machine learning algorithms, developed the codes for spectrum reconstruction, and analyzed the data.
“The spectrometer’s compact size and high scalability make it an ideal candidate for a wide range of applications, from material composition analysis to remote sensing,” Lin explained. “The broader impact of this work lies in its potential to facilitate the development of portable, high-performance optical spectrometers. This could open up new possibilities for on-site measurements and portable tools, expanding the reach of spectroscopy beyond the confines of specialized laboratories.”
There have been multiple attempts to create miniature optical spectrometers over the years, but issues arose with each attempt. The key to this discovery was that the team used artificial intelligence to overcome the issues presented in previous attempts by other researchers. Lin’s research focuses on developing advanced trustworthy AI algorithms and investigating new knowledge discovery to promote innovation with significant potential impact on complex physical and biological complex systems.
“The key to success is the AI in combination with the fabrication of the advanced plasmonic microfilter array, and the optimization of the spectrometer performance,” Lin said. “To resolve the issues, a machine-learning-based AI method was established to enable the spectrometer to use a large-scale plasmonic microfilter array to reconstruct the spectrum of an input light beam from the complementary metal oxide semiconductor (CMOS) image output.”
This discovery is part of ongoing research.The team’s next steps include further improving the AI algorithms and developing a smaller optical spectrometer.
This research was funded in part by the National Science Foundation (DMS-2053746, DMS-2134209, ECCS-2328241, and OAC-2311848).
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Source: Guang Lin, professor of mathematics and mechanical engineering and associate dean for research and innovation, College of Science
Writer: Cheryl Pierce, communications specialist
Photo by: Alisha Referda, communications specialist