The ChipSense platform from MantiSpectra includes 16 discrete filter-equipped photodetectors covering different parts of the NIR spectrum. [Image: MantiSpectra]
The Netherlands-based deep-tech startup MantiSpectra, which is focusing on development of chip-based NIR spectral sensors for a variety of end markets, said in late September that it had secured €4.0 million (US$4.2 million) in seed funding to “support its mission to revolutionize how we ‘see’ the world around us.”
Spun out from Eindhoven University of Technology (TU/e) in October 2020, MantiSpectra focuses on integrated sensor chips. Rather than taking full spectra, the MantiSpectra chips collect a limited set of NIR spectral measurements (at wavelengths between 850 and 1700 nm) using a discrete array of photodetectors and filters. That limited spectral-data set can then be assembled into a “spectral fingerprint” for use in chemical- and materials-sensing applications in agriculture, health care, industry and other areas—including, eventually, consumer applications.
The company takes its name, and the inspiration for its approach, from the natural example of the mantis shrimp, an invertebrate creature whose eyes have up to 16 photodetectors, each sensitive to a different wavelength band. (Several scientists associated with the company, including its scientific advisor, Andrea Fiore, wrote about the approach in a 2022 feature article in OPN.)
MantiSpectra says its “ChipSense” integrated spectral sensor “replaces and augments traditional bulky spectrometers, enabling compact, portable, and cost-effective material analysis everywhere.” Customers and partners in more than 20 countries—including “three of the world’s top 10 food and beverage companies”—are already using the ChipSense platform, according to the company.
Moving toward mass production
MantiSpectra says it will use the funds from its recent seed round—led by the European deep-tech venture fund Innovation Industries and the Dutch VC firm PhotonVentures—to scale up fabrication of its platform toward mass production, to increase capacity, and to develop database libraries tuned to specific end-user applications.