A high resolution spectrometer which is part of smartphones

Color, like the way in which the wavelength of light is perceived by the human eye, goes beyond a simple aesthetic element, containing important scientific information such as the composition or the state of a substance.

Spectrometers are optical devices that analyze the properties of materials by breaking down light in its constituent wavelengths, and they are widely used in various scientific and industrial fields, including material analysis, detection of chemical components and research in life sciences.

The high resolution spectrometers were large and complex, which makes them difficult to use daily. However, thanks to the ultra-compact and high resolution spectrometer developed by KAIST researchers, Light color information can now be used can be used even in smartphones or portable devices.

Professor Mooseok Jang’s research team in the Biography and Brain Engineering Department has successfully developed a reconstruction -based spectrometer technology using dual -layer disorderly metasurfaces. The work is published in Scientific advances.

The existing high resolution spectrometers have an important factor, of the order of tens of centimeters and require complex calibration processes to maintain precision. This is fundamentally resulting from the operating principle of traditional dispersive elements, such as networks and prisms, which separate the wavelengths of light along the propagation direction, just like a rainbow separates colors.

Consequently, despite the potential that Light’s colors is widely useful in daily life, spectroscopic technology has been limited to laboratory or industrial manufacturing environments.

The research team has designed a method which deviates from the conventional spectroscopic paradigm of the use of diffraction networks or prisms, which establish an individual correspondence between Light’s color information and its sense of propagation, using disorderly structures designed as optical components.

In this process, they have used metasurfacces, which can freely control the process of light propagation using dozens of tens to hundreds of nanometers, to accurately implement “complex random models (Speckle)”.

More specifically, they have developed a method that implies the implementation of a dual -layer disorderly metasurface to generate patterns of specific stains in wavelength, then rebuild precise color information (wavelength) of light from the random patterns measured by a camera.

Consequently, they have successfully developed a new concept spectrometer technology which can precisely measure light through a wide range of visible infrared (440–1 300 nm) with high resolution of 1 nanometer (NM) in a smaller device than a nail (less than 1 cm) using a single image capture.

Dong-Gu Lee, a main author of this study, said: “This technology is implemented in a manner directly integrated into commercial image sensors, and we expect it to allow easy acquisition and use of light wavelength information in daily life when it is integrated into mobile devices in the future.”

Professor Mooseok Jang said: “This technology overcomes the limits of the fields of vision machine with existing RGB colors, which distinguish and recognize only three color components (red, green, blue) and has various applications.

“We are planning various research applied for this technology, which widens the horizon of technology at the laboratory level to Vision Machine technology on a daily basis for applications such as food components, crop health diagnosis, skin health measurement, environmental pollution detection and organic / medical diagnostics.

“In addition, it can be extended to various advanced optical technologies such as hyperspectral imagery, which records the wavelength and spatial information simultaneously with high -resolution 3D optical trapping technology, which precisely controls the light of several wavelengths in the desired forms and ultra -fast imaging technology, which captures the phenomenon in very short periods.”

This research was directed in collaboration by Dong-Gu Lee (candidate PH.D.) and Gokho Song (candidate Ph.D.) of the Kaist department of organic engineering and the brain as co-prirs.