Competing short-wavelength infrared sensing technologies

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The widespread adoption of machine vision makes image sensors}} able to detect light outside the visible spectrum increasingly useful, as the goal is to increase human vision rather than duplicate it. For example, imaging in the short-wave infrared (SWIR) spectral region, which ranges from 1000 to 2000 nm, offers multiple advantages that can complement conventional cameras.

Arguably the most compelling attribute of imaging in the SWIR region is the reduced optical scattering of longer wavelengths of light – a phenomenon that makes sunsets red because moisture droplets scatter the light. blue during the longer path of light in the atmosphere. The reduced scatter means that SWIR cameras on vehicles and drones can see through fog and dust clouds, dramatically improving visibility and therefore safety.

Another advantage of SWIR imaging is to distinguish visually similar materials, which may have similar absorption (and therefore reflection) spectra in the visible region but significant differences in the SWIR region. This capability is invaluable for applications such as quality control in industrial processes, where it can identify unwanted elements such as rocks and metals in food production for example, and sorting and recycling.

Other benefits include thermal imaging for articles with temperature between 200 and 500 ° C and the ability to see through materials that are opaque to visible light but transparent to SWIR. Silicon is a prime example, with SWIR imaging used to verify the quality of wafer fixation.

If SWIR imaging offers all of the benefits described, why is it not more common? The answer is that at present, shortwave infrared (SWIR, 1000-2000nm) imaging is dominated by expensive InGaAs (Indium Gallium Arsenide) sensors that can absorb light down to around 1800nm. These can cost up to $ 10,000 due to the cost of producing the InGaAs layer by vapor deposition, low fabrication yields, and limited pixel density which increases material consumption for resolution. given compared to standard silicon photodetectors.

The combination of commercially desirable attributes and expensive legacy technology creates a clear opportunity for a disruptive, low-cost alternative. As such, several competing approaches for SWIR imaging are under development.

One approach is to extend the sensitivity of silicon photodetectors beyond the usual 1000 nm by increasing their thickness and structuring the surface. Since this “extended silicon” approach can utilize existing CMOS manufacturing technologies, it is likely a durable and relatively inexpensive alternative that applies well to autonomous vehicles and ADAS systems. However, since it is silicon-based, this technology is best suited for detecting light towards the lower end of the SWIR spectral region.

Another method, which will likely be more expensive to produce than “extended silicon” but capable of imaging at longer wavelengths, uses a hybrid structure that includes quantum dots mounted on a CMOS readout integrated circuit (ROIC). ). Quantum dots have highly adjustable absorption spectra which can be controlled by changing their diameter and can absorb light up to 2000nm. This makes them particularly promising for industrial imaging applications and potentially hyperspectral imaging.

The attached graph compares the technological and business readiness level of competing SWIR imaging technologies.

Also included are highly granular 10-year market forecasts by revenue and volume (broken down by technology and application), along with multiple application case studies and technology / business readiness assessments. The report also includes numerous company profiles based on interviews with start-ups and established companies, providing a clear view of the competitive landscape. Further details and sample downloadable pages are available at www.IDTechEx.com/imagesensor.


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