NIR and SWIR Questions and Answers

What is near infrared (NIR) and shortwave infrared (SWIR)? What are their advantages and suitable applications?

Typically we define near infrared (NIR) from 780 nm to 1400 nm and shortwave infrared (SWIR) from 1400 nm to 3000 nm. But it is also common to refer to the entire range from 780 nm up to 3000 nm as NIR or SWIR.

The NIR/SWIR region has multiple advantages, and some of the most well-known ones are discussed below.

Beyond visible

NIR and SWIR wavelengths aren’t visible to human eyes and have less energy than UV and visible wavelengths, but the light still interacts with objects. So in the case of NIR/SWIR imaging, we can capture images of objects and see aspects that we couldn’t see in the visual range.

In addition, longer wavelengths can be used to look through plastic packaging and silicon, providing another method for nondestructive testing.

Example applications:

  • Automotive
  • Surveillance
  • Remote sensing
  • Wafer inspection
  • Packaging and filling inspection

 

Silicon wafer: (Left) Visible image, (Right) SWIR image.

 

 

Water content measurement

Water has a high absorption rate at 1450 nm and 1900 nm, making it easy to detect areas with high water density using NIR/SWIR.

Example application: Food quality sorting

Food sorting

Identifying contaminants (stones) in coffee beans

Thermal detection

SWIR has the capability to detect heat even though it’s not as sensitive as MWIR (midwave infrared) and LWIR (longwave infrared), which can detect low temperatures. Unlike MWIR and LWIR imaging that blur the contours of objects in an image, SWIR imaging produces clearly defined images with added temperature information, allowing the detection of hot spots in a scene or object.

Example application: Process control

Material differentiation

Between 780-2500 nm, substances such as plastic, organic compounds, and non-organic compounds can be easily differentiated, which is hard to do in the visible range. Hyperspectral SWIR imaging can provide detailed information about an object based on its infrared spectrum.

Example applications:

  • Plastic sorting
  • Agriculture
  • Pharmaceutical inspection

 

Example of hyperspectral imaging

Different plastic types: (Left) Visible image, (Right) After hyperspectral imaging.

How are NIR and SWIR detected?

There are multiple methods and materials to detect NIR and SWIR including InGaAs (indium gallium arsenide), MCT (mercury cadmium telluride), and QDIP (quantum dot infrared photodetector). These three are discussed below.

InGaAs (indium gallium arsenide)

InGaAs is the most well-known material for NIR and SWIR detection. Like silicon photodetectors, InGaAs photodetectors are photovoltaic detectors with a p-n junction, but they have a smaller bandgap energy than silicon, so they detect a longer wavelength range. Standard InGaAs can detect light from 900 nm to 1700 nm, and extended InGaAs can go all the way to 2500 nm. InGaAs detectors are suitable for most NIR/SWIR applications due to their high sensitivity and high linearity.

Pros Cons
High sensitivity Dark current is sensitive to temperature
High linearity  

To see Q&As about InGaAs, click here.

MCT or HgCdTe (mercury cadmium telluride)

MCT detectors use the photoconductive effect, where the resistance value of the detector element decreases when exposed to light. MCTs have a wide bandwidth detection range, typically from 2 µm to 14 µm but can vary within 0.8 µm and 30 µm. They are suitable for wide bandwidth applications that have no RoHS requirement.

Pros Cons
High sensitivity High cost
Wide bandwidth detection Low linearity
  Restricted by RoHS directive
  Typically requires Stirling coolers

QDIP (quantum dot infrared photodetector)

Quantum dots are a new solution for certain NIR/SWIR applications. QDIPs use a layer of quantum dots on a silicon surface to create a three-dimensional quantum confinement active region, enabling the absorption of longer wavelengths. They are suitable for low cost and temperature-critical applications.

Pros Cons
Low cost Low uniformity
Independent from temperature (or no temperature dependence) Low sensitivity
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Meet the engineers

Albert Tu is a marketing engineer working on NIR/SWIR applications. He’s been helping customers find the right solution for their technology, and he’s developing new business by exploring potential technologies. Albert’s experience in high-tech industry and startups allows him to identify the need first and to find the right solution to solve it. Recently, he enjoys cooking in his spare time and likes to try out new recipes.

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