Thermoelectric infrared sensors
There are endless applications for infrared sensors and arrays (cameras), examples such as obstacle detection, night vision, circuit debugging, preventative maintenance, industrial diagnosis, and medical surgery are just a few of the current uses.
In the past, IR cameras have been quite expensive and bulky, but new microfabrication technology and advancement in the materials is constantly reducing the cost which is why in just the past few years passive IR sensors have become available to the average consumer and light industry.
There are two main types of infrared sensors: photon and thermal. In our lab, we study thermal specifically, which involves radiant heating of a part of the sensor as a means of detecting IR light. Since mid range IR (thermal IR) light can radiantly heat objects easily, uncooled sensors are often designed to have an IR absorber and sensor element that is thermally isolated from its surroundings and support in an effort to provide maximum temperature change upon absorbing IR light. This heat change or difference is then transduced to electricity in one of three ways; by changing of resistance in a conductor as in a thermistor, by direct energy conversion as in a thermocouple, or by spontaneous polarization phenomenon (pyroelectric effect) which happens when a pyroelectric material experiences a change in temperature.
In our lab we are trying to come up with new materials and fabrication processes to enhance the performance of passive IR sensors while at the same time trying to reduce the manufacturing cost in an effort to keep the sensor design practical.
The whole idea in any uncooled infrared detector is to have a good thermal isolation between the absorber and the substrate.
However, when we make the thermoelectric wires very long and thin, we also lower the natural resonance frequencies of the structure. This might be a problem if these resonance modes have frequencies close to the detector working bandwidth. Why? because silicon is a piezo-resistive material. When the detector starts resonating, it will generate undesired signals in the output. If these unwanted signals cannot be filtered out, then we are in serious problem.
This simulation shows the lowest resonace frequency of an uncooled thermoelectrc infrared detector.
This MATLAB code calculates the complex refractive index of a substrate. This code is written to find these values from the measured reflection and transmission spectra (at normal incident angle, but it can be modified for an oblique angle) using a FTIR system. The knowledge of the substrate thickness is required. A starting point is also required .
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This code calculates the complex refractive index of a thin film deposited on a transparent substrate. The assumption here is coherent reflection in the thin film and incoherent propagation in the substrate. The IR reflection and transmission spectra are required. Thin film, and substrate thickness along with the n,k info for the substrate are requried. The n, k data for the substrate can be calculated using the above code.
This code calculates reflection, transmission and absorption spectra through a multilayer thin film stack. If the films are deposited on a substrate, the effect of incoherent transmission through the substrate can be simply taken into account. If there is no substrate, the required spectra can be still calculated. There is no limit on the number of the layers that can be added. Even metal films can be included in the simulation (This is actually what we did, we were investigating the effect of metallic thin films in the absorption of IR radiation).
More info (a good source book for this kind of stuff) is inside the main file.
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