The paper reports on a long-wave infrared (cut-off wavelength ~ 9 μm) HgCdTe detector operating under nbiased condition and room temperature (300 K) for both short response time and high detectivity operation. The ptimal structure in terms of the response time and detectivity versus device architecture was shown. The response time of the long-wave (active layer Cd composition, xCd = 0.19) HgCdTe detector for 300 K was calculated at a level of τs ~ 1 ns for zero bias condition, while the detectivity − at a level of D* ~ 109 cmHz1/2/W assuming immersion. It was presented that parameters of the active layer and P+ barrier layer play a critical role in order to reach τs ≤ 1 ns. An extra series resistance related to the processing (RS+ in a range 5−10 Ω) increased the response time more than two times (τs ~ 2.3 ns).

In this work we report simulation and experimental results for an MWIR HgCdTe photodetector designed by computer simulation and fabricated in a joint laboratory run by VIGO Sytems S.A. and Military University of Technology. The device is based on a modified N+pP+ heterostructure grown on 2”., epiready, semi-insulating (100) GaAs substrates in a horizontal MOCVD AIX 200 reactor.

The devices were examined by measurements of spectral and time responses as a function of a bias voltage and operating temperatures. The time response was measured with an Optical Parametric Oscillator (OPO) as the source of ~25 ps pulses of infrared radiation, tuneable in a 1.55–16 μm spectral range. Two-stage Peltier cooled devices (230 K) with a 4.1 μm cut-off wavelength were characterized by 1.6 × 1012 cm Hz1/2/W peak detectivity and < 1 ns time constant for V > 500 mV.

Accurate determination of material parameters, such as carrier lifetimes and defect activation energy, is a significant problem in the technology of infrared detectors. Among many different techniques, using the time resolved photoluminescence spectroscopy allows to determine the narrow energy gap materials, as well as their time dynamics. In this technique, it is possible to observe time dynamics of all processes in the measured sample as in a streak camera. In this article, the signal processing for the above technique for Hg(1-x)CdxTe with a composition x of about 0.3 which plays an extremely important role in the mid-infrared is presented. Machine learning algorithms based on the independent components analysis were used to determine components of the analyzed data series. Two different filtering techniques were investigated. In the article, it is shown how to reduce noise using the independent components analysis and what are the advantages, as well as disadvantages, of selected methods of the independent components analysis filtering. The proposed method might allow to distinguish, based on the analysis of photoluminescence spectra, the location of typical defect levels in HgCdTe described in the literature.