Infrared detectors: Advances, challenges and new technologies

Novel InAs/InGaAs quantum dots-in-a-well (DWELL) infrared photodetectors are reviewed. These detectors, in which the active region consists of InAs quantum dots (QDs) embedded in an InGaAs quantum well, represent a hybrid between a conventional quantum well infrared photodetector (QWIP) and a QD infrared photodetector (QDIP). Like QDIPs, DWELL detectors display normal incidence operation without gratings or optocouplers while demonstrating reproducible ‘dial-in recipes’ for control over the operating wavelength, like QWIPs. Using femtosecond spectroscopy, long carrier lifetimes have been observed in DWELL heterostructures, suggesting their potential for high temperature operation. Moreover, DWELL detectors have also demonstrated bias-tunability and multicolour operation in the mid-wave infrared (3–5 µm), long-wave infrared (LWIR, 8–12 µm) and very long-wave infrared (>14 µm) regimes. We have recently developed LWIR 320 × 256 focal plane arrays operating at liquid nitrogen temperatures. One of the potential problems with these detectors is the low quantum efficiency, which translates into low responsivity and detectivity. Some solutions for mitigating these problems are suggested at the end of this paper.

Quantum-dot infrared photodetectors: Status and outlook

The development of a scalable, low cost, low power, and room temperature operating detector technology capable of high spatial resolution imaging over IR bands of interest can advance and extend space and satellite sensing capabilities such as remote sensing and earth observation. Conventional infrared (IR) band photodetectors based on HgCdTe material operating over short-wave infrared (SWIR), mid-wave infrared (MWIR), and/or long-wave infrared (LWIR) bands often require external cooling to achieve high performance IR sensing and imaging. By integrating bilayers of doped graphene to function as a high mobility channel to aid the recombination of photogenerated carriers, a graphene-enhanced IR photodetector with HgCdTe absorbing layer can be developed providing high performance uncooled detection over SWIR, MWIR, and LWIR (~1.3-14 μm) bands. Development of the high-performance IR photodetector technology involves ptype doping of graphene bilayers deposited on Si/SiO₂ with boron using a spin-on dopant (SOD) process, and then transfer of the doped bilayer graphene onto HgCdTe substrates. The graphene-enhanced HgCdTe SWIR/MWIR/LWIR band detectors were analyzed and characterized material and optoelectronically to demonstrate high performance IR detection at room temperature for advanced NASA Earth Science, defense, and commercial applications.

: Infrared (IR) sensor technology is critical to all phases of ballistic missile defenses. Traditionally, material systems such as indium antimonide (InSb), platinum silicide (PtSi), mercury cadmium telluride (MCT), and arsenic doped silicon (Si: As) have dominated IR detection. Improvement in surveillance sensors and interceptor seekers requires large size, highly uniform and multicolor (or multispectral) IR focal plane arrays involving mid-wave, long-wave and very-long-wave IR regions. Among the competing technologies are the quantum well infrared photodetectors (QWIP) based on lattice matched GaAs/Al GaAs and strained layer InGaAs/AlGaAs material systems. In this paper, a discussion of cooled IR technology with emphasis on QWIP and MCT will be given. Details will be given concerning device physics, material growth, device fabrication, device performance, and cost effectiveness for long wavelength infrared, very long wavelength infrared, and multicolor applications. The conclusion drawn here is that even though QWIP cannot compete with MCT at the single device level, it has potential advantages over MCT for long wavelength and very long wavelength focal plane array applications in term of the array size, uniformity, operability, yield, reliability, and cost of the systems. QWIPs are especially promising for very-long-wave IR at low temperature operation, and when simultaneous multicolor detection using a single focal plane array is desired. Operating a very-long-wave IR focal plane array at low background is a big challenge to both MCT and QWIP, while QWIP has more potential to be realized due to its good device property at low temperature.

In the past five years, significant progress has been accomplished in the reduction of infrared detector pitch and detector size. Recently, longwave infrared (LWIR) detectors in limited quantities have been fabricated with a detector pitch of 5 μm. Detectors with 12-μm pitch are now becoming standard in both midwave infrared (MWIR) and LWIR sensors. Persistent surveillance systems are pursuing 10-μm detector pitch in large format arrays. The fundamental question that most system designers and detector developers desire an answer to is: "How small can you produce an infrared detector and still provide value in performance?" If a system is mostly diffraction-limited, then developing a smaller detector is of limited benefit. If a detector is so small that it does not collect enough photons to produce a good image, then a smaller detector is not much benefit. Resolution and signal-to-noise are the primary characteristics of an imaging system that contribute to targeting, pilotage, search, and other human warfighting task performance. We investigate the task of target discrimination range performance as a function of detector size/pitch. Results for LWIR and MWIR detectors are provided and depend on a large number of assumptions that are reasonable.

A long standing debate has existed on the utility of Mid Wave Infrared (MWIR) vs Long Wave Infrared (LWIR) remote-sensing imagery for Precision Agriculture applications. We have conducted a combined qualitative and quantitative, multi-field, aircraft remote-sensing study to show that LWIR measurements often result in more actionable for day-to-day farm management applications. LWIR imagery when processed with SaraniaSat's nonlinear, weak-signal detection algorithms is an effective predictor of crops stress and ultimate harvest yield. It is also shown that both processed LWIR and MWIR imagery contain actionable, crop-stress information that is absent in the conventional Normalized Difference Vegetation Index (NDVI) that is currently, widely used for Precision Agriculture. Finally, at a simulated 10m ground resolution (satellite remote sensing) it is shown, once again, that LWIR is superior and more actionable.

Biomimetic staring infrared imaging omnidirectional detection technology

We present a new optical system for infrared (IR) image-spectrum integration remote sensing. The purpose to develop this instrument is to find the key spectral characteristics of typical hot target and to explore a new intelligence fusion method for the recognition. When mounted on a two-dimensional rotation stage, it can track the suspected target by image processing, and then get its spectrum to do recognition. It is a dual-band system with long-wave infrared (LWIR) imaging and mid-wave infrared (MWIR) spectrum. An IR dichroic beamsplitter is used to divide wideband incident infrared into LWIR and MWIR. Compared to traditional infrared combined imaging and spectral-analysis instruments, it yields higher sensitivity for measuring the IR spectrum. The sensors for imaging and spectrum detection are separate, so high spatial resolution, frame rate, and spectrum resolution can all be obtained simultaneously.

The intrinsic semiconductor mercury cadmium telluride (Hg1−xCdxTe), a solid solution of HgTe and CdTe, has assumed an ever increasing role in the fabrication of infrared (IR) detectors because its energy gap (0-1.5 eV) can be tailored to match the specific needs of IR detection and fiber optic systems. In photovoltaic focal plane array (FPA) applications, low power consumption, as well as excellent sensitivity at elevated temperatures, have made Hg1−xCdxTe the material of choice for both the midwave IR (MWIR) and longwave IR (LWIR) region.

Current stand-off hyperspectral imaging detection solutions that operate in the mid-wave infrared (MWIR), nominally 2.5 – 5 μm spectral region, are limited by the number of absorption bands that can be addressed. This issue is most apparent when evaluating a scene with multiple absorbers with overlapping spectral features making accurate material identification challenging. This limitation can be overcome by moving to the long wave IR (LWIR) region, which is rich in characteristic absorption features, which can provide ample molecular information in order to perform presumptive identification relative to a spectral library. This work utilises an instrument platform to perform negative contrast imaging using a novel LWIR optical parametric oscillator (OPO) as the source. The OPO offers continuous tuning in the region 5.5 – 9.5 μm, which includes a number of molecular vibrations associated with the target material compositions. Scanning the scene of interest whilst sweeping the wavelength of the OPO emission will highlight the presence of a suspect material and by analysing the resulting absorption spectrum, presumptive identification is possible. This work presents a selection of initial results using the LWIR hyperspectral imaging platform on a range of white powder materials to highlight the benefit operating in the LWIR region compared to the MWIR.

Alternative solutions are desired for mid-wavelength and long-wavelength infrared radiation detection and imaging arrays. We have investigated quantum dot infrared photodetectors (QDIPs) as a possible solution for long-wavelength infrared (8 to 12 {mu}m) radiation sensing. This document provides a summary for work done under the LDRD 'Infrared Detection and Power Generation Using Self-Assembled Quantum Dots'. Under this LDRD, we have developed QDIP sensors and made efforts to improve these devices. While the sensors fabricated show good responsivity at 80 K, their detectivity is limited by high noise current. Following efforts concentrated on how to reduce or eliminate this problem, but with no clear path was identified to the desired performance improvements.

: This is the Final Report of ARO Grant No. DAADl9-02-l-0437. It is a report on the characteristics of(InGa)As/GaAs long-wave (8-12 um) quantum-dot infrared photodetector structures. Pcak responsivities and dctectivitics were measured using a calibrated black body source. The results of this work indicate that for the structures characterized here, the maximum operating temperature is limited to %O5 K. No effort was made in the original design of the device structure for higher temperature operation. For operation at temperatures higher than this, one must investigate other device structures; such structures have been identified and will be the subject of future work. The work reported here has paved the way to the identification of candidate device structures for high operating temperature (HOT) quantum-dot detector

The increasing availability of complex multivariate data yielded by sensor technologies permits qualitative and quantitative data analysis for material characterization. Multivariate data are hard to understand by visual inspection and intuition. Thus, data-driven models are required to derive study-specific insights from large datasets. In the present study, a partial least squares regression (PLSR) model was used for the prediction of elemental concentrations using the mineralogical techniques mid-wave infrared (MWIR) and long-wave infrared (LWIR) combined with data fusion approaches. In achieving the study objectives, the usability of the individual MWIR and LWIR datasets for the prediction of the concentration of elements in a polymetallic sulphide deposit was assessed, and the results were compared with the outputs of low- and mid-level data fusion methods. Prior to low-level data fusion implementation, data filtering techniques were applied to the MWIR and LWIR datasets. The pre-processed data were concatenated and a PLSR model was developed using the fused data. The mid-level data fusion was implemented by extracting features using principal component analysis (PCA) scores. As the models were applied to the MWIR, LWIR, and fused datasets, an improved prediction was achieved using the low-level data fusion approach. Overall, the acquired results indicate that the MWIR data can be used to reliably predict a combined Pb–Zn concentration, whereas LWIR data has a good correlation with the Fe concentration. The proposed approach could be extended for generating indicative element concentrations in polymetallic sulphide deposits in real-time using infrared reflectance data. Thus, it is beneficial in providing elemental concentration insights in mining operations.

Multispectral infrared imaging systems that simultaneously operate in the long-wave infrared (LWIR) and mid-wave infrared (MWIR) bands offer significant advantages for target detection and recognition. However, conventional infrared optical systems rely on bulky multi-element lens assemblies to accommodate incident wavelengths of LWIR and MWIR bands, making it challenging for compact thermal optics design. Here, we propose and experimentally demonstrate an inverse designed infrared metalens capable of simultaneously focusing LWIR and MWIR radiation at wavelengths of 9.5 μm and 4.75 μm with a focal length variation of 1%. In the experiment, the proposed metalens with detector enables a dual-wavelength thermal imaging with a compact size (26 × 26 × 18 mm3) and a light weight (19 g). This work establishes a robust and scalable inverse design strategy for dual-wavelength infrared metalenses and provides a promising route toward compact, integrated, and multifunctional infrared imaging lens.

An infrared (IR) sensor model is validated using experimentally derived peak pixel signal-to-noise ratio (SNR) versus range for detection of either an unresolved or a resolved unmanned aerial vehicle (UAV) target. The model provided estimates the time-averaged peak SNR values for the ranges used in the field collection. A mid-wave infrared (MWIR) camera and a long-wave infrared (LWIR) camera provided the measured data. Commercially available UAVs are flown along a line from the cameras to a clear sky region for background. A laser range finder measures the range at seven stopping points along the path. The data result in five ranges of unresolved target information for the MWIR camera and in four ranges for the LWIR camera. We provide details for using the data collected from the model to match the cameras used in the field collection. Also, the processing used to extract peak SNR versus range from imagery is presented.