Woo-Yong Jang

Reduction in dark current using resonant tunneling barriers in quantum dots-in-a-well long wavelength infrared photodetector

We report the use of resonant tunneling (RT) assisted barriers to reduce the dark current in quantum dots-in-a-well (DWELL) infrared photodetectors. Designed RT barriers allow energy-selective extraction of photoexcited carriers while blocking a continuum of energies. Over two orders of magnitude reduction in the dark current in the RT-DWELL device over a control sample without RT-DWELL at 77K has been demonstrated. Specific detectivity (D*) of 3.6×109cmHz1∕2W−1 at 77K at λpeak=11μm with a conversion efficiency of 5.3% was obtained in the RT-DWELL device. D* for the RT-DWELL device is five times higher than that of the control sample.

Demonstration of Bias-Controlled Algorithmic Tuning of Quantum Dots in a Well (DWELL) MidIR Detectors

The quantum-confined Stark effect in intersublevel transitions present in quantum-dots-in-a-well (DWELL) detectors gives rise to a midIR spectral response that is dependent upon the detectors operational bias. The spectral responses resulting from different biases exhibit spectral shifts, albeit with significant spectral overlap. A postprocessing algorithm was developed by Sakoglu that exploited this bias-dependent spectral diversity to predict the continuous and arbitrary tunability of the DWELL detector within certain limits. This paper focuses on the experimental demonstration of the DWELL-based spectral tuning algorithm. It is shown experimentally that it is possible to reconstruct the spectral content of a target electronically without using any dispersive optical elements for tuning, thereby demonstrating a DWELL-based algorithmic spectrometer. The effects of dark current, detector temperature, and bias selection on the tuning capability are also investigated experimentally.

Versatile Spectral Imaging With an Algorithm-Based Spectrometer Using Highly Tuneable Quantum Dot Infrared Photodetectors

We report on the implementation of an algorithm-based spectrometer capable of reconstructing the spectral shape of materials in the mid-wave infrared (MWIR) and long-wave infrared (LWIR) wavelengths using only experimental photocurrent measurements from quantum dot infrared photodetectors (QDIPs). The theory and implementation of the algorithm will be described, followed by an investigation into this algorithmic spectrometers performance. Compared to the QDIPs utilized in an earlier implementation, the ones used here have highly varying spectral shapes and four spectral peaks across the MWIR and LWIR wavelengths. It has been found that the spectrometer is capable of reconstructing broad spectral features of a range of bandpass infrared filters between wavelengths of 4 and 12 as well as identifying absorption features as narrow as 0.3 in the IR spectrum of a polyethylene sheet.

Multispectral Classification With Bias-Tunable Quantum Dots-in-a-Well Focal Plane Arrays

Mid-wave and long-wave infrared (IR) quantum-dots-in-a-well (DWELL) focal plane arrays (FPAs) are promising technology for multispectral (MS) imaging and sensing. The DWELL structure design provides the detector with a unique property that allows the spectral response of the detector to be continuously, albeit coarsely, tuned with the applied bias. In this paper, a MS classification capability of the DWELL FPA is demonstrated. The approach is based upon: 1) imaging an object repeatedly using a sequence of bias voltages in the tuning range of the FPA and then 2) applying a classification algorithm to the totality of readouts, over multiple biases, at each pixel to identify the “class” of the material. The approach is validated for two classification problems: separation among different combinations of three IR filters and discrimination between rocks. This work is the first demonstration of the MS classification capability of the DWELL FPA.

Data compressive paradigm for multispectral sensing using tunable DWELL mid-infrared detectors

While quantum dots-in-a-well (DWELL) infrared photodetectors have the feature that their spectral responses can be shifted continuously by varying the applied bias, the width of the spectral response at any applied bias is not sufficiently narrow for use in multispectral sensing without the aid of spectral filters. To achieve higher spectral resolutions without using physical spectral filters, algorithms have been developed for post-processing the DWELLs bias-dependent photocurrents resulting from probing an object of interest repeatedly over a wide range of applied biases. At the heart of these algorithms is the ability to approximate an arbitrary spectral filter, which we desire the DWELL-algorithm combination to mimic, by forming a weighted superposition of the DWELLs non-orthogonal spectral responses over a range of applied biases. However, these algorithms assume availability of abundant DWELL data over a large number of applied biases (>30), leading to large overall acquisition times in proportion with the number of biases. This paper reports a new multispectral sensing algorithm to substantially compress the number of necessary bias values subject to a prescribed performance level across multiple sensing applications. The algorithm identifies a minimal set of biases to be used in sensing only the relevant spectral information for remote-sensing applications of interest. Experimental results on target spectrometry and classification demonstrate a reduction in the number of required biases by a factor of 7 (e.g., from 30 to 4). The tradeoff between performance and bias compression is thoroughly investigated.

Comparison of Quantum Dots-in-a-Double-Well and Quantum Dots-in-a-Well Focal Plane Arrays in the Long-Wave Infrared

Our previous research has reported on the development of the first generation of quantum dots-in-a-well (DWELL) focal plane arrays (FPAs), which are based on InAs quantum dots (QDs) embedded in an InGaAs well having GaAs barriers, which have demonstrated spectral tunability via an externally applied bias voltage. More recently, technologies in DWELL devices have been further advanced by embedding InAs QDs in InGaAs and GaAs double wells with AlGaAs barriers, leading to a less strained InAs/InGaAs/GaAs/AlGaAs heterostructure. These lower strain quantum dots-in-a-double-well devices exhibit lower dark current than the previous generation DWELL devices while still demonstrating spectral tunability. This paper compares two different configurations of double DWELL (DDWELL) FPAs to a previous generation DWELL detector and to a commercially available quantum well infrared photodetector (QWIP). All four devices are 320 × 256 pixel FPAs that have been fabricated and hybridized with an Indigo 9705 read-out integrated circuit. Radiometric characterization, average array responsivity, array uniformity and measured noise equivalent temperature difference for all four devices is computed and compared at 60 K. Overall, the DDWELL devices had lower noise equivalent temperature difference and higher uniformity than the first-generation DWELL devices, although the commercially available QWIP has demonstrated the best performance.

Analysis of subwavelength metal hole array structure for the enhancement of back-illuminated quantum dot infrared photodetectors

This paper is focused on analyzing the impact of a two-dimensional metal hole array structure integrated to the back-illuminated quantum dots-in-a-well (DWELL) infrared photodetectors. The metal hole array consisting of subwavelength-circular holes penetrating gold layer (2D-Au-CHA) provides the enhanced responsivity of DWELL infrared photodetector at certain wavelengths. The performance of 2D-Au-CHA is investigated by calculating the absorption of active layer in the DWELL structure using a finite integration technique. Simulation results show that the performance of the DWELL focal plane array (FPA) is improved by enhancing the coupling to active layer via local field engineering resulting from a surface plasmon polariton mode and a guided Fabry-Perot mode. Simulation method accomplished in this paper provides a generalized approach to optimize the design of any type of couplers integrated to infrared photodetectors. Experimental results demonstrate the enhanced signal-to-noise ratio by the 2D-Au-CHA integrated FPA as compared to the DWELL FPA. A comparison between the experiment and the simulation shows a good agreement.

Enhanced normal incidence photocurrent in quantum dot infrared photodetectors

The authors report an enhancement in the photocurrent caused by normal incidence (s-polarization) radiation in a quantum dot-in-a-well (DWELL) based infrared photodetector. The s-to-p polarization ratio was increased to 50%, compared to the 20% in conventional quantum dot (QD) detectors. This improvement was achieved through engineering the dot geometry and the quantum confinement via postgrowth capping materials of the QDs. The effect of the capping procedures was determined by examining the dot geometry using transmission electron microscopy (TEM) and s-to-p ratio of the polarized photocurrent in the DWELL infrared photodetector. The TEM image shows a quantum dot with a reduced base of 12 nm and an increased height of 8 nm. The infrared photodetector fabricated from this material shows peak photodetectivities of 1×109 cm Hz1/2/W at 77 K for a peak wavelength of 4.8 μm and 1×107 cm Hz1/2/W at 300 K for a peak wavelength of 3.2 μm. The dark current density is as low as 2×10−4 A/cm2 and the photoconductive...

High Operating Temperature Quantum-Dot Infrared Photodetector Using Advanced Capping Techniques

We demonstrate an improvement in the operating temperature of a quantum dot-in-a-well (DWELL)-based infrared photodetector with spectral response observable till 250 K. This improvement was achieved through engineering the dot geometry and the quantum confinement via postgrowth capping of the quantum dots (QDs) by selecting overlying materials under various growth conditions. The effect of the capping procedures was determined by examining the optical properties of the QDs. These were then introduced into the active region of a DWELL IR photodetector. Using this approach, the dark current density is as low as 6.3 × 10^-7 A/cm² (V_b = 7 V) at 77 K; the highest operating temperature is increased to 250 K with the λ_p = 3.2 μm. The peak detectivity is found to be 1 × 10⁹ cm·Hz^1/2 /W at 77 K and 7.2 × 10⁷ cm·Hz^1/2/W at 250 K.

Joint spatio-spectral based edge detection for multispectral infrared imagery

Image segmentation is one of the most important and difficult tasks in digital image processing. It represents a key stage of automated image analysis and interpretation. Segmentation algorithms for gray-scale images utilize basic properties of intensity values such as discontinuity and similarity. However, it is possible to enhance edge-detection capability by means of using spectral information provided by multispectral (MS) or hyperspectral (HS) imagery. In this paper we consider image segmentation algorithms for multispectral images with particular emphasis on detection of multi-color or multispectral edges. More specifically, we report on an algorithm for joint spatio-spectral (JSS) edge detection. By joint we mean simultaneous utilization of spatial and spectral characteristics of a given MS or HS image. The JSSbased edge-detection approach, termed Spectral Ratio Contrast (SRC) edge-detection algorithm, utilizes the novel concept of matching edge signatures. The edge signature represents a combination of spectral ratios calculated using bands that enhance the spectral contrast between the two materials. In conjunction with a spatial mask, the edge signature give rise to a multispectral operator that can be viewed as a threedimensional extension of the mask. In the extended mask, the third (spectral) dimension of each hyper-pixel can be chosen independently. The SRC is verified using MS and HS imagery from a quantum-dot in a well infrared (IR) focal plane array, and the Airborne Hyperspectral Imager.