Multispectral Detectors Research Articles

Spray‐Stencil Lithography Enabled Large‐Scale Fabrication of Multispectral Colloidal Quantum‐Dot Infrared Detectors

AbstractInfrared HgTe colloidal quantum dots (CQDs) are attracting great interest due to their synthesis scalability, mechanical flexibility, wide spectrum tunability, and excellent photoelectric properties. However, traditional HgTe CQD infrared detector fabrication methods such as drop casting and spin coating cannot achieve spatial control of patterned CQD films, which limits their sensing range to just single waveband and greatly hinders the realization of pixelated or multispectral CQD detectors. In this paper, an efficient spray‐stencil lithography technique is demonstrated for the scalable fabrication of multichannel HgTe CQD infrared detectors that can respond to different spectral ranges. Uniform and smooth CQD films can be deposited on rigid, flexible, and curved substrates up to 4 inch wafer. Both photoconductive and photovoltaic infrared HgTe CQD detectors are fabricated with peak D* above 1011 Jones across short‐wave and mid‐wave regions and show infrared imaging with noise equivalent temperature difference down to 26.7 mK. Flexible multispectral detectors with six channels are fabricated by the proposed spray‐stencil lithography method, and experimentally demonstrate spectral sensing and chemical analysis capability. It is believed that the proposed fabrication method provides a reliable scheme for the production of high‐performance multispectral CQD infrared detector arrays.

Detection of moisture and carotenoid content in carrot slices during hot air drying based on multispectral imaging equipment with selected wavelengths

Abstract Moisture content and carotenoid content are important indicators for evaluating the drying process of carrot slices. There are growing attention to develop non-destructive methods as effectively analytical tools in quality assurance of drying carrot slices. In this study, the characteristic wavelengths of moisture and carotenoid content in carrot slices during hot air drying were extracted based on hyperspectral imaging technology. A multispectral imaging equipment was built after that, and the wavelengths of filters were determined according to the characteristic wavelengths. Based on the successive projection algorithm (SPA), the optimal wavelengths of moisture and carotenoid content were further determined, and prediction models of both were established based on the system. There were 12 filters selected in this study. The results showed that a support vector machine (SVM) prediction model for moisture content was established based on seven optimal wavelengths with 0.991 for the coefficient of determination of prediction set (R 2 p ) and 10.318 for the residual prediction residual (RPD). Based on eight optimal wavelengths, a SVM prediction model for carotenoid content was also established with 0.968 for R 2 p and 5.337 for RPD. The prediction performance is close to or even better than that based on hyperspectral. The study confirmed the feasibility of using the multispectral imaging equipment to measure the moisture and carotenoid content of carrot slices during drying based on selected wavelengths, laying a foundation for the further preparation of a portable multispectral detector for the quality of dry products.

Multispectral camouflage for infrared, visible, lasers and microwave with radiative cooling

Interminable surveillance and reconnaissance through various sophisticated multispectral detectors present threats to military equipment and manpower. However, a combination of detectors operating in different wavelength bands (from hundreds of nanometers to centimeters) and based on different principles raises challenges to the conventional single-band camouflage devices. In this paper, multispectral camouflage is demonstrated for the visible, mid-infrared (MIR, 3–5 and 8–14 μm), lasers (1.55 and 10.6 μm) and microwave (8–12 GHz) bands with simultaneous efficient radiative cooling in the non-atmospheric window (5–8 μm). The device for multispectral camouflage consists of a ZnS/Ge multilayer for wavelength selective emission and a Cu-ITO-Cu metasurface for microwave absorption. In comparison with conventional broadband low emittance material (Cr), the IR camouflage performance of this device manifests 8.4/5.9 °C reduction of inner/surface temperature, and 53.4/13.0% IR signal decrease in mid/long wavelength IR bands, at 2500 W ∙ m−2 input power density. Furthermore, we reveal that the natural convection in the atmosphere can be enhanced by radiation in the non-atmospheric window, which increases the total cooling power from 136 W ∙ m−2 to 252 W ∙ m−2 at 150 °C surface temperature. This work may introduce the opportunities for multispectral manipulation, infrared signal processing, thermal management, and energy-efficient applications.

Organic-based photodetectors for multiband spectral imaging

Using organic photodetectors for multispectral sensing is attractive due to their unique capabilities to tune spectral response, transmittance, and polarization sensitivity. Existing methods lack tandem multicolor detection and exhibit high spectral cross talk. We exploit the polarization sensitivity of organic photodetectors, together with birefringent optical filters to design single-pixel multispectral detectors that achieve high spectral selectivity and good radiometric performance. Two different architectures are explored and optimized, including the Solc-based and multitwist-retarder-based organic photodetectors. Although the former demonstrated a higher spectral resolution, the latter enables a more compact sensor as well as greater flexibility in device fabrication.

Deep Cross-Modal Representation Learning and Distillation for Illumination-Invariant Pedestrian Detection

Integrating multispectral data has been demonstrated to be an effective solution for illumination-invariant pedestrian detection, in particular, RGB and thermal images can provide complementary information to handle light variations. However, most of the current multispectral detectors fuse the multimodal features by simple concatenation, without discovering their latent relationships. In this paper, we propose a cross-modal feature learning (CFL) module, based on a split-and-aggregation strategy, to explicitly explore both the shared and modality-specific representations between paired RGB and thermal images. We insert the proposed CFL module into multiple layers of a two-branch-based pedestrian detection network, to learn the cross-modal representations in diverse semantic levels. By introducing a segmentation-based auxiliary task, the multimodal network is trained end-to-end by jointly optimizing a multi-task loss. On the other hand, to alleviate the reliance of existing multispectral pedestrian detectors on thermal images, we propose a knowledge distillation framework to train a student detector, which only receives RGB images as input and distills the cross-modal representations guided by a well-trained multimodal teacher detector. In order to facilitate the cross-modal knowledge distillation, we design different distillation loss functions for the feature, detection and segmentation levels. Experimental results on the public KAIST multispectral pedestrian benchmark validate that the proposed cross-modal representation learning and distillation method achieves robust performance.

Ferroelectric Superdomain Controlled Graphene Plasmon for Tunable Mid-Infrared Photodetector with Dual-Band Spectral Selectivity

Dual-band infrared photodetectors (DBIPs) can discriminate desired signals from complex scenes and thus are highly expected for threat-warning, remote sensing, and astronomy applications. Conventional DBIPs with high-performances are, however, typically based on semiconductor thin films, but remain the challenges of complex spatial align, expensive growth and cooling requirement. Here, we report a tunable graphene plasmonic photodetector with dual-band infrared spectral selectivity driven by ferroelectric superdomain. The periodic ferroelectric polarization array with nanoscale ring shapes provides ultrahigh electrostatic field for spatially doping of monolayer graphene to desired patterns, and is further used to excite and confine intrinsic graphene plasmons. Our devices exhibit tunable resonance photoresponse in both two bands of 3.7-16.3 um and 15.1-52.1 um. The numerical calculations show that our devices own ultrahigh responsivities of 667-1080 A W-1 at room temperature in range of 5-50 um. Our devices make possible the applications of infrared imaging system and both stationary and motion state of objects detection. These investigations provide a novel approach for advanced infrared system construction by employing simple, low-cost, uncooling multispectral detectors array.

Spectral dependence of subwavelength slit geometry

For two decades, extraordinary optical transmission (EOT) has amplified exploration into subwavelength systems. Researchers have previously suggested exploiting the spectrally selective electromagnetic field confinement of subwavelength slits for multispectral detectors. Utilizing the finite-difference frequency domain (FDFD) method, we examine electromagnetic field confinement in both 2-dimensional and 3-dimensional scenarios from 2.5 to 6 microns, i.e. midwave infrared (MWIR). We explore the trade space of deep subwavelength slits and its impact on resonant enhancement of the electromagnetic field. This builds fundamental understanding of the coupling mechanisms allowing for prediction of resonant spectral behavior based on slit geometry and material properties.

Ultra-Low-Cost Self-Referencing Multispectral Detector for Non-Destructive Measurement of Fruit Quality

A very low-cost sensor is developed to non-destructively test fruits by sequentially turning on light-emitting diodes at 12 different wavelengths and measuring the reflectance in the interactance mode. The detector is tested on kiwifruit to measure soluble solids content (SSC) and dry matter (DM) non-destructively, while the performance is compared with a benchtop spectrometer. For SSC and DM measurements, a total of 378 and 200 samples of kiwifruits were measured respectively. Non-parametric regression was used for the multi-spectral detector, while a partial least squares regression model was used for the benchtop spectrometer. Different regression techniques were used as they provided the best prediction for the two different measurements. For SSC measurements, coefficient of determination (R2) of 0.83, root mean square error for prediction (RMSEP) of 0.85%, bias of −0.004%, and SDR of 2.45 were observed using the multispectral detector. The corresponding values achieved with the benchtop spectrometer were 0.98, 0.37%, 0.01%, and 5.60, respectively. For dry matter measurements with 200 kiwifruits, R2, RMSEP, bias, and SDR of 0.83, 0.61%, −0.02, and 2.44 were achieved with the prototype multispectral detector compared with the values of 0.96, 0.31%, −0.11, and 4.80, respectively, achieved with the benchtop spectrometer. The efficacy of the multispectral detector was also tested by measuring 30 navel oranges, wherein an R2 and root mean square error for calibration (RMSEC) of 0.79 and 0.47% were achieved for SSC measurements. While the performance of the multispectral detection is lower than a benchtop spectrometer, its performance is still better than low-cost spectrometers and can be used to inexpensively measure the quality of fruits in a non-destructive manner.

A fast RetinaNet fusion framework for multi-spectral pedestrian detection

At present, the mainstream visible pedestrian detector is easily affected by the ambient lighting, the complex background, and the pedestrians distance. While the infrared images (IR) can compensate for the defects of visible images because of its insensitivity to illumination conditions. Based on the Deep Convolutional Neural Network (DCNN), we proposed a multispectral pedestrian detector that combines visual-optical (VIS) image and infrared (IR) image. We carefully designed three DCNN fusion architectures to study the better fusion stages of the two-branch DCNN. In addition, we compared the three fusion strategies and found that the sum fusion strategy showed better performance to our multispectral detector. Our multispectral pedestrian detectors are more adaptable to the around-the-clock applications such as autonomous driving and unattended monitoring, by testing on the public multispectral benchmark dataset KAIST, our best fusion architectures achieved a log-average miss rate of 27.60% comparable to the state-of-the-art detector, but with half the runtime.

Electrostatically Doped Silicon Nanowire Arrays for Multispectral Photodetectors.

Nanowires have promising applications as photodetectors with superior ability to tune absorption with morphology. Despite their high optical absorption, the quantum efficiencies of these nanowire photodetectors remain low due to difficulties in fabricating a shallow junction using traditional doping methods. As an alternative, we report nonconventional radial heterojunction photodiodes obtained by conformal coating of an indium oxide layer on silicon nanowire arrays. The indium oxide layer has a high work function which induces a strong inversion in the silicon nanowire and creates a virtual p-n junction. The resulting nanowire photodetectors show efficient carrier separation and collection, leading to an improvement of quantum efficiency up to 0.2. In addition, by controlling the nanowire radii, the spectral responses of the In2O3/Si nanowire photodetectors are tuned over several visible light wavelengths, creating a multispectral detector. Our approach is promising for the development of highly efficient wavelength-selective photodetectors.

Multispectral superconducting nanowire single photon detector.

In this work, we report multispectral superconducting nanowire single photon detectors (SNSPDs) that can simultaneously detect single photons at multiple wavelengths with high efficiency. The superconducting nanowires are fabricated on an all-dielectric mirror consisting of two quarter-wave stack reflectors with separated central wavelengths. The unique optical structure results in serially coupled optical cavities, leading to multiple resonant absorption bands that are utilized for high-efficiency single photon detection. The fabricated detector shows system detection efficiencies of >80% at the three target wavelengths of 1550 nm, 1310 nm, and 1064 nm. The multispectral detector may eliminate the need for multiple SNSPDs for different wavelengths in a system, potentially resulting in a reduction in size, weight, and power, as well as in the cost of the overall detection system. The detector may also find interesting use for applications such as multispectral ranging or imaging.

A USB high resolution lock-in photometer

A design is presented, in which the DDC112 current-input analogue-to-digital converter is combined with a PIC microcontroller and associated circuitry to give a simple and economical dual-beam photometer / electrometer. The PIC supervises the operation of the analogue-digital converter and performs a lock-in function using a rolling average filter, which enables intensity measurement to parts per million. It also synchronously controls a regulated current source to drive, typically, one or more power LEDs as light sources. It has been applied in various fluorescence and absorbance measurements and can be used with Cavity Enhanced Absorption Spectrometry to determine ultra-low absorbance. An expanded version has been created with a PIC32 processor handling eight channels for a PixelSensor multispectral detector. All circuit details and source code are made available.

The use of optical microscope equipped with multispectral detector to distinguish different types of acute lymphoblastic leukemia

The article describes the use of a computer optical microscopy with multispectral camera to characterize the texture of blasts bone marrow of patients with different variants of acute lymphoblastic leukemia: B- and T- types. Specific characteristics of the chromatin of the nuclei of blasts for different types of acute lymphoblastic leukemia were obtained.

Scalable Fabrication of Infrared Detectors with Multispectral Photoresponse Based on Patterned Colloidal Quantum Dot Films

Colloidal quantum dots (CQDs) are promising materials for developing infrared (IR) detectors. Absorption spectra and spectral photoresponse can be continuously tuned by controlling the size, shape, and composition of CQDs. However, the incapability to achieve site-selective patterning of CQDs by conventional methods (i.e., drop casting, spin coating, and spray coating) greatly hinders the realization of CQD-based multipixel or multispectral detectors. In this paper, we demonstrate a simple and highly efficient poly(methyl methacrylate)-assisted transfer technique for the scalable fabrication of CQD-based photodetectors with multiple pixels, which respond to different spectral ranges of IR, by using patterned HgTe CQD films. Large arrays of three-pixel photodetectors were produced on both flat and curved substrates with a high fabrication success rate of over 95%. The maximum room-temperature responsivity of up to 0.1 A/W under low operation voltage (<10 V) was achieved. Furthermore, a spectral photodetect...

High-quality infrared imaging with graphene photodetectors at room temperature.

Graphene, a two-dimensional material, is expected to enable broad-spectrum and high-speed photodetection because of its gapless band structure, ultrafast carrier dynamics and high mobility. We demonstrate a multispectral active infrared imaging by using a graphene photodetector based on hybrid response mechanisms at room temperature. The high-quality images with optical resolutions of 418 nm, 657 nm and 877 nm and close-to-theoretical-limit Michelson contrasts of 0.997, 0.994, and 0.996 have been acquired for 565 nm, 1550 nm, and 1815 nm light imaging measurements by using an unbiased graphene photodetector, respectively. Importantly, by carefully analyzing the results of Raman mapping and numerical simulations for the response process, the formation of hybrid photocurrents in graphene detectors is attributed to the synergistic action of photovoltaic and photo-thermoelectric effects. The initial application to infrared imaging will help promote the development of high performance graphene-based infrared multispectral detectors.

Generalized unmixing model for multispectral flow cytometry utilizing nonsquare compensation matrices

Multispectral and hyperspectral flow cytometry (FC) instruments allow measurement of fluorescence or Raman spectra from single cells in flow. As with conventional FC, spectral overlap results in the measured signal in any given detector being a mixture of signals from multiple labels present in the analyzed cells. In contrast to traditional polychromatic FC, these devices utilize a number of detectors (or channels in multispectral detector arrays) that is larger than the number of labels, and no particular detector is a priori dedicated to the measurement of any particular label. This data-acquisition modality requires a rigorous study and understanding of signal formation as well as unmixing procedures that are employed to estimate labels abundance. The simplest extension of the traditional compensation procedure to multispectral data sets is equivalent to an ordinary least-square (LS) solution for estimating abundance of labels in individual cells. This process is identical to the technique employed for unmixing spectral data in various imaging fields. The present study shows that multispectral FC data violate key assumptions of the LS process, and use of the LS method may lead to unmixing artifacts, such as population distortion (spreading) and the presence of negative values in biomarker abundances. Various alternative unmixing techniques were investigated, including relative-error minimization and variance-stabilization transformations. The most promising results were obtained by performing unmixing using Poisson regression with an identity-link function within a generalized linear model framework. This formulation accounts for the presence of Poisson noise in the model of signal formation and subsequently leads to superior unmixing results, particularly for dim fluorescent populations. The proposed Poisson unmixing technique is demonstrated using simulated 8-channel, 2-fluorochrome data and real 32-channel, 6-fluorochrome data. The quality of unmixing is assessed by computing absolute and relative errors, as well as by calculating the symmetrized Kullback-Leibler divergence between known and approximated populations. These results are applicable to any flow-based system with more detectors than labels where Poisson noise is the dominant contributor to the overall system noise and highlight the fact that explicit incorporation of appropriate noise models is the key to accurately estimating the true label abundance on the cells. © 2013 International Society for Advancement of Cytometry.

Optical design of common aperture, common focal plane, multispectral optics for military applications

With recent developments in multispectral detector technology, the interest in common aperture, common focal plane multispectral imaging systems is increasing. Such systems are particularly desirable for military applications, where increased levels of target discrimination and identification are required in cost-effective, rugged, lightweight systems. During the optical design of dual waveband or multispectral systems, the options for material selection are limited. This selection becomes even more restrictive for military applications, where material resilience, thermal properties, and color correction must be considered. We discuss the design challenges that lightweight multispectral common aperture systems present, along with some potential design solutions. Consideration is given to material selection for optimum color correction, as well as material resilience and thermal correction. This discussion is supported using design examples currently in development at Qioptiq.

Modeling a tunable multispectral X-ray SR detector with time-division bands

Several configurations of a tunable multispectral X-ray detector of synchrotron radiation are modeled. The detector can record the signals of two spectral bands due to differences in the delays of the drift and diffusion current components appearing in the output signal.

Medipix3 CT for material sciences

Innovative detector systems for non-destructive material analysis and for medical diagnosis are an important development to improve the performance and the quality of examination methods. For a number of years now photon-counting X-ray detectors are being developed to process incoming X-ray photons as single events. These detectors facilitate a higher signal-to-noise ratio (SNR) than conventional, non-photon-counting, scintillator based detector systems, which detect X-ray photons indirectly through conversion into visible light. The Medipix is a pixelated photon counting semiconductor detector which features adjustable energy thresholds allowing energy selective, multispectral X-ray imaging. The Medipix chip is under continued development by the ``Medipix2 Collaboration'' and ``Medipix3 Collaboration'' at CERN [1]. The Medipix electronic offers 256 × 256 pixels with a pixel pitch of 55 × 55 μm2 and can be hybridized with different sensor materials like Si, CdTe or GaAs. The newest member of the Medipix family is the Medipix3 (ASIC in 0.13 μm CMOS technology) providing up to eight separate 12-bit counters per pixel. It offers a couple of different working modes [2], which are useful for X-ray imaging applications. A Medipix3 CT X-ray measuring station was built up for small animal X-ray imaging and non-destructive material analysis [3]. The combination of the low energy threshold ( ∼ 4 keV) of the Medipix3 with its multispectral capability enables tomographic investigations on objects with low absorption contrast. The advantage of photon counting, multispectral detectors like Medipix3 for material sciences will be presented here as well as a comparison with a scintillator based CT.

Spatial Composition Grading of Quaternary ZnCdSSe Alloy Nanowires with Tunable Light Emission between 350 and 710 nm on a Single Substrate

We demonstrated a general methodology of growing spatially composition-controlled alloys by combining spatial source reagent gradient with a temperature gradient. Using this dual gradient method, we achieved for the first time a continuous spatial composition grading of single-crystal quaternary Zn(x)Cd(1-x)S(y)Se(1-y) alloy nanowires over the complete band gap range along the length of a substrate. The band gap grading spans between 3.55 eV (ZnS) and 1.75 eV (CdSe) on a single substrate, with the corresponding light emission over the entire visible spectrum. We also showed that the dual gradient method can be extended to achieve alloy composition control in two spatial dimensions. The unique material platform achieved will open a wide range of applications from color engineered display and lighting, full spectrum solar cells, multispectral detectors, or spectrometer on-a-chip to superbroadly tunable nanolasers. The growth methodology can be extended more generally to other alloy systems.