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Lead-based organic–inorganic hybrid perovskite single crystals (OIHP SCs) offer promising opportunity for X-ray detection and imaging owing to their high X-ray attenuation coefficient, excellent optoelectronic properties, and simple fabrication processes. Nevertheless, it remains a key challenge to reduce its dark current and meanwhile maintain a high sensitivity. Herein, we developed an on-substrate method for growing methylamine lead bromide (MAPbBr3) SCs on aluminum oxide (Al2O3) layer coated indium tin oxide (ITO) glass. The photodiode based on this approach exhibits an ultralow-dark-current density of 1 nA cm−2 at an operative voltage of −5 V, a signal-to-noise ratio (SNR) more than 80 dB, and meanwhile retaining a high X-ray sensitivity of 2.02 $\times 10^{{3}}\,\, \mu \text{C}\cdot $ ${\mathrm {Gy}}_{\text {air}}^{-1} \cdot $ cm−2. Our further investigation reveals that the dark current was reduced due to two beneficial effects of the Al2O3 layer in tandem, including the interfacial defect passivation and blocking of hole injection by increased interfacial energy barrier. Our approach sheds light on advancing the fabrication of high-performance OIHP SCs-based X-ray sensors that can be potentially integrated with large-area readout panel at low temperature. [ABSTRACT FROM AUTHOR]

Transition-edge sensors (TES) are outstanding calorimeters based on the steep superconductive transition of a metallic film. Among other photon detectors, they are renowned for the fine energy resolution, the photon-number resolving (PNR) capability and an extremely low dark count rate. Due to the broad detection spectrum, from gamma-ray to visible and submillimetre wavelengths, TESs are highly sought-after in a great variety of fields, such as X-ray detection and quantum technologies. Each of these fields demands a step forward in TESs performance with regards to the recovery time and energy resolution. Here we present a program, primarily capable of predicting the performance of TESs. Using established theoretical and empirical methods we developed a software that allows the users to choose active area, thickness, and material composition of a TES and to calculate its performance. Furthermore, the software can simulate TES properties at different working points. The aim of the software is to minimize the production cost and speed up the overall process for the creation of new devices with improved performance. [ABSTRACT FROM AUTHOR]

Medical expert support systems using medical data significantly contribute to the field of medicine by utilizing intelligent image analysis technology. Such medical systems must be validated and must have a transparent internal structure. Therefore, the technique of analyzing the results of the medical system is an important factor. This study proposes a diagnosis support model of cardiomegaly based on CNN using ResNet and explainable feature map. To configure the model, initially, a cardiomegaly diagnosis model is configured using ResNet, and a chest X-ray data set is used and learned. As the result changes resulting from the input changes of the model configured for model diagnosis support are detected, an explainable feature map for analysis is implemented. The input changes of the model are made as each pixel of the required image is reversed in sequence and the changes of the neural network output layer are saved on the feature map. As a result, the configured analysis method provides information inside the neural network through an accuracy result close to 80% and a visually expressed feature map. In particular, this interpretation method can be extended to a more general form in a medical support system that analyzes patterns.

Given its low dose and compactness, chest radiography has been widely used as the first-line test to determine the presence of lung anomalies. Nevertheless, a high-performance diagnosis for initial screening to detect shadows in lungs due to general lung diseases is not available. During initial screening, chest radiography can be used to distinguish any diseased lung shadowing caused by lung diseases. Thus, chest radiography can contribute to the early diagnosis and prevention of novel lung infectious diseases if training for a specific disease is not required. Accordingly, we propose a deep-learning-based diagnostic system called contrast-shifted instances via patch-based percentile (CSIP) to automatically detect diseased lung shadowing via training only on chest X-ray data from healthy subjects. CSIP is the first application of a patch-based percentile approach to state-of-the-art one-class classifiers (OCCs). This application improves the sensitivity of the network to recognize shadowing density differences in each local area of the lung, thereby considerably improving the diagnostic performance of average area under the curve (AUC) by more than 20% and achieving a sufficiently high diagnostic performance (average AUC of 0.96 for various lung diseases), compared to the existing OCC case without applying our patch-based approach (average AUC of 0.74). Therefore, CSIP may contribute to the early detection of anomalies caused by novel infectious diseases such as variants of the coronavirus disease, for whom training data are scarce. The code is available at https://github.com/kskim-phd/CSIP.

For the purpose of ensuring public security, automatic inspection of X-ray scanners has been deployed at the entry points of many public places to detect dangerous objects. However, current surveillance systems cannot function without human supervision and intervention. In this article, we propose an effective method using deep convolutional neural networks to detect objects during X-ray baggage inspection. As a first step, a large amount of training data is generated by a specific data augmentation technique. Second, a feature enhancement module is used to improve feature extraction capabilities. Then, in order to address the foreground–background imbalance in the region proposal network, focal loss is adopted. Third, the multiscale fused region of interest is utilized to obtain more robust proposals. Finally, soft nonmaximum suppression is adopted to alleviate overlaps in baggage detection. As compared with existing algorithms, the proposed method proves that it is more accurate and robust when dealing with densely cluttered backgrounds during X-ray baggage inspection. [ABSTRACT FROM AUTHOR]

Aviation security X-ray equipment currently searches objects through primary screening, in which the screener has to re-search a baggage/person to detect the target object from overlapping objects. The advancements of computer vision and deep learning technology can be applied to improve the accuracy of identifying the most dangerous goods, guns and knives, from X-ray images of baggage. Artificial intelligence-based aviation security X-rays can facilitate the high-speed detection of target objects while reducing the overall security search duration and load on the screener. Moreover, the overlapping phenomenon was improved by using raw RGB images from X-rays and simultaneously converting the images into grayscale for input. An O-Net structure was designed through various learning rates and dense/depth-wise experiments as an improvement based on U-Net. Two encoders and two decoders were used to incorporate various types of images in processing and maximize the output performance of the neural network, respectively. In addition, we proposed U-Net segmentation to detect target objects more clearly than the You Only Look Once (YOLO) of Bounding-box (Bbox) type through the concept of a “confidence score”. Consequently, the comparative analysis of basic segmentation models such as Fully Convolutional Networks (FCN), U-Net, and Segmentation-networks (SegNet) based on the major performance indicators of segmentation-pixel accuracy and mean-intersection over union (m-IoU)-revealed that O-Net improved the average pixel accuracy by 5.8%, 2.26%, and 5.01% and the m-IoU was improved by 43.1%, 9.84%, and 23.31%, respectively. Moreover, the accuracy of O-Net was 6.56% higher than that of U-Net, indicating the superiority of the O-Net architecture.

Immediate and accurate detection of foreign metal objects (FMOs) in clothing products is important for guaranteeing human safety. This article proposes an online detection approach based on deep learning, which is suitable for detecting small FMOs from X-ray images of clothing packages. A conveyor belt X-ray scanning system is developed for image collection. The X-ray images are preprocessed by using the morphological erosion operation to improve the accuracy of FMOs detection. These images are then down-sampled to reduce the computation cost. Feature pyramid network (FPN) is adopted for aggregating feature maps with different resolutions, which proved to be effective for small FMOs detection. The stochastic gradient descent (SGD) is used to optimize a multitask loss. The trained model was tested offline on 200 X-ray images, which achieved precision = 0.999, recall = 0.988, F1-score = 0.993, and AP = 0.946. Compared to original Faster region-based convolutional neural networks (R-CNN), the proposed method significantly improved the performance for small FMOs detection in terms of precision and recall rate. [ABSTRACT FROM AUTHOR]

We describe a novel coupled microwave dielectric resonator system (an unusual form of parametric amplifier), which is under development, aimed at realizing a high-resolution single X-ray photon energy detector. Unlike other high-resolution detectors, it operates at a relatively high cryogenic temperature in the range of 7–30 K. Construction of the cooler system and thermal characterization system is completed. All aspects of the novel calorimeter performance have been evaluated, including demonstration of single-particle detection, the required rapid thermal time constant of a coupled resonator, a high $df/dT$ response, and promising development of a low-noise microwave detection system. [ABSTRACT FROM AUTHOR]

Direct X-ray detection plays an indispensable role in medical and industrial development. However, developing a stable, low-cost, and sensitive direct X-ray detector is highly desired for future commercial application. In this work, a direct X-ray detector using a straightforward digital printing fabrication process based on nontoxic micropyramid triclinic bismuth oxide (ω-Bi2O3) ink is reported. The printed device exhibits a low detection limit of 56.95 μ Gyair s−1 with a sensitivity of 3.077 μC Gyair−1 cm−2 at 20 V bias voltage, which is better than most of the metal oxide-based direct X-ray detectors reported so far. Furthermore, the ω-Bi2O3 based X-ray detector shows excellent stability without packaging for eight months and exposure to a dose of 5120 mGyair equivalent to 25 000 chest X-ray scans. The applicability of our array device printed in a direct patterning method as an X-ray imaging detector is shown. Our findings inform a qualified competitor in the medical and industrial fields in the future. [ABSTRACT FROM AUTHOR]

We characterized the performance of abiased superconducting nanowire to detect X-ray photons. The device, made of a 10 nm thin NbTiN film and fabricated on a dielectric substrate (SiO2, Nb3O5) detected 1000 times larger signal than anticipated from direct X-ray absorption. We attributed this effect to X-ray induced generation of secondary particles in the substrate. The enhancement corresponds to an increase in the flux by the factor of 3.6, relative to a state-of-the-art commercial X-ray silicon drift detector. The detector exhibited 8.25 ns temporal recovery time and 82 ps timing resolution, measured using optical photons. Our results emphasize the importance of the substrate in superconducting X-ray single photon detectors. [ABSTRACT FROM AUTHOR]

X-ray fluorescence computed tomography (XFCT) with nanoparticles (NPs) as contrast agents shows potential for molecular biomedical imaging with higher spatial resolution than present methods. To date the technique has been demonstrated on phantoms and mice, however, parameters such as radiation dose, exposure times and sensitivity have not yet allowed for high-spatial-resolution in vivo longitudinal imaging, i.e., imaging of the same animal at different time points. Here we show in vivo XFCT with spatial resolution in the 200- $400~\boldsymbol {\mu }\text{m}$ range in a proof-of-principle longitudinal study where mice are imaged five times each during an eight-week period following tail-vein injection of NPs. We rely on a 24 keV x-ray pencil-beam-based excitation of in-house-synthesized molybdenum oxide NPs (MoO2) to provide the high signal-to-background x-ray fluorescence detection necessary for XFCT imaging with low radiation dose and short exposure times. We quantify the uptake and clearance of NPs in vivo through imaging, and monitor animal well-being over the course of the study with support from histology and DNA stability analysis to assess the impact of x-ray exposure and NPs on animal welfare. We conclude that the presented imaging arrangement has potential for in vivo longitudinal studies, putting emphasis on designing biocompatible NPs as the future focus for active-targeting preclinical XFCT. [ABSTRACT FROM AUTHOR]

The sensitive detection of low-dose X-ray radiation is essential to many X-ray applications. In this article, the ultrasensitive X-ray detector based on pure Cs2AgBiBr6 all-inorganic lead-free perovskite film is successfully demonstrated and encapsulated using a metal casing with a Be window. The high-quality Cs2AgBiBr6 films are obtained through the low-cost solution process with long electron–hole diffusion length (~700 nm) and long carrier lifetime (~750 ns). Benefiting from the excellent properties of the Cs2AgBiBr6 film and the stable ambient provided by the packaging module, the resulting device exhibits attractive X-ray detection capabilities with a minimum detectable dose rate of 145.2 nGyairs−1 and a detection sensitivity up to 1.8 × 104μ nGyair−1 cm−2, which is about a thousand times higher than the sensitivity achieved with commercial a-Se X-ray detectors. Besides, the encapsulated device maintains superior detection performance after 2 months of storage, indicating the favorable reliability of the encapsulated device. This article demonstrates a possibility to use Cs2AgBiBr6 perovskite film and Be window for the sensitive X-ray detection, which will inspire further development of radiation electronics by utilizing all-inorganic lead-free perovskite. [ABSTRACT FROM AUTHOR]

An intelligent and rapid detection approach based on an X-ray orientation instrument is proposed to identify the single-crystal defects through online single and offline batch defection. This method can effectively solve the problems of current detection equipment, such as longer detection time, higher cost, and human involvement. A total of eight factors in two pattern vectors that can express the rocking curve characteristics of the crystal structure are selected as the feature factors for defect detection. An improved algorithm of the fuzzy transitive closure clustering (FTCC) is presented to identify the defect type of one single-crystal online based on the real-time data, satisfying the real-time requirement of online defect detection. An improved algorithm of the fuzzy c-means that can effectively solve the problems of the bad initial clustering centers and abnormal data, combined with the improved algorithm of the FTCC, is employed to identify the defect types of batch single-crystals offline based on many measured data and to meet the rapid requirement of batch single-crystal defect identification. The sapphire is selected as an example of the single crystal to identify the defects both online and offline, and the experiment results indicate that the proposed method is a rapid and effective means of the defect detection that meets industrial manufacturing requirements. [ABSTRACT FROM AUTHOR]

The small molecule 6,13-bis (triisopropylsilylethynyl) (TIPS) pentacene has been used as an interlayer for the reduction of dark currents in organic photodetectors (OPDs) based on a bulk heterojunction of poly-3-hexyl-thiophene(P3HT) and [6, 6]-phenyl C61 butyric acid methyl ester. We report OPDs with dark currents of ~0.9 nA/cm² at -5 V and external quantum efficiencies close to 80% at 530 nm. Compared to the reference, P3HT interlayer, TIPS pentacene shows a significant increase of the OPD's detectivity from 3.29 x 1012 to 1.63 x 1013 Jones. Also, the OPD's dynamic range is improved reducing the limit of signal detection from 132 to 6.3 nW/cm² under green light irradiation. Singular hysteresis in the I-V characteristic curve has been observed and impedance spectroscopy measurements were carried out to analyze its origin and generate a replacement electrical model for the device at reverse bias. Finally, OPDs with TIPS pentacene interlayer have been integrated on top of amorphous silicon thin-film transistor backplanes to obtain the first OPD-based image sensor using this interlayer. [ABSTRACT FROM AUTHOR]

The proposed spectral CT method solves the constrained one-step spectral CT reconstruction (cOSSCIR) optimization problem to estimate basis material maps while modeling the nonlinear X-ray detection process and enforcing convex constraints on the basis map images. In order to apply the optimization-based reconstruction approach to experimental data, the presented method empirically estimates the effective energy-window spectra using a calibration procedure. The amplitudes of the estimated spectra were further optimized as part of the reconstruction process to reduce ring artifacts. A validation approach was developed to select constraint parameters. The proposed spectral CT method was evaluated through simulations and experiments with a photon-counting detector. Basis material map images were successfully reconstructed using the presented empirical spectral modeling and cOSSCIR optimization approach. In simulations, the cOSSCIR approach accurately reconstructed the basis map images (<1% error). In experiments, the proposed method estimated the low-density polyethylene region of the basis maps with 0.5% error in the PMMA image and 4% error in the aluminum image. For the Teflon region, the experimental results demonstrated 8% and 31% error in the PMMA and aluminum basis material maps, respectively, compared with −24% and 126% error without estimation of the effective energy window spectra, with residual errors likely due to insufficient modeling of detector effects. The cOSSCIR algorithm estimated the material decomposition angle to within 1.3 degree error, where, for reference, the difference in angle between PMMA and muscle tissue is 2.1 degrees. The joint estimation of spectral-response scaling coefficients and basis material maps was found to reduce ring artifacts in both a phantom and tissue specimen. The presented validation procedure demonstrated feasibility for the automated determination of algorithm constraint parameters. [ABSTRACT FROM AUTHOR]

We report on the development of Mo/Au based transition edge sensors (TESs) aimed at soft X-ray detection. TESs of different sizes with Tc ∼ 100 mK and very narrow transitions have been fabricated. Dark characterization based on I–V, complex impedance, and noise measurements has allowed us to obtain their basic functional parameters at different bath temperatures and operating points. Electrodeposited Bi films, to be used as X-ray absorbers, have been developed and characterized. [ABSTRACT FROM PUBLISHER]

Direct conversion crystalline silicon X-ray imagers are used for low-energy X-ray photon (4–20 keV) detection in scientific research applications such as protein crystallography. In this paper, we demonstrate a novel pixel architecture that integrates a crystalline silicon X-ray detector with a thin-film transistor amorphous silicon pixel readout circuit. We describe a simplified two-mask process to fabricate a complete imaging array and present preliminary results that show the fabricated pixel to be sensitive to 5.89-keV photons from a low activity Fe-55 gamma source. This paper presented can expedite the development of high spatial resolution, low cost, direct conversion imagers for X-ray diffraction and crystallography applications. [ABSTRACT FROM PUBLISHER]

X-ray detectors in clinical computed tomography (CT) usually operate in current-integrating mode. Their complicated signal statistics often lead to intractable likelihood functions for practical use in model-based image reconstruction (MBIR). It is therefore desirable to design simplified statistical models without losing the essential factors. Depending on whether the CT transmission data are logarithmically transformed, pre-log and post-log models are two major categories of choices in CT MBIR. Both being approximations, it remains an open question whether one model can notably improve image quality over the other on real scanners. In this study, we develop and compare several pre-log and post-log MBIR algorithms under a unified framework. Their reconstruction accuracy based on simulation and clinical datasets are evaluated. The results show that pre-log MBIR can achieve notably better quantitative accuracy than post-log MBIR in ultra-low-dose CT, although in less extreme cases, post-log MBIR with handcrafted pre-processing remains a competitive alternative. Pre-log MBIR could play a growing role in emerging ultra-low-dose CT applications. [ABSTRACT FROM AUTHOR]

This paper presents a stacked microfabricated power generator that vertically integrates multiple magnets on silicon wafers in a batch process to enhance electromagnetic induction multiple times. The power output is increased by increasing the magnetic flux change for each power-generator unit in the stack, in addition to the increase due to increased number of units. A stack consisting of two arrays of four power-generator units is fabricated and characterized. Wax-bonded Nd–Fe–B powders are embedded in the silicon wafer and magnetized as an integrated micromagnet, which serves as a proof mass suspended by a parylene diaphragm. Dual-layer coils are isolated by a parylene layer, connected via a hole and fabricated with electroplating copper on the same wafer. Experimental results show an improvement by about a factor of four on the power output from the same coils when two power-generator arrays are stacked vertically. In particular, an array of four microfabricated power generators occupying a volume of 51 \times 11 \times 0.4 mm ^{\mathrm {3}} in the stack produces an induced electromotive force of 1.02 mV with 0.55 nW power output when it is vibrated at 400 Hz with vibration amplitude of 10~\mu $ m. [2014-0029] [ABSTRACT FROM AUTHOR]

This paper presents a high-speed wafer-scale CMOS X-ray detector with an active area of 12~cm \times 12 cm, which features $100~\mu $ m-sized pixels. A horizontal row driver is adopted for implementing a three-side buttable detector with the tiling technique and thereby enabling the extension of the active area. The proposed detector employs 14-b column-parallel extended-counting analog-to-digital converters (EC ADCs) using digital correlated double sampling for high-speed operation and high-gray-scale resolution. The oversampling binning method using a $\Delta \Sigma $ modulator in EC ADCs is proposed for high sensitivity and the pipelined timing method is adopted for a high frame rate, which results in reduction of the X-ray dose. An offset cancellation method for the input buffer is used to improve the uniformity between column ADCs. The proposed CMOS X-ray detector is fabricated using a 0.35- $\mu $ m CMOS process with the stitching technique. The measured differential column fixed pattern noise and random noise without X-ray exposure are 3.01 and 3.06 least significant bits, respectively, at a resolution of 14 b. In the full-resolution mode, the proposed detector operates up to a frame frequency of 108 frames/s with the pipelined timing and 60 frames/s without the pipelined timing. [ABSTRACT FROM AUTHOR]

The energy information acquired using spectral X-ray detectors allows noninvasive identification and characterization of chemical components of a material. To achieve this, it is important that the energy response of the detector is calibrated. The established techniques for energy calibration are not practical for routine use in pre-clinical or clinical research environment. This is due to the requirements of using monochromatic radiation sources such as synchrotron, radio-isotopes, and prohibitively long time needed to set up the equipment and make measurements. To address these limitations, we have developed an automated technique for calibrating the energy response of the pixels in a spectral X-ray detector that runs with minimal user intervention. This technique uses the X-ray tube voltage (kVp) as a reference energy, which is stepped through an energy range of interest. This technique locates the energy threshold where a pixel transitions from not-counting (off) to counting (on). Similarly, we have developed a technique for calibrating the energy response of individual pixels using X-ray fluorescence generated by metallic targets directly irradiated with polychromatic X-rays, and additionally \gamma-rays from ^241Am. This technique was used to measure the energy response of individual pixels in CdTe-Medipix3RX by characterizing noise performance, threshold dispersion, gain variation and spectral resolution. The comparison of these two techniques shows the energy difference of 1 keV at 59.5 keV which is less than the spectral resolution of the detector (full-width at half-maximum of 8 keV at 59.5 keV). Both techniques can be used as quality control tools in a pre-clinical multi-energy CT scanner using spectral X-ray detectors. [ABSTRACT FROM PUBLISHER]

The absorbed energy distribution (AED) in X-ray imaging detectors is an important factor that affects both energy resolution and image quality through the Swank factor and detective quantum efficiency. In the diagnostic energy range (20–140 keV), escape of characteristic photons following photoelectric absorption and Compton scatter photons are primary sources of absorbed-energy dispersion in X-ray detectors. In this paper, we describe the development of an analytic model of the AED in compound X-ray detector materials, based on the cascaded-systems approach, that includes the effects of escape and reabsorption of characteristic and Compton-scatter photons. We derive analytic expressions for both semi-infinite slab and pixel geometries and validate our approach by Monte Carlo simulations. The analytic model provides the energy-dependent X-ray response function of arbitrary compound materials without time-consuming Monte Carlo simulations. We believe this model will be useful for correcting spectral distortion artifacts commonly observed in photon-counting applications and optimal design and development of novel X-ray detectors. [ABSTRACT FROM AUTHOR]

We have demonstrated a new type of phonon sensor for cryogenic particle detectors with high-bandwidth SQUID readout. Our Quasiparticle-trap assisted Electrothermal feedback Transition edge sensor (QET) utilizes aluminum quasiparticle traps attached to a tungsten superconducting transition edge sensor patterned on a silicon substrate. The tungsten lines are voltage biased and self-regulate in the transition region. Phonons from particle interactions in the silicon deposit energy into the creating quasiparticles. The quasiparticles are trapped into the tungsten and cause its electrical resistance to increase. The resulting decrease in current through the sensor is measured with a DC SQUID array. We have been able to demonstrate xy-position resolution of /spl sim/0.3 mm for 6 keV X-rays from an /sup 55/Fe source in a 2 cm/spl times/2 cm/spl times/4 mm (4 g) detector. We describe our optimizations of the sensor design for improved energy and position. By simultaneously measuring the ionization yield we have demonstrated discrimination between electron and nuclear recoil events in a 100 g Si detector for the CDMS (Cryogenic Dark Matter Search) experiment. [ABSTRACT FROM PUBLISHER]

Superconducting tunnel junctions coupled to superconducting absorbers may be used as high-resolution, high-efficiency X-ray spectrometers. We have tested devices with niobium X-ray absorbing layers coupled to aluminum layers that serve as quasiparticle traps. In this work we measure the current pulses from a large-area tunnel junction using an amplifier based on an array of 100 SQUIDs. Using this amplifier and a 282 /spl mu/m/spl times/282 /spl mu/m junction, we have measured an energy resolution of 19 eV FWHM for 1.5 keV X-rays and 21 eV for 2.6 keV X-rays. The area of this junction is eight times the area of any junction previously measured to have such high energy resolution. [ABSTRACT FROM PUBLISHER]

We present the first high quality Nb/Al-based tunnel junctions, fabricated with a superconducting interface onto single crystal substrates of Nb and Ta. Current-voltage measurements down to 1.4 K show a subgap current which is dominated by thermal excitation of quasiparticles, no ohmic or superconducting leakages could be observed. The fabrication process and development steps, such as preparation of ultra-smooth crystal surfaces are described. [ABSTRACT FROM PUBLISHER]

Nb-based superconducting tunnel junctions are being developed as high energy resolution X-ray detectors. Unfortunately, loss of excess quasiparticles at the edges, combined with lateral diffusion, results in an inhomogeneous response. To study this degradation of energy resolution, we manufactured detectors with a Ta trap in the top or bottom electrode away from the tunneling barrier. Excess quasiparticles in this so-called killed electrode will be trapped effectively and thus removed from the tunneling process. The X-ray spectra of the active electrode can be fitted with a model based on classical diffusion of quasiparticles. On junctions with a killed bottom electrode also Low Temperature Scanning Electron Microscopy (LTSEM) measurements have been performed. The X-ray spectra and the LTSEM scans are consistent with each other and with the model. The energy resolution of the junctions presented here is limited by loss of quasiparticles at the edges. [ABSTRACT FROM PUBLISHER]

UV and X-ray astronomy need hyperspectral imaging devices, i.e. large format (1000/spl times/1000) arrays of pixels in which each single-photon event is tagged with spectral information. Such devices permit multicolor imagery and surveys to be obtained with a single camera. Here we discuss the first-stage of development of a new generation of UV/X-ray detectors that will provide 0.1-0.01% energy resolution in an array format. [ABSTRACT FROM PUBLISHER]

We have developed superconducting single-photon imaging X-ray detectors with an energy resolution of 54 eV at 6 keV and a spatial resolution of 1 /spl mu/m over an effective length of 40 /spl mu/m. They utilize a current-sensitive low-noise preamplifier with a dc voltage bias. It has a signal bandwidth of 300 kHz, current noise of i/sub n/=0.26 pA//spl radic/(Hz) and voltage noise of e/sub n/=0.5 nV//spl radic/(Hz) with an input capacitance of 200 pF under operating conditions. Injected pulses with a charge Q=3.7/spl middot/10/sup 6/ electrons have been measured with a standard deviation /spl sigma/Q=3400 electrons, corresponding to an electronic noise of 13 eV at 6 keV. [ABSTRACT FROM PUBLISHER]

Superconducting tunnel junctions show an excellent energy resolution in X-ray detection. A simple procedure is employed to give an overview of the detector characteristics regardless of superconductor materials such as Al, Sn and Nb. By introducing an empirical relationship between junction parameters, the detector characteristics of signal magnitude and energy resolution are reproduced to an acceptable degree. This method gives helpful suggestion for understanding detector performance, and also serves as a guide line for designing tunnel junctions. [ABSTRACT FROM PUBLISHER]

A high quality Nb-based tunnel junction with a dimension of 200 /spl mu/m/spl times/200 /spl mu/m was tested by irradiating with X-rays. Two kinds of stable operation modes were observed by applying a magnetic field with different ramping speeds. The junction exhibited a good response to X-rays of 5.9 keV, and FWHM (full width at half maximum) of 93 eV was obtained. [ABSTRACT FROM PUBLISHER]

We have fabricated Ag/Al/sub 2/O/sub 3//Al tunnel junctions on Si substrates using a new process. This process was developed to fabricate superconducting tunnel junctions (STJs) on the surface of a superconductor. These junctions allow us to study the proximity effect of a superconducting Al film on a normal metal trapping layer. In addition, these devices allow us to measure the hot-electron diffusion constant using a single junction. Lastly these devices will help us optimize the design and fabrication of tunnel junctions on the surface of high-Z, ultra-pure superconducting crystals. [ABSTRACT FROM PUBLISHER]