Detector Structure Research Articles

Feasibility study of TPC detector at high luminosity Z pole on the circular collider

With the development of the circular collider, it is necessary to make accurate physics experimental measurements of particle properties at higher luminosity [Formula: see text] pole. Micro-pattern gaseous detectors (MPGDs), which contain gaseous electron multiplier (GEM) and micro-mesh gaseous structures (Micromegas), have excellent potential for development as the readout devices of the time projection chamber (TPC) tracker detector. To meet the updated physics requirements of the high luminosity [Formula: see text] from the preliminary concept design report (preCDR) to concept design report (CDR) at the circular electron–positron collider (CEPC). In this paper, the space charge distortion of the TPC detector is simulated with the CEPC beam structure. Using the multi-physics simulation software package, the distribution of ion estimated by Geant4 is used as the input for the differential equation, and the relationship between the ion density distribution and electric field in the detector chamber is simulated. These simulation results show that the maximum deviation for Higgs [Formula: see text] meets the performance requirements in CEPC TPC detector at the high luminosity [Formula: see text] pole, while it is still a considerable challenge for [Formula: see text] pole, with the maximum deviation [Formula: see text]. According to the previous developments, the cascaded structure of GEM and Micromegas detector has been measured. The new considerations of the detector’s requirements were given, the gain needs to be reached to about 2000 with IBF[Formula: see text]Gain under 0.1, and IBF means the ions back flow ratio of the detector. The pixel TPC is a potential option to replace the traditional MPGDs with the low gain, low occupancy, and outstanding pattern recognition. Finally, some update parameters and experiments results were compared.

SAVSDN: A Scene-Aware Video Spark Detection Network for Aero Engine Intelligent Test.

Due to carbon deposits, lean flames, or damaged metal parts, sparks can occur in aero engine chambers. At present, the detection of such sparks deeply depends on laborious manual work. Considering that interference has the same features as sparks, almost all existing object detectors cannot replace humans in carrying out high-precision spark detection. In this paper, we propose a scene-aware spark detection network, consisting of an information fusion-based cascading video codec-image object detector structure, which we name SAVSDN. Unlike video object detectors utilizing candidate boxes from adjacent frames to assist in the current prediction, we find that efforts should be made to extract the spatio-temporal features of adjacent frames to reduce over-detection. Visualization experiments show that SAVSDN can learn the difference in spatio-temporal features between sparks and interference. To solve the problem of a lack of aero engine anomalous spark data, we introduce a method to generate simulated spark images based on the Gaussian function. In addition, we publish the first simulated aero engine spark data set, which we name SAES. In our experiments, SAVSDN far outperformed state-of-the-art detection models for spark detection in terms of five metrics.

Ultimate detectivity of multiple-stage interband cascade infrared photodetectors

In this work, we theoretically demonstrate that the ultimate detectivities in multi-stage interband cascade infrared photodetector configurations are higher than what can be achieved in a conventional single-absorber detector structure in any circumstance even including where carrier diffusion length is very long. Detailed derivations are provided to analytically show that in the limit of an infinite diffusion length, the ultimate detectivity of a multiple-stage device is about 11% higher than that of an optimized single-stage device. Furthermore, how the sequence of absorber thicknesses is optimized for maximizing the detectivity is described and discussed. Insights and explanations to the results are presented to improve the understanding, clarify possible confusion with different perspectives in the technical community, and to generate more interest in the development of advanced multi-stage interband cascade infrared photodetectors for various applications.

Carrier localization and miniband modeling of InAs/GaSb based type-II superlattice infrared detectors

Microscopic features of carrier localization, minibands, and spectral currents of InAs/GaSb based type-II superlattice (T2SL) mid-infrared detector structures are studied and investigated in detail. In the presence of momentum and phase-relaxed elastic scattering processes, we show that a self-consistent non-equilibrium Green’s function method within the effective mass approximation can be an effective tool to fairly predict the miniband and spectral transport properties and their dependence on the design parameters such as layer thickness, superlattice periods, temperature, and built-in potential. To benchmark this model, we first evaluate the band properties of an infinite T2SL with periodic boundary conditions, employing the envelope function approximation with a finite-difference discretization within the perturbative eight-band framework. The strong dependence of the constituent material layer thicknesses on the band-edge positions and effective masses, offers a primary guideline to design performance-specific detectors for a wide range of operation. Moving forward, we demonstrate that using a finite T2SL structure in the Green’s function framework, one can estimate the bandgap, band-offsets, density of states and spatial overlap which comply well with the results and the experimental data. Finally, the superiority of this method is illustrated via a reasonable estimation of the band alignments in barrier-based multi-color non-periodic complex T2SL structures. This study, therefore, provides deep physical insights into the carrier confinements in broken-gap heterostructures and sets a perfect stage to perform transport calculations in a full-quantum picture.

Optimization of the rod forces in the reticular support structure of JUNO central detector

The structure of Jiangmen Underground Neutrino Observatory (JUNO) central detector is a complex structure subjected to a complex environment. The inner continuous acrylic spherical shell is connected to the outer reticulated stainless-steel (SS) shell through SS rods, and all these structural components are supported by an SS supporting frame. The inner shell is subjected to considerable buoyancy since the detection liquid inside the inner shell has less density than the outside water. Optimization of load path of such an underground structure subjected to buoyancy and pressure loads is difficult due to these complex situations, and in this paper, we tackle the problem of finding the optimal load path to minimize the rod forces. We adopt three types of design variables relevant to the load path, i.e., rod locations, chimney liquid level, and disc spring stiffness. Specifically, B-spline function is adopted to map the rod locations so as to significantly reduce the number of variables, and the chimney liquid level that influences the pressure distribution is taken as a new type of design variable. Subsequently, a numerical method combining the finite element analysis and a derivative-free optimization algorithm is proposed. Based on the optimization results, influences of the design variables, including their types, number, and initial values, on the optimal solutions are discussed in depth. The results suggest that the chimney liquid level and disc spring stiffness have a global effect of shifting rod force distribution, while distribution of rod forces strongly depends on the rod locations. The proposed method is shown to be effective to find an optimal load path of a complex spherical shell structure under various nonlinear constraints.

A Self-Test, Self-Calibration and Self-Repair Methodology of Thermopile Infrared Detector

To improve the reliability and yield of thermopile infrared detectors, a self-test, self-calibration and self-repair methodology is proposed in this paper. A novel micro-electro-mechanical system (MEMS) infrared thermopile detector structure is designed in this method with a heating resistor building on the center of the membrane. The heating resistor is used as the stimuli of the sensing element on chip to achieve a self-test, and the responsivity related with ambient temperature can be calibrated by the equivalent model between electrical stimuli and physical stimuli. Furthermore, a fault tolerance mechanism is also proposed to localize the fault and repair the detector if the detector fails the test. The simulation results with faults simulated by the Monte Carlo stochastic model show that the proposed scheme is an effective solution to improve the yield of the MEMS thermopile infrared detector.

An edge-on energy-resolved X-ray semiconductor detector

The hyperspectral X-ray imaging has long been sought in various fields from material analysis to medical diagnosis. Here we propose a semiconductor detector structure to realize multi-energy imaging at potentially low cost. The device is designed based on the dramatically energy-dependent attenuation of X-ray in solids. An array or a two-/three-dimensional matrix of semiconductor cells is used to map the X-ray intensity along its trajectory. The X-ray spectrum could be extracted from a Laplace like transform or a regression via supervised machine learning. We conceptually demonstrated an energy-resolved X-ray detection with a regular silicon CMOS camera and a dummy sample of copper wires on top of an aluminum flake. The experiment provides energy-resolved X-ray image of the sample. The demonstration shows an energy resolution of less than 10 keV. We concluded that the proposed edge-on structure is potentially useful as energy-resolved high efficiency low-cost X-ray detectors.

A Comparative Analysison Metal Detection By Using TheConcept of Robotic System With Internet of Things

In this paper we are able to communicate about the awesome today's association of innovation in our existence generates quite a few benefits and disadvantages. However, and to profoundly increase its high first-class affect, maximum technological understanding be conveyed to serve the humankind and society. Researchers can captivating in improvement of sturdy and co-operative robot system that successful of solving hard responsibilities barring any human manage. Steel or any kind of metal detector i.e. one of the robotic(s) system concepts because of its effective work as in assessment manualoperate and very slow common method(s). In the newsletter, 3 fundamental elements which are targeted 1) design a robot that's car-set up sensors that successful of incorporates the sensors of the metallic and impediment of the course; 2) manipulate the robotic device wirelessly by using a pc-primarily based to commanding the robot function by the use of pretty a few units of person’s tips and manipulate the robot pointers by using the usage of the technology of internet of things (iot); and 3) conduct an built-in machine that attaining navigated records by way of metallic detector primarily based on database of IoT. Additionally, noted a assessment of the preceding detector structures and features on numerous deserves. The proposed device a hit of entirely manage the robot gadget additionally.

Anchor Distance for 3D Multi-Object Distance Estimation From 2D Single Shot

Visual perception of the objects in a 3D environment is a key to successful performance in autonomous driving and simultaneous localization and mapping (SLAM). In this letter, we present a real time approach for estimating the distances to multiple objects in a scene using only a single-shot image. Given a 2D Bounding Box (BBox) and object parameters, a 3D distance to the object can be calculated directly using 3D reprojection; however, such methods are prone to significant errors because an error from the 2D detection can be amplified in 3D. In addition, it is also challenging to apply such methods to a real-time system due to the computational burden. In the case of the traditional multi-object detection methods, existing works have been developed for specific tasks such as object segmentation or 2D BBox regression. These methods introduce the concept of anchor BBox for elaborate 2D BBox estimation, and predictors are specialized and trained for specific 2D BBoxes. In order to estimate the distances to the 3D objects from a single 2D image, we introduce the notion of anchor distance based on an object's location and propose a method that applies the anchor distance to the multi-object detector structure. We let the predictors catch the distance prior using anchor distance and train the network based on the distance. The predictors can be characterized to the objects located in a specific distance range. By propagating the distance prior using a distance anchor to the predictors, it is feasible to perform the precise distance estimation and real-time execution simultaneously. The proposed method achieves about 30 FPS speed, and shows the lowest RMSE compared to the existing methods.

Long wavelength InAs/InAsSb superlattice barrier infrared detectors with p-type absorber quantum efficiency enhancement

We studied long and very long wavelength InAs/InAsSb superlattice barrier infrared detectors that contain p-type absorber layers in order to take advantage of the longer electron diffusion length for quantum efficiency (QE) enhancement. While they can achieve higher QE than devices that use only n-type absorbers, their dark current characteristics are affected by the presence of metallurgical and surface p–n junctions, and are best operated under lower biasing conditions where the tunneling dark currents are less pronounced. Rather than using a p-type absorber only, a barrier infrared detector structure with a combination of p- and n-type absorber sections can benefit from a shallower mesa etch that reduces fabrication demands and also decreases the p-type absorber exposed surface area. We compare four complementary barrier infrared detector structures that use an n-type absorber, a combination of p- and n-type absorbers, or a p-type absorber and briefly report results from a 13.3 μm cutoff focal plane array.

Fabrication of a 1024 × 1024 format long wavelength infrared focal plane array based on type-II superlattice and barrier enhanced structure

1024 × 1024 format long-wavelength infrared focal plane arrays are realized using type-II superlattice material with a double-barrier enhanced structure grown on 3″ GaSb substrate. The detector structure material exhibits excellent crystalline quality and uniformity. A 100% cutoff wavelength of ~11.8 μm was obtained at 82 K. A dark current density of 1.4 × 10−6 A/cm2 and a differential resistance-area product RA of 4.7 × 104 Ωcm2 at 49 K, 3.6 × 10−5 A/cm2 and 2.8 × 103 Ωcm2 at 70 K, and 2.5 × 10−4 A/cm2 and 5.5 × 102 Ωcm2 at 82 K, at a reverse bias of ~ 50 mV, were obtained, respectively. At zero bias, the R0A was 5.1 × 104 Ωcm2, 290.6 Ωcm2, and 35.6 Ωcm2 at 49 K, 70 K, and 82 K, respectively. Noise equivalent temperature differences of 37.4 mK at 82 K and 31.9 mK at 70 K were achieved with an integration time of 0.12 ms, a 300 K background and f/2.0 optics. The large format FPA also shows excellent imaging.

A high-performance quantum well infrared photodetector based on semiconductor–metal periodic microstructure

Quantum well infrared detector has been extensively applied in military and civil fields. In order to break through the bottleneck of low quantum efficiency, a novel quantum well infrared photodetector based on SiO2–dielectric–metal microstructure has been proposed and investigated in this paper. The detector is composed of three layers, which are SiO2 particle array on the top, quantum well in the middle layer and metallic film at the bottom. The results shown that the SiO2–dielectric–metal sandwich structure can absorb electromagnetic waves between 14 and 15 µm which the quantum well infrared photodetector work at. In addition, we have studied the influence of the parameters of the detector structure, it is found that the absorption band is insensitive to period of photodetector microstructure and the thickness of SiO2 layer, which indicates the quantum well infrared photodetector has a stable performance. The quantum well infrared detector proposed in this paper has large potential applications in the miniaturization and integration of optoelectronic devices in the future.

Self-powered multilayer radioisotope identification device.

This is a computational study to develop a rugged self-powered Radioisotope Identification Device (RIID). The principle of operation relies on the High Energy Current (HEC) concept (Zygmanski and Sajo, Med Phys. 43 4-15, 2016) with measurement of fast electron currents between low-Z and high-Z thin-film electrodes separated by nanoporous aerogel films in a multilayer detector structure whose prototypes were previously investigated (Brivio, Albert, Freund, Gagne, Sajo and Zygmanski, Med Phys, 46 4233-4240, 2019), (Brivio, Albert, Gagne, Freund, Sajo and Zygmanski, J Phys D Appl Phys, 53 265303, 2020). Here, we present an optimal detector design that accounts for a wide energy range (keV-MeV) of x-ray-emitting radioisotopes that are of interest to national security and radiation therapy. We studied numerous multilayer detector geometries with N=1..24 basic detector elements composed of 3 electrodes: N x (Al-aerogel-Ta-aerogel-Al). The thicknesses of electrodes and their total number were varied depending on the incident x-ray spectra and its ability to penetrate and interact with the different layers, producing fast electrons. We used radiation transport simulations to find a balanced geometry that accounts for all energies from 10keV to 6MeV in a single design with relatively few detector elements (N=24). In the balanced design, the electrodes have increasing thickness as a function of depth in the detector, ranging from 0.5μm-Ta and 10μm-Al at the entrance to 10mm-Ta and 2.5mm-Al at the exit. Aerogel thickness was fixed at 50μm. Electron currents forming RIID signals were acquired from all Ta electrodes. A model function M(x, Ei ) representing the detector yield as a function of the cumulative Ta thickness (x) for 70 monoenergetic incident beams (E) was derived. We also investigated the detector response to selected radioactive isotopes (Pd-103, I-125, Pu-239, U-235, Ir-192, Cs-137, Co-60). Additional studies were performed with Bremsstrahlung spectra produced by electron beams in kVp tubes and in MV Linacs used in radiology and radiation therapy departments. We investigated different algorithms for radioisotope identification that would work for unknown unshielded as well as shielded sources. Characteristic features of response functions for monoenergetic beams and radioisotopes were determined and used to develop two inverse algorithms of radioisotope identification. Using these algorithms, we were able to identify the unshielded and shielded sources, quantify the minimum, mean and maximum effective energies of the shielded spectra, and estimate the amount of Compton background in the spectrum. A multilayer sensor based on fast electron current was optimized and studied in its abilities as RIID. A balanced design permits the identification of radioisotopes with of a wide range of keV-MeV energies. The device is low cost, rugged, self-powered and can withstand very high dose rates, allowing deployment in difficult conditions, including radiation incidents. The algorithm we developed for radioisotope identification and spectral unfolding is robust and it is an important component in practical applications.

Accurate spectra for high energy ions by advanced time-of-flight diamond-detector schemes in experiments with high energy and intensity lasers

Time-Of-Flight (TOF) methods are very effective to detect particles accelerated in laser-plasma interactions, but they show significant limitations when used in experiments with high energy and intensity lasers, where both high-energy ions and remarkable levels of ElectroMagnetic Pulses (EMPs) in the radiofrequency-microwave range are generated. Here we describe a novel advanced diagnostic method for the characterization of protons accelerated by intense matter interactions with high-energy and high-intensity ultra-short laser pulses up to the femtosecond and even future attosecond range. The method employs a stacked diamond detector structure and the TOF technique, featuring high sensitivity, high resolution, high radiation hardness and high signal-to-noise ratio in environments heavily affected by remarkable EMP fields. A detailed study on the use, the optimization and the properties of a single module of the stack is here described for an experiment where a fast diamond detector is employed in an highly EMP-polluted environment. Accurate calibrated spectra of accelerated protons are presented from an experiment with the femtosecond Flame laser (beyond 100 TW power and ~ 1019 W/cm2 intensity) interacting with thin foil targets. The results can be readily applied to the case of complex stack configurations and to more general experimental conditions.

Analysis of the Unconcentrated Background of the EPIC pn Camera on Board XMM-Newton

Abstract Our understanding of the background of the EPIC/pn camera on board XMM-Newton is incomplete. This affects the study of extended sources and can influence the predictions of the expected background of future X-ray missions, such as the Advanced Telescope for High Energy Astrophysics (ATHENA). Here we provide new results based on the analysis of the largest data set ever used. We focus on the unconcentrated component of the EPIC/pn background, supposedly related to cosmic rays interacting with detector and telescope structures. We show that the so-called out field-of-view region of the pn detector is actually exposed to the sky. After carefully cleaning from the sky contamination, the unconcentrated background measured in the out field-of-view region does not show significant spatial variations, and its time behavior is anticorrelated with the solar cycle. We find a very tight linear correlation between unconcentrated backgrounds detected in the EPIC/pn and EPIC/MOS2 cameras. This relationship permits the correct evaluation of the pn unconcentrated background of each exposure on the basis of MOS2 data, avoiding the use of the contaminated out field-of-view region of the pn, as done in standard techniques. We find a tight linear correlation between the pn unconcentrated background and the proton flux in the 630–970 MeV energy band, as measured by the EPHIN instrument on board SOHO. Through this relationship, we quantify the contribution of cosmic-ray interaction to the pn unconcentrated background. This reveals a second source that contributes to the pn unconcentrated background for a significant fraction (30%–70%). This agent does not depend on the solar cycle or vary with time and is roughly isotropic. After having ruled out several candidates, we find that the hard X-ray photons of the cosmic X-ray background satisfy all known properties of the constant component. Our findings provide an important observational confirmation of simulation results on ATHENA and suggest that a high-energy particle monitor could contribute decisively to the reproducibility of the background for both experiments on ATHENA.

Characterization of Seamless CdTe Photon Counting X-Ray Detector

Spectrally selective X-ray imaging provides improved material and tissue discrimination in comparison with the state-of-the-art dual energy technologies that are commonly used in medical, industrial, and security applications. Cadmium telluride (CdTe)- and cadmium zinc telluride (CdZnTe)-based line scanners and small size two-dimensional X-ray sensors are emerging to the market, but the need for large-scale panels is axiomatic. In this study, a seamless CdTe tile was developed that enables the implementation of large-sized, energy selective X-ray detector panels. The developed tile consists of a $64\times64$ pixel array (with $150~\mu \text{m}$ pitch) with a necessary substrate, ASIC, and CdTe crystal. The performance of the constructed seamless tile was characterized by focusing on spectral resolution and stability. In addition, a simple pixel trimming method that automates the equalization of each energy selective pixel was developed and analyzed. The obtained results suggest that the proposed concept of seamless (tileable) detector structures is a feasible approach to scale up panel sizes. The seamless tile shows comparable spectral resolution and stability performance with commercial CdTe sensors. The effect of tile to tile variation, the realization of a large-scale panel, as well as the charge sharing performance were left out of the scope and are to be studied in the next phase.

HCE: Hierarchical Context Embedding for Region-Based Object Detection.

State-of-the-art two-stage object detectors apply a classifier to a sparse set of object proposals, relying on region-wise features extracted by RoIPool or RoIAlign as inputs. The region-wise features, in spite of aligning well with the proposal locations, may still lack the crucial context information which is necessary for filtering out noisy background detections, as well as recognizing objects possessing no distinctive appearances. To address this issue, we present a simple but effective Hierarchical Context Embedding (HCE) framework, which can be applied as a plug-and-play component, to facilitate the classification ability of a series of region-based detectors by mining contextual cues. Specifically, to advance the recognition of context-dependent object categories, we propose an image-level categorical embedding module which leverages the holistic image-level context to learn object-level concepts. Then, novel RoI features are generated by exploiting hierarchically embedded context information beneath both whole images and interested regions, which are also complementary to conventional RoI features. Moreover, to make full use of our hierarchical contextual RoI features, we propose the early-and-late fusion strategies (i.e., feature fusion and confidence fusion), which can be combined to boost the classification accuracy of region-based detectors. Comprehensive experiments demonstrate that our HCE framework is flexible and generalizable, leading to significant and consistent improvements upon various region-based detectors, including FPN, Cascade R-CNN, Mask R-CNN and PA-FPN. With simple modification, our HCE framework can be conveniently adapted to fit the structure of one-stage detectors, and achieve improved performance for SSD, RetinaNet and EfficientDet.

Scale-Aware Anchor-Free Object Detection via Curriculum Learning for Remote Sensing Images

Accurate detection of multiclass instance objects in remote sensing images (RSIs) is a fundamental but challenging task in the field of aviation and satellite image processing, which plays a crucial role in a wide range of practical applications. Compared with the natural image-based object detection task, RSIs-based object detection still faces two main challenges: 1) The instance objects often present large variations in object size, and they are densely arranged in the given input images; and 2) Complex background distributions around instance objects tend to cause boundary blurring, making it difficult to distinguish instance objects from the background, resulting in undesired feature learning interference. In this article, to address the abovementioned challenges, we propose a novel RSI anchor-free object detection framework that consists of two key components: a cross-channel feature pyramid network (CFPN) and multiple foreground- attentive detection heads (FDHs). First, an anchor-free baseline detector with the CFPN structure is developed to extract features from different convolutional layers and incorporates these multiscale features through parameterized cross-channel learning processes, learning the semantic relations across different scales and levels. Next, each FDH is designed to predict an attention map to enhance the features of the foreground region in RSIs. Furthermore, under this scale-aware anchor-free baseline detector structure, we design a curriculum-style optimization objective that dynamically reweights training instances during the current training epoch, enabling the detector to receive relatively easy instances that match with its current ability. Experimental results on three publicly available object detection datasets demonstrate that the proposed method outperforms existing object detection methods.

Детектирование терагерцевых электромагнитных волн с помощью проводящих антиферромагнетиков

We investigate a mathematical model of a terahertz electromagnetic wave detector based on a conducting antiferromagnet and a heavy metal. The mechanism of resonant straightening of oscillations is based on the inverse spin Hall effect in a heavy metal under spin pumping from an antiferromagnet. It is shown that the frequency dependence of the constant voltage of the detector has a resonant character with a peak corresponding to the frequency of antiferromagnetic resonance. The sensitivity to an alternating terahertz signal of the proposed detector structure is comparable to the sensitivity of modern detectors based on Schottky and Gunn diodes.

A thermal bonding method for manufacturing Micromegas detectors

For manufacturing Micromegas detectors, the “bulk” method based on photoetching, was successfully developed and widely used in nuclear and particle physics experiments. However, the complexity of the method requires a considerable number of advanced instruments and processing, limiting the accessibility of this method for production of Micromegas detectors. In view of these limitations with the bulk method, a new method based on thermal bonding technique (TBM) has been developed to manufacture Micromegas detectors in a much simplified and efficient way without etching. This paper describes the TBM in detail and presents performance of the Micromegas detectors built with the TBM. The effectiveness of this method was investigated by testing Micromegas detector prototypes built with the method. Both X-rays and electron beams were used to characterize the prototypes in a gas mixture of argon and CO2 (7%). A typical energy resolution of ∼16% (full width at half maximum, FWHM) and an absolute gain greater than 104 were obtained with 5.9 keV X-rays. Detection efficiency greater than 98% and a spatial resolution of ∼65μm were achieved using a 5 GeV electron beam at the DESY test-beam facility. The gas gain of a Micromegas detector could reach up to 105 with a uniformity of better than 10% when the size of the avalanche gap was optimized thanks to the flexibility of the TBM in defining the gap. Additionally, the TBM facilitates the exploration of new detector structures based on Micromegas owing to the much-simplified operation with the method.