X-ray Detector Research Articles

Exploring Lead-Free (Guanidinium)3Bi2Br9 Perovskite-type Crystal toward X-ray Detection with an Ultralow Detection Limit.

Lead-free bismuth halogen perovskites have emerged as a promising candidate for high-performance X-ray detection, owing to their unique properties of bulk resistivity, significant X-ray absorption capabilities and diminished ion migration. Herein, using the facile low-temperature solution method, we obtained a large-size single crystal of (guanidinium)3Bi2Br9 (GBB), which adopts a zero-dimensional (0D) inorganic perovskite-like framework. The as-grown crystals show high resistivity (3.51 × 1012 Ω cm), low trap density (1.14 × 1010 cm-3) and large carrier mobility-lifetime product (μτ =1.13×10-3 cm2 V-1) under X-ray irradiation. Strikingly, the X-ray detectors fabricated on GBB single crystals exhibit notable performances including low dark current drift, high sensitivity of ~1645.7 µC Gyair-1 cm-2, and ultralow detection limit of ~0.85 nGyair s-1. This detection limit is among the lowest level for the reported 0D perovskite X-ray detectors. This study illuminates the prospective research into novel lead-free hybrid perovskites for the advancement of high-performance detectors of irradiation.

MAPbX3 Perovskite Single Crystals for Advanced Optoelectronic Applications: Progress, Challenges, and Perspective.

Perovskite single crystals have garnered significant attention due to their impressive properties in optoelectronic applications, including long carrier diffusion lengths, low trap-state densities, and enhanced stability. Methylamino lead halide perovskite (MAPbX3, where X is a halogen such as Cl, Br, or I) is a notable example of a metal halide perovskite with desirable properties and ideal cubic perovskites with a tolerance factor between 0.9 and 1.0. MAPbX3 has adjustable bandgap, high thermal and chemical stability, and excellent light absorption capacity. Here the unique characteristics of MAPbX3, including molecular structure, optical absorption properties, and carrier transport of MAPbX3 single crystals are summarized. Universal growth technologies for MAPbX3 single crystals, including inverse temperature crystallization, anti-solvent evaporation crystallization, solvent evaporation method, and single-crystalline thin film, including epitaxial method and space limiting method, are briefly introduced. Additionally, a comprehensive review of MAPbX3 single crystals in various optoelectronic device applications, including photodetectors, X-ray detectors, light-emitting diodes, lasers, and solar cells is mainly discussed. Finally, the current challenges and future prospects of the large-scale preparation and growth of MAPbX3 single crystals are put forward. With the continuous progress of photoelectric technology, more innovative photoelectric applications in the future are expected to bring more convenience and progress.

Enhanced stability and performance of perovskite solar cells and X-ray detectors via MoS2@MoO3 composites integration

Enhanced stability and performance of perovskite solar cells and X-ray detectors via MoS2@MoO3 composites integration

Synchronous Regulation of Charge Transfer and Defects in Perovskite Nanocomposite Films for Enhanced Sensitivity and Stability in Monolithically Integrated X-Ray Imaging Arrays.

Perovskites nanocrystals (PNCs) have garnered significant research interest in X-ray detection due to their strong X-ray absorption capability, and unique advantages in large area and thick film deposition that result from the decoupling of perovskite crystallization from film formation. However, traditional long-chain ligands used in PNCs, such as oleic acid and oleyl amine, suffer from poor conductivity and susceptibility to detachment, which limits the performance of X-ray detectors based on them. In this study, a strategy is proposed to partially replace long-chain ligands with short-chain counterparts like phenethylammoniumbromide (PEABr) and CF3PEABr, during the synthesis of CsPbBr3 PNCs. This approach leads to a lower defect density, enhanced carrier transport, and suppressed ion migration simultaneously in the resulting PNCs. These PNCs are then combined with organic bulk heterojunction to construct the nanocomposite X-ray detectors, which exhibit an impressive sensitivity of 10787 µC Gyair⁻¹ cm⁻2 and stable dark current baseline under a large electric field of ≈17000V cm-1. Finally, a flat panel X-ray imaging sensor is prepared by monolithically integrating the nanocomposite film with a thin-film transistor backplane, enabling high-resolution and real-time X-ray imaging. The image quality is further enhanced through a super-resolution reconstruction approach, effectively facilitating a wide range of practical applications in real-world scenarios.

High Energy X-Ray Detection by MicroPattern Gaseous Detector

High Energy X-Ray Detection by MicroPattern Gaseous Detector

Optimization, analysis, and thermal performance enhancement of the cooling flow channel for a condenser mirror

Condenser mirrors with the ellipsoidal surface type are widely used in laser illuminating systems. Nonetheless, thermal absorption in optical components is unavoidable because of high-energy lasers, leading to a decline in surface shape accuracy. In extreme instances, this can shorten the operational longevity or impair the system’s focusing capabilities. Currently, water cooling is a major technical approach for controlling the thermal deformation of condenser mirrors. This paper proposes an efficient cooling flow channel based on topology optimization methods for high-gradient ellipsoidal optical mirrors. Firstly, topology optimization of the cooling flow channel was performed with the objective function of minimizing average temperature and entransy dissipation. Next, the influence of different design parameters on the optimization results was investigated, and the optimal topological structure was obtained. Then, a thermal–fluid–solid coupled simulation was carried out for a three-dimensional model of the water-cooled condenser mirror to verify the topology optimization design. The results show that when the inlet flow rate is 2.82×10−4m3/s, the surface shape accuracy of the water-cooled condenser mirror (RMS 213.79 nm) equipped with the topology optimization cooling flow channel is reduced by 22.96% compared to that of the water-cooled condenser mirror (RMS 277.66 nm) with the traditional spiral cooling flow channel. Finally, the manufacturability of the optimized model was verified by selective laser melting technology and x-ray detection.

Ultra-stable and Sensitive X-ray Detectors Using 3D Hybrid Perovskitoid Single Crystals.

Organic-inorganic hybrid perovskites (OIHPs) have shown great potential for direct X-ray detection in security screening and medical diagnostics. However, their humidity stability is compromised due to the susceptibility of the structural components to water molecules, thereby limiting their practical application. In this work, stable and sensitive X-ray detection is achieved using high-quality bulk single crystals of the 3D perovskitoid (DMPZ)Pb2Br6 (DPB, DMPZ = N,N'-dimethyl-pyrazinium), wherein N-acid protons are replaced with hydrophobic alkyl groups. Notably, the crystals maintain phase stability after 60 days of immersion in water at room temperature, demonstrating their significant potential for moisture-stable X-ray detectors. Based on the bulk crystals of DPB, the X-ray detectors are successfully fabricated, achieving a high sensitivity of 6437.2 µC Gyair -1 cm-2 at 70V bias and a detection limit low to 46.7 nGyair s-1, outperforming most low-dimensional perovskite detectors. Most strikingly, the detectors retain 79.6% of their initial sensitivity after 14 days of water immersion, highlighting exceptional moisture stability. This work is the first to construct moisture-stable high-performance X-ray detectors using 3D perovskitoid single crystals, advancing the development of stable X-ray detection.

High-Performance Oxide Crystal BaTeW2O9 X-ray Detector with High Stability, Low Detection Limit, and Ultralow Dark Current Drift.

X-ray detection materials and devices have received widespread attention due to their irreplaceable role in the medical, industrial, and military fields. In this paper, BaTeW2O9 (BTW) crystal containing lone pairs of electrons with large atomic numbers and high density is reported as a new type of oxide crystal X-ray detection material. The anisotropic X-ray detection performance of the BTW single crystal (SC) is systematically studied. At 120 keV hard X-ray photon energy, the BTW SC X-ray detectors along the crystallographic a-, b-, and c-axes directions achieved high sensitivities of 371, 404, and 368 μC Gyair-1 cm-2 respectively. More importantly, no dark current drift phenomenon was observed in the BTW SC X-ray detectors. The dark current drifts along the crystallographic a-, b-, and c-axes directions are as low as 7.81 × 10-9, 8.61 × 10-9, and 7.71 × 10-9 nA cm-1 s-1 V-1, respectively. In addition, the BTW SC X-ray detector has an ultralow detection limit of 21.9 nGyair s-1. Our research provides a new X-ray detection material with potential application value and a new material design strategy for the field of radiation detection.

Assessment of a New CT Detector and Filtration Technology: Part 1 - X-ray Beam Characterization and Radiation Dosimetry.

This study evaluated beam quality and radiation dosimetry of a CT scanner equipped with a novel detector and filtration technology called PureVision Optics (PVO). PVO features miniaturized electronics, a detector cut with microblade technology, and increased filtration in order to increase x-ray detection and reduce image noise. We assessed the performance of two similar 320-detector CT scanners: one equipped with PVO and one without. Beam quality was measured by determining the half-value layer (HVL) and effective energy (Eeff) for both scanners using all tube voltages (80 kV, 100 kV, 120 kV, 135 kV) and bowtie filters (small, medium, large) available. Energy correction factors were identified for optically stimulated luminescent dosimeters (OSLDS) compared to a calibrated ionization chamber. Surface and internal doses were measured for an anthropomorphic CT angiography head phantom and a cadaver head scanned with CTDIvol matched as close as possible at the conventional (55.1 mGy) and PVO (55.4 mGy) CT scanners. For all scan settings, the PVO scanner showed significantly higher HVL (range, 4.33-11.02 mm Al) and effective energy (range, 39.4-68.0 keV) values compared to the conventional scanner (HVL, 4.19-8.25 mm Al; effective energy, 38.4-55.2 keV). For equivalent CTDIvol values, the energy-corrected surface skin and lens doses were on average 6.7% lower with the PVO scanner than the conventional scanner (P < 0.01). PVO technology yielded higher HVL and effective energies and, for the same CTDIvol, resulted in lower surface organ doses, indicating a potential for reduced patient radiation exposure in clinical settings.

Phase-dependent materials design and characteristic properties of two-dimensional (2D) halide perovskite single crystals for optoelectronic applications

Two-dimensional organic-inorganic hybrid halide perovskites have garnered much attention owing to their outstanding stability alongside unique quantum-well structures and anisotropic properties, leading to improved charge dynamics. Two-dimensional perovskites can be divided into three phases including Ruddlesden-Popper, Dion-Jacobson, and Alternating cations in the interlayer space phase. Each phase of these perovskites shows distinguished phase-dependent structural and optoelectrical properties. Tuning their properties by designing the materials can be a key strategy to enhance the device performance in optoelectrical applications. Configuration of spacer cations and the control of octahedral layer numbers (n ) can be important parameters in material design, enabling the tuning of dielectric properties, exciton binding energy, and bandgaps, as well as materials structures, thereby influencing stability and charge transport behaviors. In this point, two-dimensional perovskite single crystals can play essential roles in not only understanding phase-dependent intrinsic natures but also enhancing performance of optoelectronic applications, specifically owing to their long carrier diffusion length and enhanced stability with little grain boundaries and low trap density. This review will deliver the strategy of phase-dependent materials design with an understanding of their anisotropic properties and charge dynamics for optoelectronic applications, including photodetectors and X-ray detectors.

Halide perovskites, a game changer for future medical imaging technology.

The accurate detection of x-rays enables broad applications in various fields, including medical radiography, safety and security screening, and nondestructive inspection. Medical imaging procedures require the x-ray detection devices operating with low doses and high efficiency to reduce radiation health risks, as well as expect the flexible or wearable ones that offer more comfortable and accurate diagnosis experiences. Recently, halide perovskites have shown promising potential in high-performance, cost-effective x-ray detection owing to their attractive features, such as strong x-ray absorption, high-mobility-lifetime product, tunable bandgap, fast response, as well as low-cost raw materials, facile processing, and excellent flexibility. In this review, we comprehensively summarize the recent advances in halide perovskite x-ray detectors and imaging, focusing on their application potential in medical imaging technology. We highlight the recent demonstrations and optimizations of halide perovskite x-ray detectors and imaging and their application in medical radiography. Finally, we conclude by pointing out the challenges of perovskite x-ray detection devices for the clinical practical applications and by sharing our perspectives on the potential solutions for driving the field forward.

A flexible active-matrix X-ray detector with a backplane based on two-dimensional materials

A flexible active-matrix X-ray detector with a backplane based on two-dimensional materials

Interpretable COVID-19 chest X-ray detection based on handcrafted feature analysis and sequential neural network.

Deep learning methods have significantly improved medical image analysis, particularly in detecting COVID-19 chest X-rays. Nonetheless, these methodologies frequently inhibit some drawbacks, such as limited interpretability, extensive computational resources, and the need for extensive datasets. To tackle these issues, we introduced two novel algorithms: the Dynamic Co-Occurrence Grey Level Matrix (DC-GLM) and the Contextual Adaptation Multiscale Gabor Network (CAMSGNeT). Ground-glass opacity, consolidation, and fibrosis are key indicators of COVID-19 that are effectively captured by DC-GLM, which is designed to adaptively respond to diverse texture sizes and orientations. It emphasizes coarse texture patterns, adeptly catching significant structural alterations in the texture of chest X-rays, enhancing diagnostic precision by documenting the spatial correlations among pixel intensities and facilitating the detection of both significant and minor irregularities. To enhance coarse feature extraction, we introduced CAMSGNeT, which emphasizes fine features via Contextual Adaptive Diffusion. In contrast to conventional multiscale Gabor filtering, CAMSGNeT improves feature extraction by modifying the diffusion process according to both gradients and local texture complexity. The Contextual Adaptation Diffusion approach adjusts the diffusion coefficient by incorporating both gradient and local variance, enabling intricate texture areas to preserve finer details while smoothing regions are diffused to decrease noise. Air bronchograms and crazy-paving patterns are maintained by this adaptive method, which enhances edge identification and texture characteristics while preserving essential tiny details. Finally, a simple optimized sequential neural network analyzes these refined features, resulting in enhanced classification accuracy. Feature importance analysis improves the model's interpretability by revealing the contributions of individual features to its decisions. Our methodology outperforms numerous state-of-the-art models, achieving 98.27% and 100% accuracy on two datasets, providing a more interpretable, precise, and resource-efficient solution for COVID-19 detection.

Novel Self-Powered Sensitive X-Ray Detection Crystal Bi2Mo0.36W1.64O9 with Effective Functional Motif Coupling in a Quasi-2D Perovskite Structure.

The demand for medical imaging with reduced patient dosage and higher resolution is growing, driving the need for advanced X-ray detection technologies. This paper proposes a design paradigm for X-ray detection semiconductors by coupling constituent motifs through crystal structure engineering. The study introduces a strongly anisotropic Aurivillius-type quasi-2D perovskite structure, combining [Bi2O2]2+ groups with stereochemically active lone pair electrons (SCALPEs) and [W/Mo2O7]2- anionic groups, enabling enhanced X-ray Compton scattering and self-powered capabilities through local electric field ordering. This results in the first self-powered Bi-based tungstate Bi2Mo0.36W1.64O9 (BMWO) X-ray detector, achieving a record self-powered sensitivity of 381 µC Gy-1 cm-2. Additionally, the study demonstrates the imaging capability of a Bi-based perovskite X-ray detector operating in self-driven mode. The work highlights BMWO as a promising candidate for stable direct detection imaging and validates the material design strategy that leverages the large anisotropy of quasi-2D structures for sensitive and self-powered detection.

Study of the TOFPET2c ASIC in time-of-flight detection of x-rays for scatter rejection in medical imaging applications.

Integrating time-of-flight (ToF) measurements in radiography and computed tomography (CT) enables an approach for scatter rejection in imaging systems that eliminates the need for anti-scatter grids, potentially increasing system sensitivity and image quality. However, present hardware dedicated to the time-correlated measurement of X-rays is limited to a small scale and low density. A switch to highly integrated electronics and detectors is needed to progress towards a medium-scale system capable of acquiring images, while offering a timing resolution below 300 ps FWHM to achieve scatter rejection comparable to current grids. &#xD;Approach. Using off-the-shelf photodetectors and readouts designed for ToF positron emission tomography (PET) provides a preliminary evaluation of available high-density systems in the context of ToF scatter rejection. The TOFPET2c ASIC from PETSys showed good potential, offering an established development platform necessary for fast and reliable results, with no known limitation regarding time-correlated detection of medical imaging X-rays (20 keV to 140 keV).&#xD;Main results. Reliable photon detection down to 31 keV was achieved, reaching energy resolutions from 23% to 92% FWHM throughout the desired energy range. Optimal detector timing resolution (DTR) from 250 ps FWHM at 130 keV to 678 ps FWHM at 30 keV was reached. Strong time walk effects were observed, showing a time shift of 642 ps up to 1740 ps between events spanning the energies used in X-ray medical imaging.&#xD;Significance. The TOFPET2c ASIC has shown its potential for ToF scatter rejection, but meets the time resolution requirement of 300 ps FWHM only for limited energies (110 keV to 140 keV). This significant timing degradation observed at lower energies limits the use of the TOFPET2c ASIC for ToF scatter rejection, but offers significant advancements regarding the understanding of the phenomenon arising from the time-correlated detection of X-rays for medical imaging.&#xD.

A Peculiar Feature of the First Ionization Potential Effect Before a Solar Flare Impulsive Phase Observed by MSS-1B, CHASE, and SDO

Abstract The impulsive phase of solar flares is often accompanied by the depletion of the elements with low first ionization potential (FIP), whose abundance decreases from the coronal level to the photospheric level, and then recovers back to the coronal level during the decay phase. Recently, we analyzed the soft X-ray spectroscopic data of the 2024 February 16 flare event observed by the Macao Science Satellite-1B/Soft X-ray Detection Units. Surprisingly, however, it is revealed that the depletion of the low-FIP elements occurred well before the flare impulsive phase. The timing of this change provides important clues about the location of magnetic reconnection, shedding light on the mass and energy transfer between different layers of the solar atmosphere. By examining the multiwavelength data from the Solar Dynamics Observatory and CHASE missions, we found that there was no filament 0.4 hr before the flare eruption. However, an erupting filament was detected in association with the flare event. Based on these features, we propose for the first time that the flare/filament eruption for this event was initiated by magnetic reconnection in the solar chromosphere, rather than in the corona as stated in the standard flare model.

Organic Spacers Modulated Low Dose X-Ray Detection in Hybrid Halide 2D Perovskites: Unveiling Exciton Dynamics.

In this study, we investigate how modulating organic spacers in perovskites influences their X-ray detection performance and reveal the mechanism of low-dose detection with high sensitivity using femtosecond-transient absorption spectroscopy (fs-TAS). Particularly, we employ N,N,N',N'-tetramethyl-1,4-phenylenediammonium (TMPDA) and N,N-dimethylphenylene-p-diammonium (DPDA) as organic spacers to synthesize 2D perovskite single crystals (SCs). We find that DPDA-based SCs exhibit reduced interplanar spacing between inorganic layers, leading to increased lattice packing. Density functional theory (DFT) results indicate the reduced effective mass and lower lattice distortion in (DPDA)PbBr4 suppressing the formation of self-trapped exciton (STEs) and electron-phonon coupling and enhancing carrier delocalization in these SCs. Further, X-ray detection measurements reveal that (DPDA)PbBr4 demonstrates higher sensitivity than (TMPDA)PbBr4, attributed to its enhanced carrier delocalization, and higher mobility-lifetime product. The limit of detection (LoD) for (DPDA)PbBr4 is determined to be 13 nGy/s, significantly lower than both commercial detectors and state-of-the-art perovskite-based X-ray detectors. Furthermore, fs-TAS study reveals that (DPDA)PbBr4 crystals exhibit prolonged hot STE cooling and decay lifetimes, which directly correlate with their higher sensitivity. This study highlights the impact of organic spacers on X-ray detection performance, providing a framework for designing ultra-low LoD detectors essential for health and security applications.

Cesium-Based Molecular Perovskites With Superior Stability for High-Performance X-Ray Detection.

Metal-free molecular perovskites have shown great potential for X-ray detection due to their tunable chemical structures, low toxicity, and excellent photophysical properties. However, their limited X-ray absorption and environmental instability restrict their practical application. In this study, cesium-based molecular perovskites (MDABCO-CsX3, X = Cl, Br, I) are developed by introducing Cs+ at the B-site to enhance X-ray absorption while retaining low toxicity. The effects of halide modulation on the physical properties and device performance are systematically investigated. Among the variants, MDABCO-CsBr3 exhibited superior environmental stability, attributed to the optimal ionic radius and high chemical stability of Br-. This stability is further enhanced by a higher tolerance factor, which promotes a stable 3D cubic structure and suppresses ion migration within the crystal. Consequently, MDABCO-CsBr3-based X-ray detectors demonstrated reduced ionic migration, minimal dark current drift, and a stable current response under X-ray exposure, achieving a high sensitivity of 4124 µC Gy-1 cm-2 and a low detection limit of 0.45 µGy s-1. Moreover, the devices exhibit excellent thermal stability, operating effectively at temperatures up to 130 °C. These results highlight MDABCO-CsBr3 as a promising candidate for stable and efficient X-ray detection, expanding the applicability of molecular perovskites in advanced radiation detection technologies.

Efficient and Robust Europium(III)-Based Hybrid Lanthanide Scintillators for Advanced X-Ray Imaging.

Scintillators that convert ionizing radiation into low-energy photons are essential for medical diagnostics and industrial inspections. Despite advances in X-ray scintillators, challenges remain in achieving high efficiency, environmental compatibility, stability, and flexibility. Here, we present experimental investigations of a new type of europium(III)-based hybrid ternary complex scintillators for improved X-ray detection and imaging. Benefiting from the synergistic interaction between dual organic ligands and lanthanide ions, the Eu(TTA)3Phen complex demonstrates exceptional radioluminescence and light yield under X-ray excitation, with a detection limit of 19.97 nGy s-1, well below typical radiation doses used in medical diagnostics. Moreover, lanthanide complex Eu(TTA)3Phen exhibited excellent thermal and photostability, showing minimal degradation even after extended X-ray exposure. By integrating with flexible polymer matrices, a high-transmission Eu(TTA)3Phen-PMMA composite film was fabricated for X-ray radiography, demonstrating high spatial resolution (<10 um) and superior image quality across various target samples. These findings hold substantial promise for next-generation X-ray imaging applications, offering high sensitivity, stability, flexibility, and versatility, making them ideally suited for advanced radiographic systems.

Enhanced Pneumonia Detection in Chest X-Rays Using Hybrid Convolutional and Vision Transformer Networks.

The objective of this research is to enhance pneumonia detection in chest X-rays by leveraging a novel hybrid deep learning model that combines Convolutional Neural Networks (CNNs) with modified Swin Transformer blocks. This study aims to significantly improve diagnostic accuracy, reduce misclassifications, and provide a robust, deployable solution for underdeveloped regions where access to conventional diagnostics and treatment is limited. The study developed a hybrid model architecture integrating CNNs with modified Swin Transformer blocks to work seamlessly within the same model. The CNN layers perform initial feature extraction, capturing local patterns within the images. At the same time, the modified Swin Transformer blocks handle long-range dependencies and global context through window-based self-attention mechanisms. Preprocessing steps included resizing images to 224x224 pixels and applying Contrast Limited Adaptive Histogram Equalization (CLAHE) to enhance image features. Data augmentation techniques, such as horizontal flipping, rotation, and zooming, were utilized to prevent overfitting and ensure model robustness. Hyperparameter optimization was conducted using Optuna, employing Bayesian optimization (Tree-structured Parzen Estimator) to fine-tune key parameters of both the CNN and Swin Transformer components, ensuring optimal model performance. The proposed hybrid model was trained and validated on a dataset provided by the Guangzhou Women and Children's Medical Center. The model achieved an overall accuracy of 98.72% and a loss of 0.064 on an unseen dataset, significantly outperforming a baseline CNN model. Detailed performance metrics indicated a precision of 0.9738 for the normal class and 1.0000 for the pneumonia class, with an overall F1-score of 0.9872. The hybrid model consistently outperformed the CNN model across all performance metrics, demonstrating higher accuracy, precision, recall, and F1-score. Confusion matrices revealed high sensitivity and specificity with minimal misclassifications. The proposed hybrid CNN-ViT model, which integrates modified Swin Transformer blocks within the CNN architecture, provides a significant advancement in pneumonia detection by effectively capturing both local and global features within chest X-ray images. The modifications to the Swin Transformer blocks enable them to work seamlessly with the CNN layers, enhancing the model's ability to understand complex visual patterns and dependencies. This results in superior classification performance. The lightweight design of the model eliminates the need for extensive hardware, facilitating easy deployment in resource-constrained settings. This innovative approach not only improves pneumonia diagnosis but also has the potential to enhance patient outcomes and support healthcare providers in underdeveloped regions. Future research will focus on further refining the model architecture, incorporating more advanced image processing techniques, and exploring explainable AI methods to provide deeper insights into the model's decision-making process.