Pixel Detector Research Articles

Calibration procedures and data correction of ePix100 detectors at the European XFEL

The European XFEL is a research facility that delivers extremely bright and short coherent X-ray pulses of tunable energy at MHz repetition rate, providing unprecedented capabilities to conduct scientific research across multiple domains. Among the suite of deployed detectors, several ePix100 modules, belonging to the family of ePix detectors developed at SLAC, are used. These charge-integrating hybrid pixel detectors offer single-photon resolution for energies above 2 keV and a dynamic range of 100 photons at 8 keV. Their low noise, small pixel size, compact dimensions, maneuverability and vacuum compatibility make them an attractive choice for some of the hard X-ray instruments at the European XFEL for imaging, spectroscopy, and scattering experiments.The European XFEL is committed to providing users with completely corrected detector data. To achieve this goal, periodic calibration procedures are conducted to generate calibration constants that allow the conversion of raw detector output into physically meaningful information through a series of successive data correction steps. In this work, an overview of the ePix100 calibration procedures and correction algorithms will be provided, with a focus on particularly relevant processes for this detector, such as common mode noise and charge sharing correction.

Quantum-imaging detection of secondary neutrons in proton radiotherapy fields

Secondary radiation fields encountered in proton radiotherapy environments contain different particle species produced in a broad range of energies and directions. Experimental knowledge of the composition and spectral characteristics of such complex fields is valuable for operation and protection of instruments and personnel, design and optimization of irradiations as well as planning and validation of treatment plans. The neutron component, which are produced with non-negligible yield, is in particular challenging to measure and discriminate from other radiations by conventional detectors. In order to measure in such complex fields the neutron component, both fast and thermal, we make use of the semiconductor pixel detector Timepix3 equipped with a silicon sensor and a neutron converter mask. The detector was before calibrated with well-defined neutron fields. In this work, we characterize the secondary radiation field and examine in particular the neutron component behind a large water-equivalent phantom irradiated by a 190 MeV clinical proton beam. The detected neutrons have a predominant fast neutron component. No thermal neutrons are observed in the measured data. The neutron-induced interactions in the detector are resolved in a high background with enhanced discrimination by quantum-imaging visualization, micrometer scale pattern recognition and high-resolution spectral-sensitive tracking of single particles. Detailed results are provided in wide range in terms of composition of the mixed-radiation field, total and partial fluxes and dose rates as well as particle deposited dose and linear-energy-transfer (LET) spectra.

Brain tumor image pixel segmentation and detection using an aggregation of GAN models with vision transformer

AbstractA number of applications in the field of medical analysis require the difficult and crucial tasks of brain tumor detection and segmentation from magnetic resonance imaging (MRI). Given that each type of brain imaging provides distinctive information about the specifics of each tumor component, in order to create a flexible and successful brain tumor segmentation system, we first suggest a normalization preprocessing method along with pixel segmentation. Then creating synthetic images is advantageous in many fields thanks to generative adversarial networks (GANs). In contrast, combining different GANs may enable understanding of the distributed features but it can make the model very complex and confusing. Standalone GAN may only retrieve the localized features in the latent version of an image. To achieve global and local feature extraction in a single model, we have used a vision transformer (ViT) along with a standalone GAN which will further improve the similarity of the images and can increase the performance of the model for detection of tumor. By effectively overcoming the constraint of data scarcity, high computational time, and lower discrimination capability, our suggested model can comprehend better accuracy, and lower computational time and also give the understanding of the information variance in various representations of the original images. The proposed model was evaluated on the BraTS 2020 dataset and Masoud2021 dataset, that is, a combination of the three datasets SARTAJ, Figshare, and BR35H. The obtained results demonstrate that the suggested model is capable of producing fine‐quality images with accuracy and sensitivity scores of 0.9765 and 0.977 on the BraTS 2020 dataset as well as 0.9899 and 0.9683 on the Masoud2021 dataset.

Development of time-resolved photoluminescence microscopy of semiconductor materials and devices using a compressed sensing approach

Charge carrier lifetime is a key property of semiconductor materials for photonic applications. One of the most established methods for measuring lifetimes is time-resolved photoluminescence (TRPL), which is typically performed as a single-point measurement. In this paper, we demonstrate a new time-correlated single photon counting method (TCSPC) for TRPL microscopy, for which spatial information can be achieved without requiring point-by-point scanning through the use of a compressed sensing (CS) approach. This enables image acquisition with a single pixel detector for mapping the lifetime of semiconductors with high repeatability. The methodology for signal acquisition and image reconstruction was developed and tested through simulations. Effects of noise levels on the reliability and quality of image reconstruction were investigated. Finally, the method was implemented experimentally to demonstrate a proof-of-concept CS TCSPC imaging system for acquiring TRPL maps of semiconductor materials and devices. TRPL imaging results of a semiconductor device acquired using a CS approach are presented and compared with results of TRPL mapping of the same excitation area measured through a point-by-point method. The feasibility of the methodology is demonstrated, the benefits and challenges of the experimental prototype system are presented and discussed.

Integration and first operation of the Gotthard-II detector at European XFEL

Gotthard-II (G-II) is a 1-D silicon microstrip hybrid detector developed by the Paul Scherrer Institut within the framework of a collaboration agreement with the European XFEL. The ASIC features a dynamic gain switching architecture, in order to cope with the luminosity of European XFEL, and a 12-bit analog-to-digital converter with a sampling/conversion rate of more than 18 MS/s as well as a Static random-access memory, making it capable of matching the European XFEL pulse train structure, thus acquiring up to 2700 images at 4.5 MHz per burst. The sensor’s strip pitch can be either of 50 μm or 25 μm , for a total of 1280 or 2560 output channels per detector, respectively, with a spectral sensitivity that allows either X-ray detection (optimized in the 5–20 keV range) or visible light detection. Its exceptionally good compliance with the European XFEL beam conditions will make G-II the most widely employed detector across the facility, with a total of 29 modules of different flavors that will be installed in scientific instruments and beam diagnostic setups. Although the detector will be predominantly used for spectroscopic measurements it will have a variety of other applications, including X-ray diffraction/emission/absorption experiments, relative pulse arrival time monitoring (of fundamental importance for pump–probe experiments), spectral diagnostics, and beam quality monitoring, with the possibility for the detector itself to generate a veto patterns for the large area MHz framerate pixel detectors employed at the scientific instruments, such as AGIPD, LPD and DSSC. In this paper, an overview of G-II detector technology and its usage at the European XFEL will be presented; the focus will then move on towards the process of detector integration in the European XFEL control system, data acquisition, and data correction infrastructure, highlighting its challenges. Finally, an overview of the first results obtained at scientific instruments will be given.

The first test of a monolithic silicon pixel detector ASIC for the detection of electromagnetic showers of TeV energy in the FASER experiment at the LHC

The FASER experiment at the LHC is designed to look for new, long-lived fundamental particles. A W-Si preshower detector is currently under construction, with the objective of enabling the discrimination of photon pairs with O(TeV) energies and separation down to 200 μm, extending the discovery potential of the experiment. The detector will be based on a new monolithic silicon pixel sensor in 130 nm SiGe BiCMOS. The first test of the ASIC from a pre-production run shows that the building blocks of the monolithic silicon pixel detector are functional.

Vicarious calibration of the Tropospheric Monitoring Instrument (TROPOMI) short-wave infrared (SWIR) module over the Railroad Valley Playa

Abstract. The short-wave infrared (SWIR) module of the Tropospheric Monitoring Instrument (TROPOMI) on board the ESA's Sentinel-5 precursor (S5p) satellite has been very stable during its 5 years in orbit. Calibration was performed on the ground, complemented by measurements during in-flight instrument commissioning. The radiometric response and general performance of the SWIR module are monitored by on-board calibration sources. We show that after 5 years in orbit, TROPOMI-SWIR has continued to show excellent performance with degradation of at most 0.1 % in transmission and having lost less than 0.3 % of the detector pixels. Independent validation of the instrument calibration, via vicarious calibration, can be done through comparisons with ground-based reflectance data. In this work, ground measurements at the Railroad Valley Playa, a valley in central Nevada that is often used as a reference for satellite measurements, are used to perform vicarious calibration of the TROPOMI-SWIR measurements. This is done using dedicated measurement campaigns as well as automated reflectance measurements within the RADCALNET programme. As such, TROPOMI-SWIR is an excellent test case to explore the methodology of vicarious calibration applied to infrared spectroscopy. Using methodology developed for the vicarious calibration of the OCO-2 and GOSAT missions, the absolute radiometry of TROPOMI-SWIR performance is independently verified to be stable down to ∼ 6 %–10 % using the Railroad Valley when both the absolute and relative radiometric calibrations are applied. Differences with the on-board calibration originate from the bidirectional reflection distribution function (BRDF) effects of the desert surface, the large variety in viewing angles, and the different sizes of footprints of the TROPOMI pixels. Vicarious calibration is shown to be an additional valuable tool in validating radiance-level performances of infrared instruments such as TROPOMI-SWIR in the field of atmospheric composition. It remains clear that for instruments of similar design and resolution to TROPOMI-SWIR, on-board calibration sources will continue to provide superior results due to the limitations of the vicarious calibration method.

Real-time electron clustering in an event-driven hybrid pixel detector

Event-driven hybrid pixel detectors with nanosecond time resolution have opened up novel pathways in modern ultrafast electron microscopy, for example in hyperspectral electron-energy loss spectroscopy or free-electron quantum optics. However, the impinging electrons typically excite more than one pixel of the device, and an efficient algorithm is therefore needed to convert the measured pixel hits to real single-electron events. Here we present a robust clustering algorithm that is fast enough to find clusters in a continuous stream of raw data in real time. Each tuple of position and arrival time from the detector is continuously compared to a buffer of previous hits until the probability of a merger with an old event becomes irrelevant. In this way, the computation time becomes independent of the density of electron arrival and the algorithm does not break the operation chain. We showcase the performance of the algorithm with a ‘timepix’ camera in two regimes of electron microscopy, in continuous beam emission and laser-triggered femtosecond mode.

A lightweight encoder–decoder network for automatic pavement crack detection

AbstractCracks are the most common damage type on the pavement surface. Usually, pavement cracks, especially small cracks, are difficult to be accurately identified due to background interference. Accurate and fast automatic road crack detection play a vital role in assessing pavement conditions. Thus, this paper proposes an efficient lightweight encoder–decoder network for automatically detecting pavement cracks at the pixel level. Taking advantage of a novel encoder–decoder architecture integrating a new type of hybrid attention blocks and residual blocks (RBs), the proposed network can achieve an extremely lightweight model with more accurate detection of pavement crack pixels. An image dataset consisting of 789 images of pavement cracks acquired by a self‐designed mobile robot is built and utilized to train and evaluate the proposed network. Comprehensive experiments demonstrate that the proposed network performs better than the state‐of‐the‐art methods on the self‐built dataset as well as three other public datasets (CamCrack789, Crack500, CFD, and DeepCrack237), achieving F1 scores of 94.94%, 82.95%, 95.74%, and 92.51%, respectively. Additionally, ablation studies validate the effectiveness of integrating the RBs and the proposed hybrid attention mechanisms. By introducing depth‐wise separable convolutions, an even more lightweight version of the proposed network is created, which has a comparable performance and achieves the fastest inference speed with a model parameter size of only 0.57 M. The developed mobile robot system can effectively detect pavement cracks in real scenarios at a speed of 25 frames per second.

An ultra-light helium cooled pixel detector for the Mu3e experiment

The Mu3e experiment searches for the lepton flavour violating decay μ + → e + e - e + with a target sensitivity of 1 event in 1016 decays.To achieve this goal, the experiment must minimize the material budget.The pixel detector uses High-Voltage Monolithic Active Pixel Sensors (HV-MAPS) which are thinned down to 50 μm.Combined with gaseous helium as low density coolant, this results in only X/X 0 ≈ 0.1% per tracking layer.Both helium cooling and HV-MAPS are a novelty for particle physics experiments.Here, the work on successfully cooling a pixel tracker using gaseous helium, and performance data of the final HV-MAPS used by Mu3e, the MuPix11, is presented.The thermal studies focus on the two inner tracking layers, the Mu3e vertex detector, and the first operation of a functional thin pixel detector cooled with gaseous helium.Miniature turbo compressors are found to be sufficient to cool thin silicon pixel detectors at heat densities of up to 350 mW/cm2.The presented results demonstrate the feasibility of using HV-MAPS combined with gaseous helium as a coolant for an ultra-thin pixel detector exploring new frontiers in lepton flavor.

TCAD Simulation of X-ray irradiated Si microstrip detector : Impact on full depletion voltage and leakage current

In the intense x-ray radiation environment at synchrotron sources, it is reported that the performance of the silicon pixel detectors degrades with an increasing x-ray dose up to 10 MGy. To study the impact of x-ray irradiation effects in the n-Fz Si microstrip detector, the microscopic radiation damage parameters of x-ray radiation were extracted from the current–voltage, and capacitance-voltage experiments on test Si microstrip detector. The damage parameters are implemented in Synopsys TCAD. In this paper, we have irradiated the test structure up to 10 MGy, and the results on full depletion voltage, and leakage current are compared with the TCAD simulation results. A very good agreement in between experimental and simulation results is observed in the leakage current for the non-irradiated, and 1 MGy irradiated detectors, where for high doses up to 10 MGy, experimental leakage current was fifty times higher than the simulated leakage current at full depletion voltage. The full depletion voltage in 0 MGy detector is also well matched with the simulation result, and further, it shows the full depletion voltage performance of x-ray irradiated detector. Finally, the new detector design specifications and process parameters are proposed for the optimum performance of the radiation hard p+n Si pixel detector equipped with guard rigs at cut edge for the next generation photon science applications.

Predictive analysis of the power spectral irradiance from blackbody radiation source using single pixel detector

Accurate spectral irradiance measurement in the near-infrared range is significant for the design and characterization of photodetector and photovoltaic cells. Approximation method is commonly used to solve for the input power using estimated spectral irradiance, where the dependency on wavelength and temperature remains uncertain. This study aims to determine the power spectrum at different radiation temperatures using a single pixel photodetector, taking into consideration factors such as transmission spectra of alumina radiator, CaF2 collimating lens, responsivity, and measured photocurrent information of photodetectors. Utilizing predictive mathematical model, five commercial photodetectors, including Silicon, Germanium, In0.53Ga0.47As, In0.73Ga0.27As, and In0.83Ga0.17As were used to solve for the power densities as a function of wavelengths at radiation temperatures of 1000 °C and 1500 °C. The spectral irradiance of photodetectors was determined with a percentage difference of <4.9 %, presenting an accurate power density estimation for the spectrum at a wide range of radiation temperatures. Power irradiance data obtained were validated in the narrow wavelength range with 1000 nm, 1400 nm, 1500 nm, and 2000 nm bandpass filters. The reported work demonstrates a simple and efficient way which could contribute to develop a cost-effective method of measuring and determining the spectrum irradiances of objects at different radiation temperatures. This predictive analysis method hopefully intensifies the progress of efforts to reduce the reliance on complex optoelectronic instruments in accurately solving power irradiance information.

Ultrafast radiographic imaging and tracking: An overview of instruments, methods, data, and applications

Ultrafast radiographic imaging and tracking (U-RadIT) use state-of-the-art ionizing particle and light sources to experimentally study sub-nanosecond transients or dynamic processes in physics, chemistry, biology, geology, materials science and other fields. These processes are fundamental to modern technologies and applications, such as nuclear fusion energy, advanced manufacturing, communication, and green transportation, which often involve one mole or more atoms and elementary particles, and thus are challenging to compute by using the first principles of quantum physics or other forward models. One of the central problems in U-RadIT is to optimize information yield through, e.g. high-luminosity X-ray and particle sources, efficient imaging and tracking detectors, novel methods to collect data, and large-bandwidth online and offline data processing, regulated by the underlying physics, statistics, and computing power. We review and highlight recent progress in: (a.) Detectors such as high-speed complementary metal-oxide semiconductor (CMOS) cameras, hybrid pixelated array detectors integrated with Timepix4 and other application-specific integrated circuits (ASICs), and digital photon detectors; (b.) U-RadIT modalities such as dynamic phase contrast imaging, dynamic diffractive imaging, and four-dimensional (4D) particle tracking; (c.) U-RadIT data and algorithms such as neural networks and machine learning, and (d.) Applications in ultrafast dynamic material science using XFELs, synchrotrons and laser-driven sources. Hardware-centric approaches to U-RadIT optimization are constrained by detector material properties, low signal-to-noise ratio, high cost and long development cycles of critical hardware components such as ASICs. Interpretation of experimental data, including comparisons with forward models, is frequently hindered by sparse measurements, model and measurement uncertainties, and noise. Alternatively, U-RadIT make increasing use of data science and machine learning algorithms, including experimental implementations of compressed sensing. Machine learning and artificial intelligence approaches, refined by physics and materials information, may also contribute significantly to data interpretation, uncertainty quantification and U-RadIT optimization.

Seven general radiography x-ray detectors with pixel sizes ranging from 175 to 76 μm: technical evaluation with the focus on orthopaedic imaging

Aim. Flat panel detectors with small pixel sizes general can potentially improve imaging performance in radiography applications requiring fine detail resolution. This study evaluated the imaging performance of seven detectors, covering a wide range of pixel sizes, in the frame of orthopaedic applications. Material and methods. Pixel sizes ranged from 175 (detector A175) to 76 μm (detector G76). Modulation transfer function (MTF) and detective quantum efficiency (DQE) were measured using International Electrotechnical Commission (IEC) RQA3 beam quality. Threshold contrast (C T) and a detectability index (d′) were measured at three air kerma/image levels. Rabbit shoulder images acquired at 60 kV, over five air kerma levels, were evaluated in a visual grading study for anatomical sharpness, image noise and overall diagnostic image quality by four radiologists. The detectors were compared to detector E124. Results. The 10% point of the MTF ranged from 3.21 to 4.80 mm−1, in going from detector A175 to detector G76. DQE(0.5 mm−1) measured at 2.38 μGy/image was 0.50 ± 0.05 for six detectors, but was higher for F100 at 0.62. High frequency DQE was superior for the smaller pixel detectors, however C T for 0.25 mm discs correlated best with DQE(0.5 mm−1). Correlation between C T and the detectability model was good (R 2 = 0.964). C T for 0.25 mm diameter discs was significantly higher for D150 and F100 compared to E124. The visual grading data revealed higher image quality ratings for detectors D125 and F100 compared to E124. An increase in air kerma was associated with improved perceived sharpness and overall quality score, independent of detector. Detectors B150, D125, F100 and G76, performed well in specific tests, however only F100 consistently outperformed the reference detector. Conclusion. Pixel size alone was not a reliable predictor of small detail detectability or even perceived sharpness in a visual grading analysis study.

Qualification of the X-ray spectral performance of the DEPFET pixels of the DSSC imager

The first DEPFET module (128 x 512 pixels) of the DSSC pixel detector, designed for user experiments at the European XFEL, has been fully instrumented and an experimental campaign has been carried out with X-ray lines to qualify the main performance figures and to collect calibration data. X-ray spectra fitting has been optimized with consideration to the main sources of systematic errors to achieve gain calibration within 1% accuracy, which is a key issue for its successful operation at the European XFEL. The most important result is the equivalent noise charge of 16 el rms on average. This shows the potential of the DEPFET-based pixel to reach single-photon imaging down to the lowest photon energy (0.25 keV) at 4.5 MHz frame frequency that can be extrapolated at camera level with high confidence.

Thermal neutron detection and track recognition method in reference and out-of-field radiotherapy FLASH electron fields using Timepix3 detectors.

Objective.This work presents a method for enhanced detection, imaging, and measurement of the thermal neutron flux.Approach. Measurements were performed in a water tank, while the detector is positioned out-of-field of a 20 MeV ultra-high pulse dose rate electron beam. A semiconductor pixel detector Timepix3 with a silicon sensor partially covered by a6LiF neutron converter was used to measure the flux, spatial, and time characteristics of the neutron field. To provide absolute measurements of thermal neutron flux, the detection efficiency calibration of the detectors was performed in a reference thermal neutron field. Neutron signals are recognized and discriminated against other particles such as gamma rays and x-rays. This is achieved by the resolving power of the pixel detector using machine learning algorithms and high-resolution pattern recognition analysis of the high-energy tracks created by thermal neutron interactions in the converter.Main results. The resulting thermal neutrons equivalent dose was obtained using conversion factor (2.13(10) pSv·cm2) from thermal neutron fluence to thermal neutron equivalent dose obtained by Monte Carlo simulations. The calibrated detectors were used to characterize scattered radiation created by electron beams. The results at 12.0 cm depth in the beam axis inside of the water for a delivered dose per pulse of 1.85 Gy (pulse length of 2.4μs) at the reference depth, showed a contribution of flux of 4.07(8) × 103particles·cm-2·s-1and equivalent dose of 1.73(3) nSv per pulse, which is lower by ∼9 orders of magnitude than the delivered dose.Significance. The presented methodology for in-water measurements and identification of characteristic thermal neutrons tracks serves for the selective quantification of equivalent dose made by thermal neutrons in out-of-field particle therapy.

In-pixel AI for lossy data compression at source for X-ray detectors

Integrating neural networks for data compression directly in the Read-Out Integrated Circuits (ROICs), i.e. the pixelated front-end, would result in a significant reduction in off-chip data transfer, overcoming the I/O bottleneck. Our ROIC test chip (AI-In-Pixel-65) is designed in a 65 nm Low Power CMOS process for the readout of pixelated X-ray detectors. Each pixel consists of an analog front-end for signal processing and a 10b analog-to-digital converter operating at 100KSPS. We compare two non-reconfigurable techniques, Principal Component Analysis (PCA) and an AutoEncoder (AE) as lossy data compression engines implemented within the pixelated area. The PCA algorithm achieves 50× compression, adds one clock cycle latency, and results in a 21% increase in the pixel area. The AE achieves 70× compression, adds 30 clock cycle latency, and results in a similar area increase.

Mask-based single-pixel tracking and imaging for moving objects.

Tracking and imaging for high-speed moving objects have a wide range of application prospects in many fields, such as transportation and security monitoring. In this paper, the chrome plated masks are designed to carry geometric moment and random binary encoding patterns, combined with single pixel detectors, to achieve real-time tracking and imaging of fast-moving object. By using the geometric moment principle to obtain the motion trajectory of the object, coding sub-patterns and corresponding detection signals are extracted at different positions to reconstruct the image of the object. Multiple optical paths are established to avoid the side effects of motion error, and a dedicated calibration approach is proposed to improve the accuracy of tracking. The feasibility of the method is demonstrated by simulations and experiments. The proposed scheme, which modulates light with static mask instead of spatial light modulator (SLM), improves the speed and spectral range meanwhile reduces the system cost.

Extraction of Actual Faults with Adjusting the Pixel Width Parameter to Remove Undesired Noise Pixels in the Image (RPW)

Image Denoising, Deblurring, and Enhancement techniques are most commonly used on the images to reduce or completely remove the noise. The noisy images are not capable of perfectly using the solution of the desired problems such as object edge detection, object segmentation, and object classification. Because the edges of these objects have much bluer or more noise pixels for clearly stable detection. The main motivation of this study is to solve the problem of detection and elimination of the undesired noisy pixels on the encountered images. These noisy pixels are needed to be removed from the obtained images which are the results of throughout determined image processing steps. The main reason for this study motivation come out that to find the actual inscription fault has some noisy (undesired) pixels when extracting the true difference between the two images has been subtracted from each other. The subtracted image results are used in the inscription inspection process that controls the accuracy of the inscription quality. In the inscription inspection process, subtracted image results are used to determine the accuracy of the inscription quality. These subtracted images are formed by subtraction from each other of reference images and sample images. In these subtracted images if truly exist inscriptions faults or sometimes that could be occurred undesired noisy pixels at the same time in the subtraction process. This study focused on detecting and eliminating the undesired noisy pixels in order to reach actual inscription faults in the images. Thus, the remove pixels as width algorithm (RPW) has been developed and applied to these specified images.

Comparative study of conventional and synchrotron X-ray electron densities on molecular crystals.

Five different electron density datasets obtained from conventional and synchrotron single crystal X-ray diffraction experiments are compared. The general aim of the study is to investigate the quality of data for electron density analysis from current state-of-the-art conventional sources, and to see how the data perform in comparison with high-quality synchrotron data. A molecular crystal of melamine was selected as the test compound due to its ability to form excellent single crystals, the light atom content, and an advantageous suitability factor of 3.6 for electron density modeling. These features make melamine an optimal system for conventional X-ray diffractometers since the inherent advantages of synchrotron sources such as short wavelength and high intensity are less critical in this case. Data were obtained at 100 K from new in-house diffractometers Rigaku Synergy-S (Mo and Ag source, HyPix100 detector) and Stoe Stadivari (Mo source, EIGER2 1M CdTe detector), and an older Oxford Diffraction Supernova (Mo source, Atlas CCD detector). The synchrotron data were obtained at 25 K from BL02B1 beamline at SPring-8 in Japan (λ = 0.2480 Å, Pilatus3 X 1M CdTe detector). The five datasets were compared on general quality parameters such as resolution, ⟨I/σ⟩, redundancy and R factors, as well as the more model specific fractal dimension plot and residual density maps. Comparison of the extracted electron densities reveals that all datasets can provide reliable multipole models, which overall convey similar chemical information. However, the new laboratory X-ray diffractometers with advanced pixel detector technology clearly measure data with significantly less noise and much higher reliability giving densities of higher quality, compared to the older instrument. The synchrotron data have higher resolution and lower measurement temperature, and they allow for finer details to be modeled (e.g. hydrogen κ parameters).