Mid Sweden University

PERCIVAL is a novel soft X-ray detection system designed for the needs of modern microscopy. By integrating it into the TwinMic end-station at Elettra Sincrotrone Trieste, we conducted an exploratory computational microscopy experiment on biological samples, aiming at evaluating the entire system in a real use-case scenario. We present the methodology to convert the RAW data and our high-resolution image reconstructions.

CoRDIA (Continuous Readout Digitizing Imager Array) is a hybrid pixel detector development targeted to 4th generation synchrotron sources and (continuous) high-rate Free Electron Lasers. Serving the latter it builds upon the concept of the AGIPD detector, employing a charge sensitive preamplifier with adaptive gain switching. The further signal path comprises of a Correlated Double Sampling stage and an 11 bit Analogue to Digital Converter (ADC), serving a sub array of 16 pixels. 128 ADCs connect to a multi-gigabit serial link to drive the images off chip. For this part CoRDIA adopts the "GWT-CC "implementation on the Timepix4 chip by Nikhef. A chip with 256 × 192 pixels will implement 24 of these blocks. Since the links conform to industry standards (IEEE 802.3ae), the subsequent data acquisition can be based on commercial components. Performance targets are a continuous frame rate of ≈150 kHz, single-photon sensitivity at <12 keV, and a dynamic range of a few thousand photons (@ 12 keV) with a silicon sensor. The energy range could be extended using active sensors or sensors from "high-Z "materials towards lower and higher photon energies. 

Percival is a CMOS-based imager with 2 megapixels, also called P2M, designed for photon science experiments. The first generation of the P2M sensor showed some performance issues. Specifically, ADCs in full-speed operation mode are affected by crosstalk and show a non-linear and uncorrectable response. A firmware hack to the readout and data acquisition system has been introduced to partially overcome these effects, at the cost of limiting the frame rate to 83 Hz. Moreover, a non-uniform dark response of the sensor pixels is observed, explained by non-uniform bias currents across the chip: two opposite edges of the sensor cannot be digitized when applying biases that have the centre of the sensor operating normally. These issues are addressed in the re-submission of the chip. In this contribution, we present the current status of the detector and the first results from the re-designed sensor. 

New detectors in photon science experiments produce rapidly-growing volumes of data. For detector developers, this poses two challenges; firstly, raw data streams from detectors must be converted to meaningful images at ever-higher rates, and secondly, there is an increasing need for data reduction relatively early in the data processing chain. An overview of data correction and reduction is presented, with an emphasis on how different data reduction methods apply to different experiments in photon science. These methods can be implemented in different hardware (e.g., CPU, GPU or FPGA) and in different stages of a detector's data acquisition chain; the strengths and weaknesses of these different approaches are discussed.

The CoRDIA project aims to develop an X-ray imager capable of continuous operation in excess of 100 kframe/s. The goal is to provide a suitable instrument for Photon Science experiments at diffraction-limited Synchrotron Rings and Free Electron Lasers considering Continuous Wave operation. Several chip prototypes were designed in a 65 nm process: in this paper we will present an overview of the challenges and solutions adopted in the ASIC design. 

The European X-ray Free Electron Laser (European XFEL) is a cutting-edge user facility that generates per second up to 27,000 ultra-short, spatially coherent X-ray pulses within an energy range of 0.26 to more than 20 keV. Specialized instrumentation, including various 2D X-ray detectors capable of handling the unique time structure of the beam, is required. The one-megapixel AGIPD (AGIPD1M) detectors, developed for the European XFEL by the AGIPD Consortium, are the primary detectors used for user experiments at the SPB/SFX and MID instruments. The first AGIPD1M detector was installed at SPB/SFX when the facility began operation in 2017, and the second one was installed at MID in November 2018. The AGIPD detector systems require a dedicated infrastructure, well-defined safety systems, and high-level control procedures to ensure stable and safe operation. As of now, the AGIPD1M detectors installed at the SPB/SFX and MID experimental end stations are fully integrated into the European XFEL environment, including mechanical integration, vacuum, power, control, data acquisition, and data processing systems. Specific high-level procedures allow facilitated detector control, and dedicated interlock systems based on Programmable Logic Controllers ensure detector safety in case of power, vacuum, or cooling failure. The first 6 years of operation have clearly demonstrated that the AGIPD1M detectors provide high-quality scientific results. The collected data, along with additional dedicated studies, have also enabled the identification and quantification of issues related to detector performance, ensuring stable operation. Characterization and calibration of detectors are among the most critical and challenging aspects of operation due to their complex nature. A methodology has been developed to enable detector characterization and data correction, both in near real-time (online) and offline mode. The calibration process optimizes detector performance and ensures the highest quality of experimental results. Overall, the experience gained from integrating and operating the AGIPD detectors at the European XFEL, along with the developed methodology for detector characterization and calibration, provides valuable insights for the development of next-generation detectors for Free Electron Laser X-ray sources. 

Serial crystallography experiments at synchrotron and X-ray free-electron laser (XFEL) sources are producing crystallographic data sets of ever-increasing volume. While these experiments have large data sets and high-frame-rate detectors (around 3520 frames per second), only a small percentage of the data are useful for downstream analysis. Thus, an efficient and real-time data classification pipeline is essential to differentiate reliably between useful and non-useful images, typically known as ‘hit’ and ‘miss’, respectively, and keep only hit images on disk for further analysis such as peak finding and indexing. While feature-point extraction is a key component of modern approaches to image classification, existing approaches require computationally expensive patch preprocessing to handle perspective distortion. This paper proposes a pipeline to categorize the data, consisting of a real-time feature extraction algorithm called modified and parallelized FAST (MP-FAST), an image descriptor and a machine learning classifier. For parallelizing the primary operations of the proposed pipeline, central processing units, graphics processing units and field-programmable gate arrays are implemented and their performances compared. Finally, MP-FAST-based image classification is evaluated using a multi-layer perceptron on various data sets, including both synthetic and experimental data. This approach demonstrates superior performance compared with other feature extractors and classifiers. 

Pulsed laser heating of an ensemble of Pd nanoparticles, supported by a MgO substrate, is studied by x-ray diffraction. By time-resolved Bragg peak shift measurements due to thermal lattice expansion, the transient temperature of the Pd nanoparticles is determined, which quickly rises by at least 100 K upon laser excitation and then decays within 90 ns. The diffraction experiments were carried out using a Cu x-ray tube, giving continuous radiation, and the hybrid pixel detector Timepix3 operating with single photon counting in a time-of-arrival mode. This type of detection scheme does not require time-consuming scanning of the pump-probe delay. The experimental time resolution is estimated at 15 +/- 5 ns, which is very close to the detector's limit and matches with the 7 ns laser pulse duration. Compared to bulk metal single crystals, it is discussed that the maximum temperature reached by the Pd nanoparticles is higher and their cooling rate is lower. These effects are explained by the oxide support having a lower heat conductivity.

Serial crystallography experiments produce massive amounts of experimental data. Yet in spite of these large-scale data sets, only a small percentage of the data are useful for downstream analysis. Thus, it is essential to differentiate reliably between acceptable data (hits) and unacceptable data (misses). To this end, a novel pipeline is proposed to categorize the data, which extracts features from the images, summarizes these features with the 'bag of visual words' method and then classifies the images using machine learning. In addition, a novel study of various feature extractors and machine learning classifiers is presented, with the aim of finding the best feature extractor and machine learning classifier for serial crystallography data. The study reveals that the oriented FAST and rotated BRIEF (ORB) feature extractor with a multilayer perceptron classifier gives the best results. Finally, the ORB feature extractor with multilayer perceptron is evaluated on various data sets including both synthetic and experimental data, demonstrating superior performance compared with other feature extractors and classifiers. 

The past, current and planned future developments of X-ray imagers in the Photon-Science Detector Group at DESY-Hamburg is presented. the X-ray imagers are custom developed and tailored to the different X-ray sources in Hamburg, including the storage ring PETRA III/IV; the VUV-soft X-ray free electron laser FLASH, and the European Free-Electron Laser. Each source puts different requirements on the X-ray detectors, which is described in detail, together with the technical solutions implemented.