Future trends in synchrotron science at NSLS-II

Investigation of fast and efficient lossless compression algorithms for macromolecular crystallography experiments

Structural biology experiments benefit significantly from state-of-the-art synchrotron data collection. One can acquire macromolecular crystallography (MX) diffraction data on large-area photon-counting pixel-array detectors at framing rates exceeding 1000 frames per second, using 200 Gbps network connectivity, or higher when available. In extreme cases this represents a raw data throughput of about 25 GB s-1, which is nearly impossible to deliver at reasonable cost without compression. Our field has used lossless compression for decades to make such data collection manageable. Many MX beamlines are now fitted with DECTRIS Eiger detectors, all of which are delivered with optimized compression algorithms by default, and they perform well with current framing rates and typical diffraction data. However, better lossless compression algorithms have been developed and are now available to the research community. Here one of the latest and most promising lossless compression algorithms is investigated on a variety of diffraction data like those routinely acquired at state-of-the-art MX beamlines.

Investigation of the Single-Particle Scale Structure-Activity Relationship Providing New Insights for the Development of High-Performance Batteries

As electric vehicles, portable electronic devices, and tools have increasingly high requirements for battery energy density and power density, constantly improving battery performance is a research focus. Accurate measurement of the structure-activity relationship of active materials is key to advancing the research of high-performance batteries. However, conventional performance tests of active materials are based on the electrochemical measurement of porous composite electrodes containing active materials, polymer binders, and conductive carbon additives, which cannot establish an accurate structure-activity relationship with the physical characterization of microregions. In this review, in order to promote the accurate measurement and understanding of the structure-activity relationship of materials, the electrochemical measurement and physical characterization of energy storage materials at single-particle scale are reviewed. The potential problems and possible improvement schemes of the single particle electrochemical measurement and physical characterization are proposed. Their potential applications in single particle electrochemical simulation and machine learning are prospected. This review aims to promote the further application of single particle electrochemical measurement and physical characterization in energy storage materials, hoping to achieve 3D unified evaluation of physical characterization, electrochemical measurement, and theoretical simulation at the single particle scale to provide new inspiration for the development of high-performance batteries.

Efficient end-to-end simulation of time-dependent coherent X-ray scattering experiments

Physical optics simulations for beamlines and experiments allow users to test experiment feasibility and optimize beamline settings ahead of beam time in order to optimize valuable beam time at synchrotron light sources like NSLS-II. Further, such simulations also help to develop and test experimental data processing methods and software in advance. The Synchrotron Radiation Workshop (SRW) software package supports such complex simulations. We demonstrate how recent developments in SRW significantly improve the efficiency of physical optics simulations, such as end-to-end simulations of time-dependent X-ray photon correlation spectroscopy experiments with partially coherent undulator radiation (UR). The molecular dynamics simulation code LAMMPS was chosen to model the sample: a solution of silica nanoparticles in water at room temperature. Real-space distributions of nanoparticles produced by LAMMPS were imported into SRW and used to simulate scattering patterns of partially coherent hard X-ray UR from such a sample at the detector. The partially coherent UR illuminating the sample can be represented by a set of orthogonal coherent modes obtained by simulation of emission and propagation of this radiation through the coherent hard X-ray (CHX) scattering beamline followed by a coherent-mode decomposition. GPU acceleration is added for several key functions of SRW used in propagation from sample to detector, further improving the speed of the calculations. The accuracy of this simulation is benchmarked by comparison with experimental data.

A distributed data processing scheme based on Hadoop for synchrotron radiation experiments

With the development of synchrotron radiation sources and high-frame-rate detectors, the amount of experimental data collected at synchrotron radiation beamlines has increased exponentially. As a result, data processing for synchrotron radiation experiments has entered the era of big data. It is becoming increasingly important for beamlines to have the capability to process large-scale data in parallel to keep up with the rapid growth of data. Currently, there is no set of data processing solutions based on the big data technology framework for beamlines. Apache Hadoop is a widely used distributed system architecture for solving the problem of massive data storage and computation. This paper presents a set of distributed data processing schemes for beamlines with experimental data using Hadoop. The Hadoop Distributed File System is utilized as the distributed file storage system, and Hadoop YARN serves as the resource scheduler for the distributed computing cluster. A distributed data processing pipeline that can carry out massively parallel computation is designed and developed using Hadoop Spark. The entire data processing platform adopts a distributed microservice architecture, which makes the system easy to expand, reduces module coupling and improves reliability.

Synchrotron X-ray Studies of the Structural and Functional Hierarchies in Mineralised Human Dental Enamel: A State-of-the-Art Review

Hard dental tissues possess a complex hierarchical structure that is particularly evident in enamel, the most mineralised substance in the human body. Its complex and interlinked organisation at the Ångstrom (crystal lattice), nano-, micro-, and macro-scales is the result of evolutionary optimisation for mechanical and functional performance: hardness and stiffness, fracture toughness, thermal, and chemical resistance. Understanding the physical-chemical-structural relationships at each scale requires the application of appropriately sensitive and resolving probes. Synchrotron X-ray techniques offer the possibility to progress significantly beyond the capabilities of conventional laboratory instruments, i.e., X-ray diffractometers, and electron and atomic force microscopes. The last few decades have witnessed the accumulation of results obtained from X-ray scattering (diffraction), spectroscopy (including polarisation analysis), and imaging (including ptychography and tomography). The current article presents a multi-disciplinary review of nearly 40 years of discoveries and advancements, primarily pertaining to the study of enamel and its demineralisation (caries), but also linked to the investigations of other mineralised tissues such as dentine, bone, etc. The modelling approaches informed by these observations are also overviewed. The strategic aim of the present review was to identify and evaluate prospective avenues for analysing dental tissues and developing treatments and prophylaxis for improved dental health.

Using In-Situ Laboratory and Synchrotron-Based X-ray Diffraction for Lithium-Ion Batteries Characterization: A Review on Recent Developments

Renewable technologies, and in particular the electric vehicle revolution, have generated tremendous pressure for the improvement of lithium ion battery performance. To meet the increasingly high market demand, challenges include improving the energy density, extending cycle life and enhancing safety. In order to address these issues, a deep understanding of both the physical and chemical changes of battery materials under working conditions is crucial for linking degradation processes to their origins in material properties and their electrochemical signatures. In situ and operando synchrotron-based X-ray techniques provide powerful tools for battery materials research, allowing a deep understanding of structural evolution, redox processes and transport properties during cycling. In this review, in situ synchrotron-based X-ray diffraction methods are discussed in detail with an emphasis on recent advancements in improving the spatial and temporal resolution. The experimental approaches reviewed here include cell designs and materials, as well as beamline experimental setup details. Finally, future challenges and opportunities for battery technologies are discussed.