Level of automation in experiments display enourmous increase in recent decades, where progress of diffraction experiments (either in the lab or at large scale facilities) is very remarkable. Relevance for automation in diffraction is driven by a multitude of reasons, ranging from improving efficiency in data collection and analysis, mail in and remote experiments to enabling more advanced and complex studies. In the frame of the Workshop different aspects of automated diffraction experiments applying either neutron scattering, lab X-rays and/or synchrotron radiation will be discussed, namely
Precise and Reproducible Data Collection: Automated systems, including robotic sample changers and motorized goniometers.
High-Speed Data Acquisition: modern diffraction experiments often involve scanning through a range of angles or conditions to collect diffraction patterns. Automation allows for rapid data acquisition, enabling researchers to study dynamic processes, phase transitions, or time-sensitive reactions more effectively.
Sample Screening and Characterization: In materials science, where researchers may have to analyze a large number of samples, automation facilitates high-throughput screening. Automated sample loaders can handle multiple samples, allowing for the efficient characterization of various materials within a shorter timeframe.
Real-Time Analysis and Feedback: Automated data analysis algorithms can process X-ray diffraction patterns as they are collected. Real-time analysis provides immediate feedback, allowing researchers to adjust experimental parameters on the fly and optimize the data collection process for better results.
Advanced Scanning Techniques: Automation enables the execution of complex scanning protocols, such as grazing incidence diffraction, computed tomorgraphy and\or small-angle scattering etc.
Remote Operation and Collaborative Control: Automation allows diffraction experiments to be conducted remotely. Researchers can control experiments from different locations, which is especially beneficial for collaborative research involving experts from diverse geographic locations.
In Situ and Operando Studies: Automation facilitates in situ and operando diffraction experiments, where materials are analyzed under specific environmental conditions or during chemical reactions. The ability to automate such experiments offers insights into the structural changes as they occur, shedding, for example, light on reaction kinetics and mechanisms.
Crystallography and Phase Analysis: Automated systems can quickly analyze diffraction patterns to determine crystal structures and identify phases present in a sample. This capability is valuable in crystallography, materials characterization, and the study of phase transitions.
Data Integration and Visualization: Automation, along with computerized data processing, allows for the integration and visualization of diffraction data with other analytical techniques, such as spectroscopy or imaging. This multimodal approach provides a comprehensive understanding of the material's properties and structure.
Automation plays a significant role in diffraction, i.e. it is relevant because it expedites data collection, improves data quality, enables advanced scanning techniques, and enhances the capability for in situ and operando studies. It empowers researchers to efficiently study and analyze materials, understand their atomic and molecular structures, and make significant advancements in various scientific and industrial fields.
