Towards scanning nanostructure X-ray microscopy.
Anton KovyakhSoham BanerjeeChia Hao LiuChristopher J WrightYuguang C LiThomas E MalloukRobert Feidenhans'lSimon J L BillingePublished in: Journal of applied crystallography (2023)
This article demonstrates spatial mapping of the local and nanoscale structure of thin film objects using spatially resolved pair distribution function (PDF) analysis of synchrotron X-ray diffraction data. This is exemplified in a lab-on-chip combinatorial array of sample spots containing catalytically interesting nanoparticles deposited from liquid precursors using an ink-jet liquid-handling system. A software implementation is presented of the whole protocol, including an approach for automated data acquisition and analysis using the atomic PDF method. The protocol software can handle semi-automated data reduction, normalization and modeling, with user-defined recipes generating a comprehensive collection of metadata and analysis results. By slicing the collection using included functions, it is possible to build images of different contrast features chosen by the user, giving insights into different aspects of the local structure.
Keyphrases
- high resolution
- high throughput
- electron microscopy
- deep learning
- electronic health record
- big data
- randomized controlled trial
- data analysis
- machine learning
- healthcare
- ionic liquid
- primary care
- magnetic resonance
- optical coherence tomography
- artificial intelligence
- dual energy
- magnetic resonance imaging
- high frequency
- quality improvement
- circulating tumor cells
- convolutional neural network
- single molecule
- single cell
- computed tomography
- crystal structure