A synchrotron-based local computed tomography combined with data-constrained modelling approach for quantitative...

Area of Science:

• Materials Science
• Geology
• Physics

Background:

• Characterizing 3D spatial distributions of pores and material compositions presents a significant challenge, especially in heterogeneous materials like coal.
• Conventional methods often lack the necessary resolution to detail compositional variations across multiple length scales or within specific sub-regions.

Purpose of the Study:

• To propose and demonstrate a novel approach for quantitative, high-definition determination of material compositions using X-ray local computed tomography (XCT) combined with data-constrained modeling.
• To significantly improve spatial resolution for revealing finer details within regions of interest in multi-length-scale samples.

Main Methods:

• Utilized X-ray local computed tomography (XCT) for data acquisition.
• Implemented a data-constrained modeling method to enhance image resolution and quantitative analysis.
• Applied and optimized experimental parameters for the chosen methodology.

Main Results:

• Demonstrated the capability to reveal significantly finer details of compositional distributions within a coal sample.
• Achieved a dramatic improvement in spatial resolution compared to conventional techniques.
• Successfully quantified three-dimensional distributions of porosity and mineral compositions.

Conclusions:

• The developed approach provides high-definition, quantitative 3D compositional characterization of materials.
• The enhanced spatial resolution is critical for applications such as coal-bed methane reservoir evaluation and understanding mineral transformations during coal processing.
• The method is versatile and applicable to the 3D compositional characterization of various materials.