Bita Soltan Mohammadlou, Stefano Ippolito, James FitzPatrick, Prastuti Upadhyay, Tim L Burnett, Yury Gogotsi
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Characterization of MXene-Based Materials by X-Ray Computed Tomography.
MXenes are a class of 2D materials that have gained significant attention for their potential applications in energy storage, electromagnetic interference shielding, biomedicine, and (opto)electronics. Despite their broad range of applications, a detailed understanding of the internal architecture of MXene-based materials remains limited due to the lack of effective 3D imaging techniques. This work demonstrates the application of X-ray micro-computed tomography (micro-CT) to investigate various MXene systems, including nanocomposites, coated textiles, and aerogels. Micro-CT enables high-resolution, 3D visualization of the internal microstructure, MXene distribution, infiltration patterns, and defect formations, which significantly influence the material's performance. Moreover, the typical technical challenges and limitations encountered during sample preparation, scanning, and post-processing of micro-CT data are discussed. The information obtained from optical and electron microscopy is also compared with micro-CT, highlighting the unique advantages of micro-CT in providing comprehensive 3D imaging and quantitative data. This study highlights micro-CT as a powerful and nondestructive imaging tool for characterizing MXene-based materials, providing insights into material optimization and guidelines for developing future advanced applications.
Small MethodsMaterials Science-General Materials Science
CiteScore
17.40
自引率
1.60%
发文量
347
期刊介绍:
Small Methods is a multidisciplinary journal that publishes groundbreaking research on methods relevant to nano- and microscale research. It welcomes contributions from the fields of materials science, biomedical science, chemistry, and physics, showcasing the latest advancements in experimental techniques.
With a notable 2022 Impact Factor of 12.4 (Journal Citation Reports, Clarivate Analytics, 2023), Small Methods is recognized for its significant impact on the scientific community.
The online ISSN for Small Methods is 2366-9608.