Advances in Multimodal Characterization of Structural Materials

Abstract

The myriad detectors and instruments now available for materials characterization provide researchers with an ever-growing suite of tools to probe material behavior. Progress in the development of instrumentation and workflows that enable the collection, and leverage the potential, of various data modalities have provided novel insights into material behavior. Using data across multiple length scales, or performing complementary analyses of in situ and ex situ data, can help reveal a more complete picture of dynamic processes or material structure. However, the accurate combination, or fusion, of these disparate data modalities presents new challenges. Differences in resolution, as well as the varying length scales at which physical phenomena are exploited to generate these data, necessitate novel approaches to accurately interpret and combine these data. Furthermore, the papers within this special topic focus on the collection and fusion of multimodal data to better understand structural materials. From new frameworks and workflows for data segmentation and analysis, process monitoring, enhancing simulations, or interrogating mechanical response, these papers reveal the potential benefits of utilizing multimodal data.