What is correlative microscopy – and how do you use it correctly?
In the world of materials science and materials engineering, the microstructure of a material plays a central role. It not only stores the manufacturing history, but also determines the material’s performance properties. Microstructural analysis is therefore one of the fundamental tasks in this discipline. While quality assurance checks whether the microstructure complies with standards and customer specifications, research and development investigates how microstructural characteristics correlate with process parameters and properties. The aim is to optimize the processes and further develop the materials.
With the constant further development of our materials, driven by requirements such as increased strength, sustainability or cost-effectiveness, the microstructure is also becoming increasingly complex. This presents us with the challenge that a single characterization method is often no longer sufficient to fully capture the complexity of the microstructure. The solution lies in correlative microscopy – a method that combines several analysis techniques to obtain a more comprehensive picture. This approach makes it possible to combine the advantages of the different methods, compensate for their disadvantages and bring together information from different sources and on different length scales.
There are virtually no limits to creativity when it comes to combining different methods. In our investigations of complex metallic materials, we often rely on a combination of light microscopy (LM), scanning electron microscopy (SEM) and electron backscatter diffraction (EBSD). The crystallographic data and the parameters derived from the EBSD measurement provide an ideal complement to the visual information obtained by LM and SEM.
For particularly high-resolution analyses, methods such as transmission electron microscopy or atom probe tomography can also be integrated into a correlative characterization. These can also be combined with chemical information, e.g. from EDX or microprobe measurements, and mechanical characterizations such as microhardness measurements or nanoindentation.
The key to success lies in the ability to process multimodal data and carry out so-called image registration for quantitative evaluations. As the physical principles of image generation can vary greatly between the different methods, images of the same sample site are rarely congruent. This is where special algorithms for image registration are used to precisely superimpose the images from the different methods. Without this technique, only qualitative statements would be possible.
The aim of correlative characterization should always be to gain new insights from the complex and high-resolution methods, which can then be transferred to simpler and faster methods. One example from our practice is the development of new AI models for microstructural analysis, in which we use additional information from SEM and EBSD to enable series application of the AI model based on simple LM images.
In this blog series on correlative microscopy, we will regularly present application examples and show you the insights we gain from them and how the methods correlate with each other. We will start with an illustrative example, a combination of EBSD and hardness measurement on a 3D-printed nickel-based superalloy. This shows that the hardness peaks (red areas in the heat map) clearly correlate with the fine-grained microstructure areas visible in the EBSD scan – a textbook example of the fact that fine grains mean higher hardness.