Measuring microstructure: Researcher aims to take the guesswork out of materials characterization

In science, technology, engineering, and math (STEM) fields, standardization is critical. Safety practices, research processes, experimental conditions, and overall expectations in the field must be standardized—and that is just the short list. Not only does standardization ensure the quality and authenticity of research, it also allows for reproducibility of research, which is important for the development of new technology. 

Even with all of these research standards in place, the field of materials characterization does not yet have a standard way to quantify and validate microstructure images of materials. However, with the recent support of a $3 million dollar grant from the Department of Defense (DoD), Professor of Materials Science and Engineering Marc De Graef plans to create an open source computational framework to remedy this problem.

A standard framework for quantifying microstructures will make it easier and faster for researchers to design new materials which can be used in a variety of different industry applications, including improved turbines for jet propulsion and energy generation, stronger aviation alloys, advanced steels for ship hulls, and multi-functional materials. 

"I want to take the guesswork out of the current characterization process," explains De Graef. "This framework will create a far more structured way to measure and validate microstructure images."

De Graef will begin work on this project in 2016 as part of the DoD's National Security Science and Engineering Faculty Fellowship (NSSEFF). He is one of fifteen distinguished scientists and engineers selected for this fellowship, which is designed to support long-term fundamental research that has the potential to lead to important technology developments. 

In addition to easily quantifying microstructure images, the framework will also act as a predictive model. "The framework will be a game changer for the materials community because it will allow researchers to predict the outcome of characterization experiments," says De Graef. These predictions, called quantitative forward models, will allow researchers to validate microstructures that they have reconstructed from experimental data.

This new framework will help in the design of new materials, but De Graef recognizes that education is another important component needed to accelerate the design of novel materials. As part of De Graef's NSSEFF program, he plans to create a new Integrated Computational Materials Science and Engineering Master of Science program at Carnegie Mellon University.

"My goal is not only to perform research, but to train the next generation of students who will eventually be working in labs that will use these types of computational tools."

For more information, please read the DoD's NSSEFF 2016 announcement.

Provided by Carnegie Mellon University Electrical and Computer Engineering