![\"Gerd](\"https:\/\/tickle.utk.edu\/mse\/wp-content\/uploads\/sites\/2\/2025\/11\/Accelerated-Discovery-Header.jpg\")
<\/p>\nUT Positioned as Leader in Automated Characterization and Autonomous Processing<\/i><\/p>\n
<\/p>\n
Automated characterization is necessary to close the loop between synthesis and discovery of new materials. Through its award-winning faculty, state-of-the-art facilities, and location, the University of Tennessee is at the forefront of this transformative process.<\/p>\n
UT\u2019s framework serves as a model for how machine learning-driven automated materials discovery and scalable experimentation can shorten the path from concept to deployment, advancing the nation\u2019s competitiveness in\u00a0nuclear, aerospace, and advanced manufacturing technologies.<\/p>\n
UT is one of only three programs in the country that works on automated characterization, alongside Oak Ridge National Laboratory<\/a> (ORNL) and Pacific Northwest National Laboratory<\/a> (PNNL). The practice accelerates the materials discovery and development process, which can be time consuming and expensive, by using automated hardware that can execute experiments, collect and analyze data, and interpret results.<\/p>\n \u201cThese capabilities position UT as a leader in translating fundamental materials innovation into scalable, real-world applications,\u201d said Mohsen Asle Zaeem<\/a>, the department head of the Department of Materials Science and Engineering (MSE). \u201cThe integration of cloud-enabled microscopy, automated synthesis, and high-performance computing directly supports the development of next-generation materials for\u00a0nuclear energy systems,\u00a0aerospace structures and systems, and\u00a0national defense.\u201d<\/p>\n As one of the first institutions in the US to work on high-throughput automated synthesis and characterization, UT is helping advance the capabilities of AI materials discovery while training the next generation of the workforce, scientists, and engineers.<\/p>\n \u201cIt doesn’t matter how much stuff you make if you cannot characterize it,\u201d said MSE Weston Fulton Professor Sergei Kalinin<\/a>. \u201cCharacterization is the missing link from the accelerated material discovery in the future. The unique piece of UT is being the place where the accelerated characterization is being done.\u201d<\/p>\n UT has a long tradition of excellence in the field of materials characterization, spearheaded by faculty members like MSE Professor Gerd Duscher<\/a> and Dayakar Penumadu<\/a>, the Fred N. Peebles Professor and IAMM Chair of Excellence.<\/p>\n Currently, UT is the only academic institution that has built fully cloudified electron and scanning probe microscopy and nanoindentation. These instruments can stream imaging data to the cloud, analyze it, and return control commands back to the instrument. This enables the bridge between the ML-agents and real-world instrumentation, opening the door to the ML algorithms to act on the nanometer and atomic scales.<\/p>\n UT is also home to one of the first automated high throughput synthesis labs in the country, directed by Associate Professor Mahshid Ahmadi<\/a>, and combinatorial research labs, directed by Philip Rack<\/a>, MSE professor, Leonard G. Penland Chair, and Director of the Center for Materials Processing (CMP).<\/p>\nBringing AI to the Labs<\/h2>\n
\n