| Author(s) |
Nathan S. Johnson, Hrishikesh Bale, Steve Kelly, Naomi Kotwal, Roland Salzer, Herminso Villaraga-Gomez, Daniel Plecner, Richard Ankerhold, William Harris, Heiko Stegmann |
| Abstract Scope |
Automation is transforming materials characterization from a collection of instrument-specific tools into an integrated ecosystem of robotic interfaces, machine-learning analysis, AI-assisted planning, and emerging agentic workflow control. These capabilities are enabling a shift toward self-driving characterization laboratories for materials discovery, optimization, scale-up, and qualification. This talk surveys automation efforts across X-ray microscopy, electron microscopy, FIB-SEM, EBSD, EDS, and metrology platforms, with applications in metallurgy, energy materials, infrastructure, and advanced manufacturing. Drawing on lessons from diverse instruments, user environments, and deployment settings, we will examine practical opportunities and barriers to automated characterization in both industrial manufacturing and research laboratories. Finally, we will discuss how next-generation characterization suites can integrate instrumentation, data infrastructure, AI, and human expertise to reduce time-to-insight, de-risk scale-up, and accelerate the translation of materials research into commercial products. |