This article has been reviewed according to Science X's editorial process and policies. Editors have highlighted the following attributes while ensuring the content's credibility: Developing stronger and tougher structural metals such as steel requires exploring an enormous range of processing conditions. Even for the same alloy composition, heat treatment can dramatically change the material's microstructure and mechanical properties.
If there were a way to automate the process, we could pinpoint ideal conditions much more efficiently. However, experiments on bulk metallic materials are difficult to automate because they require handling solid specimens and integrating large, specialized equipment. A research team led by Yulin Xie, Sayaka Sekida and Goro Miyamoto at the Institute for Materials Research (IMR), Tohoku University, and Tadashi Furuhara (formerly at IMR) at the National Institute for Materials Science (NIMS) worked together with TsubameLab to develop an automated experimental system that integrates heat treatment, structural characterization and mechanical testing of bulk metallic materials.
This enables a continuous workflow from heat treatment to structural analysis and mechanical property evaluation without human intervention. The study is published in Science and Technology of Advanced Materials: Methods. Automating experiments on bulk structural metals has been particularly challenging compared with liquids, powders and thin films because solid specimens must be reliably transported, positioned, heated, characterized and mechanically tested.
The researchers overcame these challenges by designing dedicated specimen-handling tools and integrating the individual instruments under unified computer control. The system combines an induction heating furnace, an X-ray diffractometer (XRD) and a micro-impact testing machine using a robotic arm to transfer specimens automatically between each process. Using the newly developed platform, the team demonstrated automated experiments on one- and two-step tempering of a commercial JIS SCM435H low-alloy steel.
Excluding the heat-treatment time itself, the complete sequence of specimen handling, XRD measurement, mechanical testing and specimen recovery can be completed in approximately 800 seconds per sample. The automated system evaluates mechanical properties with accuracy comparable to conventional measurements manually performed by researchers, while conducting the experimental sequence more than 10 times faster. The system simultaneously generates processing, structure and property data.
Such process-structure-property datasets are essential for applying artificial intelligence to materials development. The researchers also implemented an AI optimization tool within the NIMS Orchestration System (NIMO), demonstrating automated optimization of furnace control parameters and establishing the technological basis for future closed-loop materials exploration. In a future autonomous system, AI will analyze the results obtained from each experiment and propose the next heat-treatment conditions to investigate.
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