[17p-D704-1~16] 10.1 Emerging materials in spintronics and magnetics (including fabrication and characterization methodologies)

▼ [17p-D704-2] Accelerating data-driven exploration of magnetocaloric materials by utilizing robotics

〇(M2)WeiSheng Wang^1,2, Kensei Terashima¹, Pedro Baptista de Castro^1,2, Yoshihiko Takano^1,2 (1.NIMS, 2.Univ. of Tsukuba)

Keywords:Automatic synthesis, magnetocaloric

Currently, our research target is magnetocaloric materials, which have the potential to be used for environmentally friendly cooling techniques. We are using machine learning and robotics to automate the synthesis of these materials. We have developed a machine learning model and software for the automatic characterization of X-ray diffraction data, and are working on constructing an automatic synthesis system using a robotic arm to dose and exchange elements and move them to the arc melting standby place. This will improve efficiency, reliability, and reproducibility in the synthesis of magnetocaloric materials.