File:Fig1 Ishizuki SciTechAdvMatMeth2023 3-1.jpeg

Figure 1. The vision of the materials explorer. The exploration involves an autonomous experimental system, materials informatics, and human researchers. The heart of the materials explorer is an autonomous experimental system based on machine learning and robots (green, orange, and blue). This system is imbued with the skills of experts and generates large amounts of experimental data that could not have been generated by human researchers (data-production factory). The data generated by the autonomous experimental system is then processed by machine learning and simulations to predict new materials (materials informatics). In addition, the system organizes the data and generates "materials maps" and models, facilitating knowledge creation by providing researchers a sharable big-picture view of unexpected materials, thereby accelerating materials development.

Ishizuki, N.; Shimizu, R.; Hitosugi, T. (2023). "Autonomous experimental systems in materials science". Science and Technology of Advanced Materials: Methods 3 (1): 2197519. doi:10.1080/27660400.2023.2197519. 

2023

Ishizuki, N.; Shimizu, R.; Hitosugi, T.

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