Difference between revisions of "File:Fig3 Tamura SciTechAdvMatMeth2023 3-1.jpeg"

Figure 3. (Top panels) Examples of the candidates files of the initial stage and that after some experiments. Here, an example for the case that N=9 is shown. (Bottom panels) Examples for the list of descriptors depending on the types of search space. If the continuous parameter space is considered, ${\displaystyle D=\{\mathbf {x} _{i}\}_{i=1,\ldots ,N}}$ is the discretized parameters. When the combination of materials is the search space, the bit strings where the material used is represented by 1 and the material not used is represented by 0 are prepared in ${\displaystyle D=\{\mathbf {x} _{i}\}_{i=1,\ldots ,N}}$. Furthermore, materials descriptors from compositions obtained by such as magpie and fingerprint of molecules obtained by such as RDKit would be used as ${\displaystyle D=\{\mathbf {x} _{i}\}_{i=1,\ldots ,N}}$.

Tamura, R.; Tsuda, K.; Matsuda, S. (2023). "NIMS-OS: An automation software to implement a closed loop between artificial intelligence and robotic experiments in materials science". Science and Technology of Advanced Materials: Methods 3 (1): 2232297. doi:10.1080/27660400.2023.2232297. 

2023

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

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