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A semi-automated material exploration scheme to predict the solubilities of tetraphenylporphyrin derivatives
| Title: | A semi-automated material exploration scheme to predict the solubilities of tetraphenylporphyrin derivatives |
| Authors: | Shirasawa, Raku Browse this author | | Takemura, Ichiro Browse this author | | Hattori, Shinnosuke Browse this author | | Nagata, Yuuya Browse this author →KAKEN DB |
| Issue Date: | 22-Nov-2022 |
| Publisher: | Nature Portfolio |
| Journal Title: | Communications Chemistry |
| Volume: | 5 |
| Issue: | 1 |
| Start Page: | 158 |
| Publisher DOI: | 10.1038/s42004-022-00770-9 |
| Abstract: | Acceleration of material discovery has been tackled by informatics and laboratory automation. Here we show a semi-automated material exploration scheme to modelize the solubility of tetraphenylporphyrin derivatives. The scheme involved the following steps: definition of a practical chemical search space, prioritization of molecules in the space using an extended algorithm for submodular function maximization without requiring biased variable selection or pre-existing data, synthesis & automated measurement, and machine-learning model estimation. The optimal evaluation order selected using the algorithm covered several similar molecules (32% of all targeted molecules, whereas that obtained by random sampling and uncertainty sampling was similar to 7% and similar to 4%, respectively) with a small number of evaluations (10 molecules: 0.13% of all targeted molecules). The derived binary classification models predicted 'good solvents' with an accuracy >0.8. Overall, we confirmed the effectivity of the proposed semi-automated scheme in early-stage material search projects for accelerating a wider range of material research. |
| Type: | article |
| URI: | http://hdl.handle.net/2115/87534 |
| Appears in Collections: | 化学反応創成研究拠点：ICReDD (Institute for Chemical Reaction Design and Discovery : ICReDD) > 雑誌発表論文等 (Peer-reviewed Journal Articles, etc)
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