Machine learning-driven optimization of the output force in photo-actuated organic crystals
We employed two types of machine learning for molecular design and experimental optimization to efficiently maximize the blocking force.
Authors
- Toru Asahi (ORCID: https://orcid.org/0000-0003-4925-8259)
- Takuya Taniguchi (ORCID: https://orcid.org/0000-0002-7885-2962)
- Kazuki Ishizaki (ORCID: https://orcid.org/0000-0002-5851-769X)
Institutions
- Waseda University (JP)
Publication Details
- Journal
- Digital Discovery
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1039/d4dd00380b
- Primary Topic
- Machine Learning in Materials Science
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Yashima Environment Technology Foundation
- Waseda University
- Japan Society for the Promotion of Science
- ACT-X