CopDDB: a descriptor database for copolymers and its applications to machine learning

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Digital Discovery, 2025, 4, 195
DOI: 10.1039/D4DD00266K

A Machine Learning Model for Copolymer Radical Reactivity Ratio Predictions with Frontier-Orbital Insights

Jingdan Chen and Nicholas E. Jackson

Chem. Mater., 2025
DOI: 10.1021/acs.chemmater.5c01608

Automation of polymer pressing by robotic handling with in-process parameter optimization

Yuki Asano, Kei Okada, Shintaro Nakagawa, Naoko Yoshie and Junichiro Shiomi

Robotics and Autonomous Systems, 2025, 185, 104868
DOI: 10.1016/j.robot.2024.104868

Bayesian optimization of radical polymerization reactions in a flow synthesis system

Shogo Takasuka, Sho Ito, Shunto Oikawa, Yosuke Harashima, Tomoaki Takayama, Aniruddha Nag, Araki Wakiuchi, Tsuyoshi Ando, Tetsunori Sugawara, Miho Hatanaka, Tomoyuki Miyao, Takamitsu Matsubara, Yu-Ya Ohnishi, Hiroharu Ajiro and Mikiya Fujii

Science and Technology of Advanced Materials: Methods, 2024, 4
DOI: 10.1080/27660400.2024.2425178

Insights into the Luminescence Quantum Yields of Cyclometalated Iridium(III) Complexes: A Density Functional Theory and Machine Learning Approach

Miho Hatanaka, Hiromoto Kato, Minami Sakai, Kosuke Kariya, Shunsuke Nakatani, Takayoshi Yoshimura and Taichi Inagaki

J. Phys. Chem. A, 2023, 127, 7630
DOI: 10.1021/acs.jpca.3c02179

Multi-objective Bayesian Optimization for Experimental Design in Copolymerization and Revealing Chemical Mechanism of Pareto Fronts

Hiromu Yamada, Shogo Takasuka, Shunto Oikawa, Yosuke Harashima, Tomoaki Takayama, Aniruddha Nag, Araki Wakiuchi, Tsuyoshi Ando, Tetsunori Sugawara, Miho Hatanaka, Tomoyuki Miyao, Takamitsu Matsubara, Yu-ya Ohnishi, Hiroharu Ajiro and Mikiya Fujii

ACS Appl. Eng. Mater., 2025, 3, 2402
DOI: 10.1021/acsaenm.5c00309