Presentation Information
[8a-PB1-8]Machine Learning-Based Prediction of Phase Transition Temperaturesin Thermoresponsive Polymer Solutions
〇Hiroaki Yamamoto1, Junpei Sakurai1,2, Seiichi Hata1, Tiemi Oka1 (1.Nagoya Univ., 2.Sojo Univ.)
Keywords:
phase transition temperature,thermoresponsive polymer,machine Learning
Thermoresponsive polymers are materials that undergo phase transitions between hydrophilic and hydrophobic states in response to temperature changes and are expected to be applied in fields such as drug delivery systems. For practical applications, it is necessary to design polymers with phase transition temperatures tailored to specific purposes. However, conventional development requires repeated polymer synthesis and evaluation, which is time-consuming and labor-intensive. Therefore, this study aims to construct a machine learning model capable of predicting the phase transition temperature from polymer preparation conditions.