Machine-learning-assisted prediction of the size of microgels prepared by aqueous precipitation polymerization.

The size of soft colloids (microgels) is essential; however, control over their size has typically been established empirically. Herein, we report a linear-regression model that can predict microgel size using a machine learning method, sparse modeling for small data, which enables the determination of the synthesis conditions for target-sized microgels.

Phase-separated structures of tunable thermoresponsive and matrix polymers for large-scale temperature monitoring coatings.

Temperature monitoring is significant and fundamental in the fields of healthcare and medicine. In surgery, ultrasonic cutting devices are used for cutting, coagulation, and hemostasis. However, surgeons are concerned about the collateral thermal damages.