Machine-learning-assisted discovery of polymers with high thermal conductivity
Scientists demonstrate the successful discovery of new polymers with high thermal conductivity, inspired by machine-learning-assisted polymer chemistry.
This discovery was made by the interplay between machine intelligence trained on a substantially limited amount of polymeric properties data, expertise from laboratory synthesis and advanced technologies for thermophysical property measurements.
Using a molecular design algorithm trained to recognise quantitative structure—property relationships with respect to thermal conductivity and other targeted polymeric properties, they identified thousands of promising hypothetical polymers.
Synthetised polymers with high thermal conductivities
From these candidates, three were selected for monomer synthesis and polymerisation because of their synthetic accessibility and their potential for ease of processing in further applications.
The synthesised polymers reached thermal conductivities of 0.18–0.41 W/mK, which are comparable to those of state-of-the-art polymers in non-composite thermo-plastics.
The study is published in: npj Computational Materials, Volume 5, Article number: 66 (2019).
