Litcius/Paper detail

Hydrothermal polymerization of porous aromatic polyimide networks and machine learning-assisted computational morphology evolution interpretation

Marianne Lahnsteiner, Michael Caldera, Hipassia M. Moura, D. Alonso Cerrón-Infantes, Jérôme Roeser, Thomas Konegger, Arne Thomas, Jörg Menche, Miriam M. Unterlass

2021Journal of Materials Chemistry A18 citationsDOIOpen Access PDF

Abstract

hybrids that form through reaction with the reaction vessel. Moreover, we have developed a computational image analysis pipeline that deciphers the complex morphologies of these SEM images automatically and also allows for formulating a hypothesis of morphology development in HTP that is in good agreement with the manual morphology analysis. Finally, we upscaled the HTP of PI(TAPB-PMA) and processed the resulting powder into dense cylindrical specimen by green solvent-free warm-pressing, showing that one can follow the full route from the synthesis of these PI networks to a final material without employing harmful solvents.

Topics & Concepts

Materials sciencePolymerizationPorosityChemical engineeringPorosimetryNanoporousDispersityPolymer chemistryComposite materialPolymerNanotechnologyPorous mediumEngineeringCovalent Organic Framework ApplicationsSynthesis and properties of polymersPolymer composites and self-healing