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

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2021

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Lahnsteiner, Marianne
Caldera, Michael
Moura, Hipassia M.
Roeser, Jérôme
Konegger, Thomas
Thomas, Arne
Menche, Jörg

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Journal of Materials Chemistry A. Royal Society of Chemistry (RSC). 2021, 9(35), pp. 19754-19769. ISSN 2050-7488. eISSN 2050-7496. Available under: doi: 10.1039/d1ta01253c

Zusammenfassung

We report on the hydrothermal polymerization (HTP) of polyimide (PI) networks using the medium H2O and the comonomers 1,3,5-tris(4-aminophenyl)benzene (TAPB) and pyromellitic acid (PMA). Full condensation is obtained at minimal reaction times of only 2 h at 200 °C. The PI networks are obtained as monoliths and feature thermal stabilities of >500 °C, and in several cases even up to 595 °C. The monoliths are built up by networks of densely packed, near-monodisperse spherical particles and annealed microfibers, and show three types of porosity: (i) intrinsic inter-segment ultramicroporosity (<0.8 nm) of the PI networks composing the particles (∼3–5 μm), (ii) interstitial voids between the particles (0.1–2 μm), and (iii) monolith cell porosity (∽10–100 μm), as studied via low pressure gas physisorption and Hg intrusion porosimetry analyses. This unique hierarchical porosity generates an outstandingly high specific pore volume of 7250 mm3 g−1. A large-scale micromorphological study screening the reaction parameters time, temperature, and the absence/presence of the additive acetic acid was performed. Through expert interpretation of hundreds of scanning electron microscopy (SEM) images of the products of these experiments, we devise a hypothesis for morphology formation and evolution: a monomer salt is initially formed and subsequently transformed to overall eight different fiber, pearl chain, and spherical morphologies, composed of PI and, at long reaction times (>48 h), also PI/SiO2 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.

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ISO 690LAHNSTEINER, Marianne, Michael CALDERA, Hipassia M. MOURA, Daniel Alonso CERRÓN INFANTES, Jérôme ROESER, Thomas KONEGGER, Arne THOMAS, Jörg MENCHE, Miriam M. UNTERLASS, 2021. Hydrothermal polymerization of porous aromatic polyimide networks and machine learning-assisted computational morphology evolution interpretation. In: Journal of Materials Chemistry A. Royal Society of Chemistry (RSC). 2021, 9(35), pp. 19754-19769. ISSN 2050-7488. eISSN 2050-7496. Available under: doi: 10.1039/d1ta01253c
BibTex
@article{Lahnsteiner2021-09-14Hydro-55093,
  year={2021},
  doi={10.1039/d1ta01253c},
  title={Hydrothermal polymerization of porous aromatic polyimide networks and machine learning-assisted computational morphology evolution interpretation},
  number={35},
  volume={9},
  issn={2050-7488},
  journal={Journal of Materials Chemistry A},
  pages={19754--19769},
  author={Lahnsteiner, Marianne and Caldera, Michael and Moura, Hipassia M. and Cerrón Infantes, Daniel Alonso and Roeser, Jérôme and Konegger, Thomas and Thomas, Arne and Menche, Jörg and Unterlass, Miriam M.}
}
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