guest ::
| Home > Publications database > Accelerating the discovery of alkaline-stable anion exchange membrane materials via computational exploration |
| Home > Publications database > Accelerating the discovery of alkaline-stable anion exchange membrane materials via computational exploration |
| Book/Dissertation / PhD Thesis | FZJ-2026-02072 |
2026
Forschungszentrum Jülich GmbH Zentralbibliothek, Verlag
Jülich
ISBN: 978-3-95806-900-8
This record in other databases:
Please use a persistent id in citations: urn:nbn:de:0001-2607011039153.745865459909 doi:10.34734/FZJ-2026-02072
Abstract: Hydrogen fuel cells and water electrolyzers using anion exchange membranes (AEMs) host an alkaline chemical environment that mitigates the need for rare platinum group metals (PGMs) as electrocatalyst. Despite the extraordinary potential for widespread adoption of these devices, they are held back by challenges associated with the AEM itself. The current generation of AEMs is particularly limited in terms of durability in the caustic conditions they inhabit, as the cationic moieties of the AEMs are vulnerable to the high concentration of hydroxide anions. Designing cationic moieties that are highly stable in alkaline conditions is, therefore, of crucial importance. Promising classes of cationic compounds for the implementation in AEMs are those based on the imidazolium group. Through adjustments of the chemical structure via different substitution schemes, the alkaline stability is highly adjustable. Experimental exploration of the vast chemical space of imidazolium-based compounds is slow due to the high resource demand and an insufficient understanding of the structure-stability relationship. The work described in this thesis has thus been predominantly focused on leveraging computational means to accelerate the discovery of alkaline stable imidazolium-based compounds. As the first step in this undertaking, a reliable computational descriptor for the alkaline stability of a given imidazolium has been identified in the Gibbs free energy change of the C-2 hydroxide attack by comparing the degradation energetics computed through ab initio simulations with experimental stability values reported in literature. Thereafter, the calculation of this descriptor was streamlined and fully automated. Next, the descriptor was applied to an extensive molecular dataset containing 5832 imidazolium-based compounds, which was constructed by systematically adding 18 different substituents to a base imidazolium structure. The dataset contains numerous compounds for which the descriptor computationally predicts an exceptional alkaline stability. The computed values were verified as part of this PhD research program by synthesizing five of the molecules and performing two different degradation tests on each, that showed good agreement with the computational predictions. Among the tested compounds, an especially stable compound was identified that surpasses the stability of comparable penta-substituted imidazoliums by substitution of the C-4 and C-5 sites with a methyl group instead of the commonly employed phenyl substituent. The dataset includes a number of additional compounds with even higher computed alkaline stability. These will be promising candidates for future experimental exploration. Additionally, the dissertation provides further in-depth insights for the design of stable compounds based on new understanding of the structure-stability relationship of imidazoliumbased compounds, that was gained through analysis of the molecular dataset. The design of novel compounds will benefit, in particular, from a quantitative assessment of the influence that a selection of 18 different substituents exerts upon addition to each site of the imidazolium ring. A machine learning model was trained for the expanded computational exploration of imidazolium-based compounds. The model is able to approximate the alkaline stability in under one second on a typical laptop processor. Computational insights were also gained regarding a recently reported azacyclic cationic group, 1,6-diazabicyclo[4.4.4]tetradecan-1,6-ium (in-DBD), which possesses an exceptionally high alkaline stability. Simulations of several degradation pathways were performed, indicating the hydroxide-induced elimination reaction as the most prominent pathway. The impact of small perturbations to the in-DBD structure was investigated to guide the introduction of the cation into a polymer structure without incurring an adverse effect on stability. It was found that the methylation at the β-carbons is especially favorable as it adds protection against the critical elimination degradation reaction. This work has made significant progress in the pursuit of materials for highly durable anion exchange membranes. A particularly stable cationic group could be identified and design aids for further improvements have been developed.
|
The record appears in these collections: |
PDF
Fulltext by OpenAccess repository