Computational Discovery of Hydrogen Bond Design Rules for Electrochemical Ion Separation
Name
GaniIoannidisKulik2016.pdf
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Author(s)
Gani, Terry Zhi Hao
Ioannidis, Efthymios Ioannis
Kulik, Heather Janine
Date Issued
September 2016
Journal
Chemistry of Materials
Publisher
American Chemical Society (ACS)
Citation
Gani, Terry Z. H. et al. “Computational Discovery of Hydrogen Bond Design Rules for Electrochemical Ion Separation.” Chemistry of Materials 28, 17 (September 2016): 6207–6218 © 2016 American Chemical Society
Version
Author's final manuscript
Abstract
Selective ion separation is a major challenge with far-ranging impact from water desalination to product separation in catalysis. Recently introduced ferrocene (Fc)/ferrocenium (Fc⁺) polymer electrode materials have been demonstrated experimentally and theoretically to selectively bind carboxylates over perchlorate through weak C–H···O hydrogen bond (HB) interactions that favor carboxylates, despite the comparable size and charge of the two species. However, practical application of this technology in aqueous environments requires further selectivity enhancement. Using a first-principles discovery approach, we investigate the effect of Fc/Fc⁺ functional groups (FGs) on the selectivity and reversibility of formate–Fc⁺ adsorption with respect to perchlorate in aqueous solution. Our wide design space of 44 FGs enables identification of FGs with higher selectivity and rationalization of trends through electronic energy decomposition analysis or geometric hydrogen bonding analysis. Overall, we observe weaker, longer HBs for perchlorate as compared to formate with Fc⁺. We further identify Fc⁺ functionalizations that simultaneously increase selectivity for formate in aqueous environments but permit rapid release from neutral Fc. We introduce the materiaphore, a 3D abstraction of these design rules, to help guide next-generation material optimization for selective ion sorption. This approach is expected to have broad relevance in computational discovery for molecular recognition, sensing, separations, and catalysis.
MIT Department
Massachusetts Institute of Technology. Department of Chemical Engineering
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DOI of Published Version
https://doi.org/10.1021/acs.chemmater.6b02378
