Issue 6, 2017

Efficient and selective separation of aqueous sulfate through recognition and precipitation

Abstract

An effective and quick approach to selectively separate sulfate anions from ethanol solution or water/EtOH mixture (1 : 1, v/v) based on the precipitation of the neutral sulfate complex, without the slow crystallization process and by utilizing a positive-charged and low-solubility receptor, is illustrated in this paper. The cationic receptor [HL1]+ with the tris(aminomethyl)ethane platform appended with three pyrrolic arms is capable of selectively separating HSO4 or H2PO4 anions in the form of precipitates from EtOH. The mono-protonated tetrapodal receptor [HL2]+, based upon a cyclic C4N2 six-member chair-form platform equipped with four pyrrolic moieties, was constructed in situ through anion-templated chemical synthesis from L1 and pyrrole-2-carboxaldehyde. This receptor shows the capability of selectively precipitating sulfate anions in EtOH or ethanol/water solution. A minor structural modification from L1 to L2 through chemical synthesis in situ leads to an increase of selectivity for sulfate binding and precipitation. The solid-state crystal structure of the precipitates [HL2]2[SO4] after recrystallization shows the encapsulation of a single sulfate within a cavity embraced by two receptors, thereby forming a supramolecular capsule. This tetrapodal receptor exhibits high affinity for sulfate anions as also revealed by a chloroform–water extraction experiment, and can be recycled after NaOH(aq) treatment for continuous usage.

Graphical abstract: Efficient and selective separation of aqueous sulfate through recognition and precipitation

Supplementary files

Article information

Article type
Paper
Submitted
29 Nov 2016
Accepted
27 Jan 2017
First published
30 Jan 2017

New J. Chem., 2017,41, 2249-2254

Efficient and selective separation of aqueous sulfate through recognition and precipitation

Y. Ke, W. Chou, Y. Chiang, C. Hsieh and Y. Horng, New J. Chem., 2017, 41, 2249 DOI: 10.1039/C6NJ03710K

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