Chemoresponsive alternating supramolecular copolymers created from heterocomplementary calix[4]pyrroles

The importance of noncovalent interactions in the realm of biological materials continues to inspire efforts to create artificial supramolecular polymeric architectures. These types of self-assembled materials hold great promise as environmentally stimuli-responsive materials because they are capable of adjusting their various structural parameters, such as chain length, architecture, conformation, and dynamics, to new surrounding environments upon exposure to appropriate external stimuli. Nevertheless, in spite of considerable advances in the area of responsive materials, it has proved challenging to create synthetic self-assembled materials that respond to highly disparate analytes and whose environmentally induced changes in structure can be followed directly through both various spectroscopic and X-ray diffraction analyses. Herein, we report a new set of artificial self-assembled materials obtained by simply mixing two appropriately chosen, heterocomplementary macrocyclic receptors, namely a tetrathiafulvalene-functionalized calix[4]pyrrole and a bis(dinitrophenyl)-meso-substituted calix[4] pyrrole. The resulting polymeric materials, stabilized by combination of donor-acceptor and hydrogen bonding interactions, undergo dynamic, reversible dual guest-dependent structural transformations upon exposure to two very different types of external chemical inputs, namely chloride anion and trinitrobenzene. The structure and dynamics of the copolymers and their analyte-dependent responsive behavior was established via single crystal X-ray crystallography, SEM, heterocomplementary isodesmic analysis, 1- and 2D NMR, and dynamic light scattering spectroscopies. Our results demonstrate the benefit of using designed heterocomplementary interactions of two functional macrocyclic receptors to create synthetic, self-assembled materials for the development of "smart" sensory materials that mimic the key biological attributes of multianalyte recognition and substrate-dependent multisignaling