Supramolecular Chemistry and Its Applications in Smart Materials
Keywords:
Supramolecular chemistry, smart materials, molecular recognition, non-covalent interactions, self-assembly, functional responsivenessAbstract
Supramolecular chemistry also has become a vital activity in the augmentation of the design and functioning of intelligent materials with a center and emphasis in non-covalent interactions and dynamic assembling points. This was demonstrated where a methodology strategy was used in this study to combine qualitative analysis of molecular recognition processes, in conjunction with quantitative experimental analysis in order to study the synthesis, characterisation limitations and performance of supramolecular systems. Covalent bonds were eliminated in favor of hydrogen bonding, host-guest, metal-ligand coordination, and 1-stacking to combine building blocks. Subsequently, the AFM, SAXS, DLS, UV-Vis and fluorescence spectroscopy, AFM, and SEM techniques were used to carefully analyze them. Thermodynamic analyses revealed both negative Gibbs free energy (3G) values as reliable indicators of spontaneous assembly, and kinetic measurements demonstrated the reversibility and responsiveness of these materials to a variety of environmental controls. Functional characterization indicated a high level of responsiveness in thermal, mechanical and electrical applications reflecting the possibilities of supramolecular systems to be deployed in sensors, responsive coatings, actuators and energy storage applications. The integration of synthesis, characterisation and functional evaluation within a single reproducible workflow (Fig. 1) suggests the effectiveness of supramolecular chemistry to come up with varied, dynamic and sustainable smart materials. Overall, these findings demonstrate that supramolecular chemistry can significantly contribute to the theoretical understanding of non-covalent interactions, as well as provide an effective and highly scalable means of creating smart material systems which are able to adapt dynamically to variability in the external environment.
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