Construction of Quasi-Ordered Metal-Organic Frameworks Superstructures via Colloidal Assembly of Anisotropic Particles for Selective Organic Vapor Sensing

Nanomaterials (Basel). 2023 Oct 9;13(19):2733. doi: 10.3390/nano13192733.

Abstract

Colloidal assembly of anisotropic particles holds great promise for achieving diverse packing geometries and unique photonic properties. One intriguing candidate for anisotropic self-assembly is colloidal metal-organic frameworks (MOFs), which possess remarkable characteristics including substantial surface areas, tunable chemical properties, a wide range of structural variations, and diverse polyhedral shapes. In this study, the colloidal assembly of nearly spherical and polyhedral MOFs particles to form quasi-ordered photonic superstructures was investigated. Specifically, monodisperse near-spherical ZIF-8 (NSZIF-8) and rhombic dodecahedron ZIF-8 (RDZIF-8) colloidal nanoparticles were synthesized as the fundamental building blocks. These nanoparticles are employed to construct MOFs-based self-assembled superstructures that exhibit thin-film interference optical properties. Importantly, these superstructures demonstrate exceptional responsiveness to gaseous homologues and isomers with approximate refractive indices. The dynamic reflection spectral patterns exhibited by these superstructures provide valuable insights into the diffusion rates and surface tension characteristics of the target solvents. These findings underscore the potential of MOFs-based superstructure thin films to discriminate between physiochemically similar solvents, opening new avenues for applications in various fields.

Keywords: colloidal assembly; metal organic frameworks; polyhedral nanoparticles; vapor sensors.

Grants and funding

This research was funded by the National Natural Science Foundation of China (21971129, 21961022, and 21661023), the Inner Mongolia Autonomous Region 2022 Leading Talent Team of Science and Technology (2022LJRC0008), the Natural Science Foundation of Inner Mongolia Autonomous Region of China (2022MS02014 and 2021BS02007), the Program for Innovative Research Team in Universities of Inner Mongolia Autonomous Region (NJYT23031), the 111 Project (D20033), the Program of Higher-Level Talents of IMU (21300-5215101), the “Grassland Leading Talent” Program of Inner Mongolia, the “Grassland-Talent” Innovation Team of Inner Mongolia, the “Science and Technology for a Better Development of Inner Mongolia” Program (2020XM03), and the Science and Technology Project of Ordos (2021 ZDI 11-14), National Natural Science Foundation of China, NSFC (Grant No. 22002051).