Journal
ADVANCED OPTICAL MATERIALS
Volume 11, Issue 6, Pages -Publisher
WILEY-V C H VERLAG GMBH
DOI: 10.1002/adom.202201911
Keywords
host-guest chemistry; hotspots modulation; molecular cages; network architectures; plasmonic nanoparticles
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Plasmonic networks have gained increasing attention due to their strong plasmon coupling effects and collective optical behavior in hotspot regions. However, engineering network architectures with flexible control over hotspot density and intensity is a challenge. This study presents a bottom-up self-assembly strategy using cage-assisted structures to construct complex plasmonic network architectures with adjustable hotspots. The integration of host-guest chemistry enables selective molecule trapping in hotspots, providing opportunities for diverse plasmon-based applications.
Plasmonic networks attract increasing attention owing to their strong plasmon coupling effects at hotspot regions, where intriguing, collective optical behavior and field enhancement occur. Engineering network architectures with flexible control over density and intensity of hotspots, thus fine-tuning electromagnetic field is the prerequisite for fully exploiting their potential use in diverse plasmon-based applications, but it represents a great challenge. Herein, a cage-assisted bottom-up self-assembly strategy is proposed to construct a series of cage-bridged complex network architectures with a high degree of flexibility in hotspot modulation. Critical parameters associated with plasmonic networks, including interparticle distance, the density and intensity of hotspots, as well as molecule accessibility of hotspot can be simultaneously and flexibly adjusted at will. Importantly, the integration of host-guest chemistry of molecular cages into interparticle regions of networks endows selective molecule trapping capability in hotspots, offering tremendous opportunities for broader plasmon-based applications. The present study not only develops efficient plasmonic networks with enhanced density of hotspots and intense electromagnetic fields, but also provides new avenues for artificially engineering network architectures with advanced functionalities and facilitates further applications in sensing and optoelectronics.
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