Multilevel Self-Assembly of Block Copolymers and Polymer Colloids for a Transparent and Sensitive Gas Sensor Platform

The recent emerging significance of the Internet of Things (IoT) demands sensor devices to be integrated with many different functional structures and devices while conserving their original functionalities. To this end, optical transparency and mechanical flexibility of sensor devices are critical...

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Veröffentlicht in:ACS nano 2022-11, Vol.16 (11), p.18767-18776
Hauptverfasser: Yang, Geon Gug, Ko, Jaehyun, Choi, Hee Jae, Kim, Dong-Ha, Han, Kyu Hyo, Kim, Jang Hwan, Kim, Min Hyuk, Park, Chungseong, Jin, Hyeon Min, Kim, Il-Doo, Kim, Sang Ouk
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Sprache:eng
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Zusammenfassung:The recent emerging significance of the Internet of Things (IoT) demands sensor devices to be integrated with many different functional structures and devices while conserving their original functionalities. To this end, optical transparency and mechanical flexibility of sensor devices are critical requirements for optimal integration as well as high sensitivity. In this work, a transparent, flexible, and sensitive gas sensor building platform is introduced by using multilevel self-assembly of block copolymers (BCPs) and polystyrene (PS) colloids. For the demonstration of an H2 gas sensor, a hierarchically porous Pd metal mesh structure is obtained by overlaying the two different patterned template structures with synergistic, distinctive characteristic length scales. The hierarchical Pd mesh shows not only high transparency over 90% but also superior sensing performance in terms of response and recovery time owing to enhanced Pd-to-hydride ratio and short H2 diffusion lengths from the enlarged active surface areas. The hierarchical morphology also endows high mechanical flexibility while securing reliable sensing performance even under severe mechanical deformation cycles. Our scalable self-assembly based multiscale nanopatterning offers an intriguing generalized platform for many different multifunctional devices requiring hidden in situ monitoring of environmental signals.
ISSN:1936-0851
1936-086X
DOI:10.1021/acsnano.2c07499