Tailoring Strain Sensor Performance by Biwetting–Dewetting Assembly

The performance indices of nanomaterial-based strain sensors are typically mutually constrained; however, diverse applications necessitate customizable sensing performance for reliable detection. Programming the performance of strain sensors using simple methods and materials remains a significant challenge. Here, we report a biwetting–dewetting (BWD) assembly method for fabricating programmable strain sensors utilizing silver nanowire (AgNW)-based composites on polydimethylsiloxane (PDMS). The BWD assembly was conducted on a highly heterogeneous PDMS surface achieved by oxidation treatment. Patterned AgNWs can self-assemble on the PDMS via a wetting–dewetting process during spin coating. By leveraging the permeability of the AgNW network, a second ink of adhesive molecules, brittle polymers, MXene, or liquid metal particles can be selectively deposited on the AgNW patterns through the same wetting–dewetting process. The straightforward BWD method provides unparalleled tunability of sensitivity and stretchability, allowing for modulation of sensitivity (gauge factor: 2.3 to 3.1 × 106) by 2 to 6 orders of magnitude within 100% strain. With this customized performance, the AgNW-based sensors demonstrate reliable detection capabilities for sound vibration and various physiological motions. The BWD method introduces an innovative approach to tailoring strain sensor performance and holds potential applicability in assembling other nanomaterials for stretchable electronics.

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Publication Details

Journal
ACS Applied Electronic Materials
Published
2024-10-24
DOI
https://doi.org/10.1021/acsaelm.4c01529
Citations
1
Primary Topic
Advanced Sensor and Energy Harvesting Materials
Type
article
Field-Weighted Citation Impact
0.18

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article

Tailoring Strain Sensor Performance by Biwetting–Dewetting Assembly

Haichuan Li, Haibo Zhou, Gui‐Shi Liu, LI Pei-jin et al.
1 citations
ACS Applied Electronic Materials
Advanced Sensor and Energy Harvesting Materials
0.18
article

Tailoring Strain Sensor Performance by Biwetting–Dewetting Assembly

Haichuan Li, Haibo Zhou, Gui‐Shi Liu, LI Pei-jin, Li Wang, Qin Tao, Fanghao Ning
article en
1 citations

Abstract

The performance indices of nanomaterial-based strain sensors are typically mutually constrained; however, diverse applications necessitate customizable sensing performance for reliable detection. Programming the performance of strain sensors using simple methods and materials remains a significant challenge. Here, we report a biwetting–dewetting (BWD) assembly method for fabricating programmable strain sensors utilizing silver nanowire (AgNW)-based composites on polydimethylsiloxane (PDMS). The BWD assembly was conducted on a highly heterogeneous PDMS surface achieved by oxidation treatment. Patterned AgNWs can self-assemble on the PDMS via a wetting–dewetting process during spin coating. By leveraging the permeability of the AgNW network, a second ink of adhesive molecules, brittle polymers, MXene, or liquid metal particles can be selectively deposited on the AgNW patterns through the same wetting–dewetting process. The straightforward BWD method provides unparalleled tunability of sensitivity and stretchability, allowing for modulation of sensitivity (gauge factor: 2.3 to 3.1 × 106) by 2 to 6 orders of magnitude within 100% strain. With this customized performance, the AgNW-based sensors demonstrate reliable detection capabilities for sound vibration and various physiological motions. The BWD method introduces an innovative approach to tailoring strain sensor performance and holds potential applicability in assembling other nanomaterials for stretchable electronics.

ACS Applied Electronic MaterialsVol. 6(11)
Jinan University (CN), Chongqing Vocational Institute of Engineering (CN)
Chongqing Municipal Education Commission Foundation, National Natural Science Foundation of China, Basic and Applied Basic Research Foundation of Guangdong Province
Openalex Percentile: Top 51%
Advanced Sensor and Energy Harvesting Materials
0.18
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