ArticleNano convergence2022
Ink-lithographic fabrication of silver-nanocrystal-based multiaxial strain gauge sensors through the coffee-ring effect for voice recognition applications.
Article in Nano convergence, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Advancing Soft Mechanosensors by Colloidal Design.Advanced materials (Deerfield Beach, Fla.) · 2026Article
- Machine learning-assisted wearable sensing systems for speech recognition and interaction.Nature communications · 2025Article
- Freestanding VONano convergence · 2025Article
- Ultrathin, High-Aspect-Ratio Bismuth Sulfohalide Nanowire Bundles for Solution-Processed Flexible Photodetectors.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024Article
- Vibration Sensors on Flexible Substrates Based on Nanoparticle Films Grown by Physical Vapor Deposition.Materials (Basel, Switzerland) · 2024Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
Human voice recognition techniques have remarkable potential for clinical applications because information from acoustic signals can reflect human body conditions. This paper reports the fabrication of Ag nanocrystal (NC)-based multiaxial wearable strain gauge sensors by ink-lithography for voice recognition systems. Benefiting from the one-step-device-fabrication strategy of ink-lithography, which can yield Ag NC patterns with specific dimensions and endow physical properties, the Ag NC-based multiaxial strain sensors can be fabricated on an ultrathin substrate (~ 6 μm). Additionally, the coffee-ring effect can be induced onto the Ag NC patterns to realize high sensitivity and angle dependence (gauge factors [Formula: see text] = 11.7 ± 1.2 and [Formula: see text] = 105.5 ± 20.1); moreover, the voice onset time for voice recognition can be detected by the sensors. These features assist in distinguishing between voiced and voiceless plosive contrasts via measurements of contact-based voice onset time differences and can act as a cornerstone for further advancements in wearable sensors as well as voice recognition and analysis.
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Registered trials
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