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Novel Integration of Conductive-Ink Circuitry with a Paper-Based Microfluidic Battery as an All-Printed Sensing Platform

Abstract

dc:description.abstract

<p>The addition of powered components for active assays into paper-based analytical devices opens new opportunities for medical and environmental analysis in resource-limited applications. Current battery designs within such devices have yet to adopt a ubiquitous circuitry material, necessitating investigation into printed circuitry for scalable platforms. In this study, a microfluidic battery was mated with silver-nanoparticle conductive ink to prototype an all-printed sensing platform. A multi-layer, two-cell device was fabricated, generating 200 μA of direct electrical current at 2.5 V sustained for 16 minutes with a power loss of less than 0.1% through the printed circuitry. Printed circuitry traces exhibited resistivity of 75 to 211 10<sup>-5</sup> Ω m. Resistance of the printed traces increased upwards of 200% depending on fold angle and directionality. X-ray diffraction confirmed the presence of face-centered cubic silver after sintering printed traces for 30 minutes at 150°C in air. A conductivity threshold was mapped and an ink concentration of 0.636 μL mm<sup>-3</sup> was identified as the lower limit for optimal electrical performance.</p>

Degree

thesis:*
Name thesis:degree_name
MS in Engineering - Materials Engineering
Discipline thesis:degree_discipline
Materials Engineering
Year dc:date.available
2016

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Kripalani, Rishi A.
Contributors dc:contributor
  • Linda Vanasupa

Subjects

dc:subject × 8

Identifiers

dc:identifier.*
OAI identifier oai:identifier
oai:digitalcommons.calpoly.edu:theses-2887

Chain of custody

source
Harvested from
Cal Poly
Base URL
digitalcommons.calpoly.edu/do/oai/
Last updated
2026-07-24
Source record
OAI-PMH GetRecord
citation

Kripalani, Rishi A.. Novel Integration of Conductive-Ink Circuitry with a Paper-Based Microfluidic Battery as an All-Printed Sensing Platform. 2016. https://digitalcommons.calpoly.edu/theses/1694