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<OAI-PMH xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/ http://www.openarchives.org/OAI/2.0/OAI-PMH.xsd"><responseDate>2026-05-19T01:38:11Z</responseDate><request verb="GetRecord" metadataPrefix="oai_dc">https://keep.lib.asu.edu/oai/request</request><GetRecord><record><header><identifier>oai:keep.lib.asu.edu:node-201604</identifier><datestamp>2025-05-12T19:35:22Z</datestamp><setSpec>oai_pmh:all</setSpec><setSpec>oai_pmh:repo_items</setSpec></header><metadata><oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>201604</dc:identifier>
          <dc:identifier>https://hdl.handle.net/2286/R.2.N.201604</dc:identifier>
                  <dc:rights>http://rightsstatements.org/vocab/InC/1.0/</dc:rights>
          <dc:rights>All Rights Reserved</dc:rights>
                  <dc:date>2025</dc:date>
                  <dc:format>59 pages</dc:format>
                  <dc:type>Masters Thesis</dc:type>
          <dc:type>Academic theses</dc:type>
                  <dc:language>en</dc:language>
                  <dc:contributor>Joseph, Jesly</dc:contributor>
          <dc:contributor>Kozicki, Michael</dc:contributor>
          <dc:contributor>Bailey, Christopher</dc:contributor>
          <dc:contributor>Yan, Feng</dc:contributor>
          <dc:contributor>Arizona State University</dc:contributor>
                  <dc:description>Partial requirement for: M.S., Arizona State University, 2025</dc:description>
          <dc:description>Field of study: Materials Science and Engineering</dc:description>
          <dc:description>The rapid advancement of technological innovation has led to increasingly complex supply chains, making them more vulnerable to threats such as counterfeiting and tampering. This has heightened the demand for robust, unclonable identifiers. Dendritic Identifiers (DIs), formed through Laplacian instabilities such as the Saffman-Taylor effect, exhibit stochastic fractal structures with unpredictable branching and termination, influenced by fluid rheology, system geometry, and environmental conditions.These identifiers are highly adaptable, directly applicable to object surfaces, and inherently unique due to their random growth processes, qualifying them as Physical Unclonable Functions (PUFs). DIs also possess intrinsic data encoding capabilities, making them compatible with computer vision systems like Oriented Fast and Rotated Brief (ORB). 
Coupling DIs with blockchain platforms further enhances supply chain transparency and security.
This study focuses on forming dendritic identifiers using a high-viscosity, shear-thinning fluid on transparent plastic substrates through a Dispense-Compress-Separate (DCS) system. Factors influencing the wavelength between dendritic fingers were systematically analysed. Two predictive models—the Lifted Hele-Shaw Cell (LHSC-Stamping) and Flexographic (RTR-Rolling) models—were compared and validated. The RTR model was refined to improve predictive accuracy by physically justifying adjustments to the gap widening coefficient (κ). The practical applicability of DIs was demonstrated by successfully printing on real-world items (heat spreader and silicon wafer), establishing their potential for secure, scalable authentication.

</dc:description>
                  <dc:subject>Materials Science</dc:subject>
          <dc:subject>Counterfeit</dc:subject>
          <dc:subject>Dendrites</dc:subject>
          <dc:subject>identifiers</dc:subject>
          <dc:subject>Laplacian Instabilities</dc:subject>
          <dc:subject>Saffman-Taylor Effect</dc:subject>
          <dc:subject>Viscous fingers</dc:subject>
                  <dc:title>Formation Of Dendritic Identifiers Using Viscous Fluids</dc:title></oai_dc:dc></metadata></record></GetRecord></OAI-PMH>
