Uric acid is a critical biomarker of purine metabolism — too high points to gout, hypertension, renal disease; too low correlates with neurodegenerative disorders. This work introduces a μPAD + smartphone platform that quantifies UA between 1.5 – 25 mg/dL without external light sources, enzymes, or nanoparticles.
Microfluidic channels are drawn directly onto Whatman G1 filter paper by a low-cost DIY XY plotter, using technical pens filled with a PDMS/heptane hydrophobic solution. Detection runs on a chromogenic reaction between potassium ferricyanide and ferric chloride — uric acid intensifies the resulting bluish-green complex, and a custom Android app reads its luminance against eight on-chip reference zones.
Healthy plasma carries 2.7 – 7.2 mg/dL of uric acid. Cross the upper bound and you risk gout, hypertension, chronic renal disease, metabolic syndrome, and cardiovascular disease. Cross the lower bound and the literature links you to multiple sclerosis, Alzheimer's, Parkinson's. Most existing detection mechanisms — electrochemical electrodes, enzyme assays, plasmon resonance with silver nanoparticles — are accurate but require lab infrastructure, reagent stability, or expensive nanomaterials.
Paper is a remarkable substrate: capillary action drives fluid without a pump, the fibre network stores reagents in an active state, and a single sheet costs essentially nothing. Since Whitesides' group introduced μPADs in 2007, fabrication techniques have multiplied — wax printing, photolithography, screen printing, inkjet, 3D printing. This work uses the cheapest of them: an XY plotter holding a technical drawing pen filled with PDMS.
μPADs are drawn directly onto Whatman Grade-1 filter paper (pore size 11 μm) with a DIY XY plotter controlled by Inkscape v1.2 — no G-code conversion required. A technical drawing pen, fitted with a 0.6 mm nib, dispenses an optimised hydrophobic solution: PDMS + Sylgard 184 (10:1) mixed with n-heptane (3:1) to tune viscosity. Curing at 150 °C for 15 min anchors the channels to the cellulose fibres.
The result: a fully hydrophobic boundary — measured at 106.04° mean contact angle over ten samples — that confines aqueous samples to the patterned zones. SEM imaging confirms that PDMS smooths the fibrous surface, reducing roughness and amplifying the wettability contrast between treated and untreated paper.
Detection runs on a redox cascade between two iron-containing reagents and uric acid. Conventional protocols introduce UA before ferric chloride, leaving the –CN group strongly bonded to Fe²⁺ and producing only a weak signal. This work reverses the order: ferricyanide first meets Fe³⁺ to form a pre-complex, then UA arrives and drives the electron transfer that yields a deeply-coloured Prussian-blue product.
FTIR confirms the mechanistic shift — the modified sequence shows a free, lower-bond-order –CN peak (2086 cm⁻¹) and a weaker C-O stretch (1035 cm⁻¹), both signatures of incomplete coordination prior to the UA encounter. UV–Vis at λ_max = 285 nm traces a first-order kinetic relationship — exactly what would be expected of a slow rate-determining step releasing two hydrogens from UA.
The Android app captures or imports an image of the μPAD, detects the wells via OpenCV's Hough Circle Transform, and calculates per-zone luminance using the standard relation
Calibration intensities are interpolated linearly to estimate the unknown — and the app then maps the value into a non-technical category. The whole pipeline is split across three activities: MainActivity for capture, AnalysisActivity for user input, GraphActivity for interpolation and plotting via MPAndroidChart.