Over the last decade, microfluidic paper-based analytical devices (μPADs) have emerged as innovative platforms due to their cost-effectiveness, compatibility, availability, user-friendliness, and disposability. Wax printing is one of the most widely used techniques for the fabrication of μPADs. This study aims to optimize wax-printing fabrication parameters, simulate pressure and fluid dynamics, and apply the optimized conditions to create various microfluidic patterns and develop a pH indicator for food safety analysis. It also focuses on developing a smartphone app to automate the results of chromogenic reactions. The influences of process parameters, namely molten wax temperature (100-160 °C), applied pressure (0.1-6 g/mm 2 ), stamp width (0.5-2 mm), and holding time (1-10 s) on the printing quality and wax spreading were studied. A smartphone app was developed using the Thunkable workspace, with Imagga integrated as the application programming interface platform. The results indicated that Whatman grade 4 exhibited the highest fluid velocity among the tested paper types, which is suggested as a suitable substrate for milk safety analysis. The optimal fabrication conditions for achieving high-quality wax printing with minimal wax spreading were determined to be at 115 °C, 1.575 g/mm 2 , 0.875 mm, and 3.25 s for temperature, pressure, stamp width, and holding time, respectively. Using these optimized conditions, a paper-based pH sticker was developed to detect pH levels ranging from 1 to 10 for milk safety analysis. The color output ranged from red at pH 1 to blue at pH 10, with a greenish hue observed around the neutral pH range. These results indicated the reliability and adaptability of the device for on-site detection of food safety. • Optimum fabrication parameters were 115 °C, 1.575 g/mm 2 , 0.875 mm, and 3.25 s • Wax printing improved with higher temperature and greater applied pressure • Wax spreading increased with higher temperature, pressure, and wider stamp width • The developed pH indicator device could detect pH levels from 1 to 10 • The smartphone app proved a reliable tool for color-based pH detection
Pou et al. (Fri,) studied this question.
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