An automated 3D-printed smartphone platform integrated with optoelectrowetting (OEW) microfluidic chip for on-site monitoring of viable algae in water.

A sudden increase of algae and their associated toxins in aquatic ecosystems can detrimentally affect the quality of the water, causing serious socio-economic and public health problems. To prevent the spread of harmful algae in aquatic ecosystems, it is essential to track the water's quality through rapid and in-situ monitoring systems. Conventional methods of algae quantification such as microscopy, hemocytometry, and UV-vis spectroscopy, however, are often unsuitable or inconvenient for in-situ assessment as they require skilled labor and expensive equipment. In this study, we developed a three-dimensional (3D)-printed smartphone platform integrated with a light-driven microfluidic chip operated by optoelectrowetting (OEW). This OEW-driven microfluidic chip not only allows multiplexed drop-wise functions such as droplet transportation, merging, mixing, immobilization on a detection zone, for on-chip water sample preparation but also fluorescent detection and counting of target algae cells using a commercially-available smartphone. Two freshwater algae (C. reinhardtii and M. aeruginosa) and two marine water algae (Amphiprora sp and C. closterium) were employed to validate the 3D-printed smartphone platform in this study. The fluorescence images of viable algae and the cell counting from the microfluidic chip were comparable to the results from a hemocytometer (P > 0.05). We have further conducted tests with spiked samples using freshwater and marine water that were directly collected from environmental samples, showing the same order of magnitude of cell numbers in the spiked and control cultures of algae cells (10 cell/mL, P > 0.05). Unlike traditional quantification methods, the 3D-printed smartphone platform integrated with the OEW offers a highly portable, user-friendly, low-cost tool that enables simple on-chip sample preparation and detection of viable algae. Thus, this stand-alone technology has the potential for rapid and in-situ monitoring of water quality, while using the smartphone's wireless communication capabilities to report the quality of the water in real-time.