Colorado State University
Ruth is a PhD student in the Department of Chemistry at Colorado State University, working under Dr. Chuck Henry and Dr. Thomas Borch. She is working on developing inexpensive sensors for environmental contaminants.
Point-of-need heavy metal detection with a paper-based multiplexed sensor array
Environmental heavy metal contamination is a critical issue that can cause severe human health effects, including kidney disease, cancer, and nerve and skeletal damage. Processes and sources like mining, industrial waste, and agricultural runoff leach heavy metals into ground and surface water, entering drinking water systems for humans and animals. Detection of heavy metals is necessary to evaluate a human’s risk of exposure from a contaminated site and its potential for remediation. Traditional analytical methods are sensitive and accurate but cost- and time-prohibitive when used for frequent measurements. In addition, they are laboratory-based and require skilled personnel to run. An inexpensive alternative that provides fast results in the field with high temporal and spatial resolution of an area will help improve our understanding of contaminant distribution as well as concentration changes with time and other factors.
Microfluidic paper-based devices (µPADs) offer a cost-effective, fast, easy-to-use alternative that is field-compatible for almost real-time analysis. µPADs combine pump-less fluid flow with dry reagent chemistry to perform a chemical reaction in a confined region on paper. The devices have been applied to a variety of disciplines, including medical diagnostics, food quality, and environmental contaminants. For a standard spot test, a hydrophobic wax barrier is printed on paper, forming a circular sample zone, and appropriate reagents are loaded on the spot. The addition of a water sample causes a color change correlating to analyte concentration. This approach has worked for many years, but it is challenging to find reagents that are specific to the analyte of interest at relevant detection limits and are not susceptible to interferences. This optimization is both time- and cost-intensive.
Our proposed device uses the concept of a sensor array, or a collection of spot tests that serve as multiple detection zones. Our sensor array consists of three layers of vertically aligned paper spots. The first layer adds one of several masking agents, the second layer adjusts the pH across a broad range with a buffer, and the final layer contains an indicator that changes color in the presence of one or more metals. This design results in 16 combinations of reagents that generate an array of spots with various colors after addition of a water sample. Different combinations of colors indicate different metals. We have successfully used linear discriminant analysis (LDA) to show discrimination between metal combinations based on the colors that result from their complexation with the indicators at different pHs. The LDA model can also predict the classification of unknown samples. For use in the field, a smartphone app can be used to take a picture of the device and analyze it to produce comprehensive results about which metals are present in the sample and at what concentration. Because the paper device is inexpensive, portable, and produces results quickly, it can be used to evaluate remediation sites with high spatial and temporal resolution as well as assess water quality. This concept can also be expanded to other environmental contaminants to provide a suite of analyses.