3D Printing the Way to Truly Remote, Autonomous, Solar Powered Sensor Networks for Environmental Monitoring of Trace Heavy Metals By Calibration-Less Anodic Stripping Coulometry of µl Sized Samples

Wednesday, October 14, 2015: 08:30
106-C (Phoenix Convention Center)
M. M. Marei, T. J. Roussel Jr., R. P. Baldwin (University of Louisville), and R. S. Keynton (University of Louisville)
The agency for toxic substances and disease registry has consistently listed As, Pb Hg, and Cd as the pollutants of most concern at Superfund sites (recently #1, 2, 3, 7, respectively, amongst hundreds of prioritized hazardous substances). Also of concern is the prevalence of arsenic in groundwater at hundreds of thousands of wells used for drinking by millions of people worldwide. Heavy metal monitoring in natural waters is currently performed in a snapshot fashion where analysis is occasionally possible by sophisticated instruments after sample collection and transportation to centralized laboratories or, less frequently, by technicians wielding portable instruments. Such a snapshot approach to analysis requires a sustained and coordinated effort to monitor many thousands of decentralized sites as frequently as possible, and a preferable approach is the deployment of remote sensor networks. Our group has therefore been interested in the development of truly remote sensor platforms that sufficiently deliver a trifecta of important attributes for heavy metals monitoring – practical, sensitive, and selective measurements– to direct the efforts of central laboratories and mobile operators to where they are most needed.

The primary challenges of truly remote sensors revolve around the dual challenges of signal calibration and sample pretreatment, which are typically performed by the operator. We will demonstrate a sensor platform that is capable of low ppb level measurements of heavy metals such as copper and arsenite from 2 µL sample volumes – without any calibration. This calibration-less aspect is achieved by using anodic stripping coulometry after exhaustive deposition of dissolved metals from a finite volume within a stopped flow thin layer cell in about a minute. The use of coulometry in this configuration of electrochemical cell offers rapid analysis, independence from ambient conditions such as temperature, and also tolerates partial electrode fouling which is likely to occur during extended field operation. We will also demonstrate simple approaches for automated sample pretreatment including on-site acidification and dissolved oxygen removal.

The use of a coulometric electrochemical method offers the advantage of inexpensive and simple to automate instrumentation with minimal energy requirements. The heart of the sensor is a microfabricated thin-film Au microelectrode array housed within a microfluidic chamber which offers practical advantages including mass-producible, redundant, inexpensive sensors, with a minimal need for on-site reagents. Additionally, we will overview how existing technologies such as miniature electronics and the prevalent communications networks for real-time data acquisition further support the feasibility of our approach. For instance, replacing the screen of even the most primitive smart phone with a solar panel already provides a platform which incorporates a micro-processor, communications ability, and a battery. The microprocessor and battery can be used to drive a miniature potentiostat and a host of commercially available, inexpensive micro-pumps to handle on-site sampling and mixing as required.  

Despite the commercial availability of many individual components and the promise of the methods we have developed, the remote use of the sensor in real world applications has been limited by the challenge of bridging the gap between a bulk volume of water and a microfluidic chamber where the measurements are made. Essentially, the ideal platform should consist of a fluidic inlet port which is compatible with the macro sized sample, and an outlet to discharge the analyzed sample. The focus of this presentation will therefore be a greatly simplified 3D printed version of platform which contains internal components such as channels and valves to direct and control the sample during operation. We also intend to explore how several modules which perform different pretreatment or measurement functions can be connected to a central 3D printed hub which contains a shared set of the most expensive components (i.e., pumps, valves, etc.). Such a design architecture would seem to offer benefits in terms of operational flexibility and simplicity and also offers the potential for the use of redundant sensors to lengthen intervals between manual maintenance. Lastly, we aim to demonstrate the stability of the platform under conditions as close to real world analysis as possible.