This project will support the development of a novel ?electronic tongue cone penetrometer? for on-site characterization of heavy metals such as Arsenic, Cadmium, Copper, Chromium, Lead, Manganese, Mercury, Nickel, Selenium, Thallium and Zinc in soils and groundwater. The electronic tongue is a device that mimics the human gustatory system using microelectrode sensor arrays coupled with artificial intelligence for pattern recognition. The project will involve fundamental research to design and assemble materials for highly sensitive and broadly-selective microelectrode sensors. This will be followed by the development of conductometric and voltammetric techniques for the hybrid electronic tongue. In addition, intelligent machine learning models for multivariate data processing and interpretation will be developed for classification and quantification of heavy metals. Calibration chamber studies will be conducted to develop methods for analysis of heavy metals in aqueous soil samples. Finally, the microelectrode sensor arrays will be deployed in a field-rugged cone penetrometer to facilitate real-time geoenvironmental site characterization.
The successful completion of this project would result in the development of a novel in situ tool and method, for rapid, safe, and cost effective characterization of heavy metal contaminated sites. This minimally invasive technology will limit potential personnel exposure to contaminated media, and reduce the amount of investigation-derived waste normally generated during conventional borehole drilling and sampling activities. It will also reduce the time-consuming laboratory analysis during initial site investigations, and will provide regulatory agencies with critical information that is necessary for taking appropriate steps such as communicating drinking water advisories in a timely manner. This technology can also be expanded further to detect other types of toxins, making this approach applicable to diverse fields such as biotechnology, pharmaceuticals and medical diagnostics, food industry, environmental monitoring, law enforcement and homeland security.
Federal Award ID: 1031505 Award Duration: 09/30/2010-08/31/14 NSF Program Officer Name: Richard Fragaszy Awardee: University of Massachusetts Lowell Principal Investigator: Pradeep Kurup Co-Principal Investigator: Ramaswamy Nagarajan Project Outcomes: Intellectual Merit: Long-term exposure to heavy metals such as arsenic, cadmium, lead, and mercury can cause damage to the kidney, liver, gastrointestinal tract and the central nervous system. Conventional methods for characterizing heavy metals in soil and groundwater require detailed sampling procedures followed by laboratory analysis using large, expensive laboratory instruments that can only be operated by highly skilled operators. This project resulted in the development of a novel "electronic tongue", using an array of electrodes (sensors) coupled with artificial intelligence for identification of heavy metals. Novel polymer modified electrodes and bismuth modified electrodes were synthesized to achieve very low parts-per-billion detection limits of toxic heavy metals in water. The researchers also developed a microprocessor driven potentiostat, and software to apply desired voltage waveforms and measure the resulting current. A sampling penetrometer made of high-density polyethylene was custom fabricated to house the electrodes. The tips of the electrodes protruded into a sample electrochemical cell within the probe. An electric centrifugal air pump was used to sample the soil pore water into the cell through a 3.2 mm thick porous plastic filter ring with an average pore size of 150 μm. The electronic tongue is based on an electrochemical technique known as voltammetry. In general, the electrodes containing specialized coatings interact with the metal ions of interest and generate unique signatures or fingerprints that identify various metal ions. Intelligent pattern recognition techniques based on principal component analysis and decision trees were developed to learn and interpret the data. Once trained, the electronic tongue would be capable of detecting a number of heavy metal species, analogous to how different chemical compounds responsible for taste are perceived by the taste receptors in the human tongue. The decision tree prediction models were able to classify the heavy metals with close to 100% accuracy both in water and aqueous sand. This study demonstrated the feasibility of a rapid and cost-effective in situ method for qualitative and quantitative analysis of heavy metals in soil and water. Broader Impact: This project provided research and educational experience for five graduate students, two undergraduate students, and a postdoctoral research associate. The researchers gained experience in synthesizing novel materials (coatings for electrodes) for highly sensitive electrodes, fabricating potentiostats and developing data acquisition systems with graphical user interface, conducting experiments, analyzing and interpreting data using various pattern recognition techniques. The students and the postdoctoral research associate also acquired collaborative skills through interactions with researchers from different disciplines, including engineers and consultants from industry and state agencies. The novel electronic tongue developed in this project has contributed to the existing infrastructure for sensing, detection and pattern recognition at the University of Massachusetts Lowell. An international patent has been filed under the PCT. The project team is exploring the possibility of commercialization/licensing of the technology. The results from this project have been published in a peer-reviewed journal and in conference proceedings. The research outcomes were also presented at various national and international scientific conferences. In addition, the technology was demonstrated to students from local high schools. The outcome of this project is expected to have important societal benefits that could positively impact human health and save human lives. Timely detection and prediction of heavy metals in water will provide regulatory agencies with critical information that is necessary for taking appropriate steps such as communicating drinking water advisories in a timely manner. The electronic tongue developed in this project can also be used for food safety analysis; for testing heavy metals in food and beverages. Beyond heavy metal sensing this research also has also shown promise in detecting energetic compounds and therefore has potential applications in defense and homeland security. The extension of this technology to sensing analytes in very complicated matrices such as food opens new opportunities for fielding this technology in food safety monitoring applications.