Grant Award Year:
2019
Principal Investigator:
Jinglei Ping
Mechanical and Industrial Engineering
University of Massachusetts Amherst
Research Description:
Water heavy metal toxicity has posed significant threats to the health of exposed human beings and wildlife animals in Massachusetts. The real-time monitoring of multiple heavy-metal ions at large spatiotemporal scale is crucial to the state’s water safety, public health, and development of water toxin guidance values which entails investigations on health outcomes of long-term low-level heavy-metal exposure. Typical heavy-metal monitoring, however, is lab-based with low efficiency in time and cost, and enabling in-field sensor systems with sufficient efficacy remain lacking. This gap can be filled by developing a network of smart sensors, each of which can be placed at water bodies of interest, monitor heavy-metal levels, and transmit data wirelessly to a center to be analyzed. This program aims to create smart sensors, the building block of the sensor network, that integrate four innovative technologies we have developed: (1) preparation of large-scale high-quality graphene monolayers, (2) aptamer-functionalized graphene microelectrodes that can detect heavy metal ions with unprecedented sensitivity, (3) a programmable ultra-low-power wireless microelectronic platform, and (4) a microfluidic sample processor. The targeted smart sensors will be credit card–sized, multiplexed for testing various types of heavy metals simultaneously, and powerable by a button cell battery for months of signal processing and wireless data transmission. Remarkably, the smart sensors will be programmable for automatic background-drift cancellation, which, along with the monolayer nature of graphene and the reference-free device structure of the sensors, will lead to ultra-high sensitivity (at the magnitude of 1 ng/mL) for quantifying heavy-metal concentrations. Enabled by a microfluidic heavy-metal extractor based on the sample processor, the smart sensors are suitable for monitoring heavy-metal levels for various water bodies: lakes, ponds, reservoirs, water towers, tap water outlets, etc. The planned smart sensors represent the first type of nano-enabled on-site analytical tool to be used as components in an ultimate water heavy-metal monitoring wireless sensor network. The deployment of the sensor network holds great promise for substantially enhancing the water safety of Massachusetts and paves the way to building scientific understanding of the toxicology of chronic low-level water heavy-metal exposure. This highly interdisciplinary research will also provide significant research-based educational and training resources and opportunities to students, particularly those of underrepresented groups, from K-12 to graduate in Amherst area.