Pathogen Detection using a Flexible Substrate Sensor System
High sensitivity with very large volume and area samplesMonitoring with real-time data processingConforms to the specific geometry of the measured environmentOnboard and/or external analysis deviceData exfiltration network automatically adjusts to the dimensions of the substrateModular and inexpensive to manufacture
Municipal systems i.e. water supply linings, wastewater systems and landfills Oil and gas pipelinesBuildings, roads and bridgesCapable in a multitude of environmental and infrastructure applications depending on shape In a sheet – to line landfillsIn a strip – for wick drains to monitor groundwater and subsurface contaminantsIn a cylindrical arrangement – lining pipelines and conduits, including inversion lining procedure for facilities already in placeIn a strip and cylindrical shape arrangements – in drilling and for exploration tools in oil wells and in the mining industryMeasurable characteristics of interest pH, ionic strength, temperature, electrical impedance, turbidity, stress, strain, flexure, vibration, non-vibratory motion, acoustics and corrosion.
Current systems have to either sacrifice sensitivity to sample a large volume or sample a much smaller volume at the required sensitivity. The result is that it is either too low to detect the analyte at the required level or the smaller volume is not representative of the larger volume. It is therefore, either too expensive, too time consuming or impossible to perform the analysis. It has also been very difficult for present systems to transmit information. Our approach solves these long standing problems with both onboard and external devices transmitting signals in real-time via a wireless network. The network can control the readout of the array as well as optimize its operation and lifetime. These novel enhancements include initiating sensor cleaning and sleep cycles as well as changing readout sequences to optimizing detection of any analyte or subset of analytes.
United States
8,701,469
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