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ARPA-E Awards PARC Funding to Develop Carbon Nanotube Printed Methane Detection Sensor Array

Come: Chinese Academy of Sciences    Date: 2015-06-18 10:22:25


 PARC, a Xerox company, has secured funding with the U.S. Department of Energys Advanced Research Projects Agency-Energy (ARPA-E) under the Methane Observation Networks with Innovative Technology to Obtain Reductions (MONITOR) program.

PARC will deliver very low cost printed sensor arrays to quantify and locate methane leaks, using a variety of modified carbon nanotube (CNT) sensors. The combined response of the sensors will provide "fingerprints" for methane and other gases. The novel approach offers a solution to identify, quantify and locate natural gas leaks at a cost point compatible with widespread deployment. Methane, a major component of natural gas, is a significant greenhouse gas, with many times the heat-trapping effect of carbon dioxide.

"We are very excited about this project," said David Schwartz, project lead and Manager of Energy Devices and Systems at PARC. "It is a perfect example of how printed sensor systems can provide new capabilities and enable applications with real positive impact in the energy sector and beyond."

The ARPA-E funded System of Printed Hybrid Intelligent Nano-Chemical Sensors (SPHINCS) will be delivered in partnership with BP and NASA Ames Research Center. BP will provide gas composition data, access to production sites and other facilities, and will help develop a market strategy to address upstream and downstream applications. The system will build upon NASA Ames delivered and successful demonstration of both best-in-class electrochemical methane sensors and selective gas sensor arrays.

PARCs methane detection system is based on sensor arrays fabricated on polymer substrates. Each substrate contains functional printed CNT sensor elements and supporting electronics. The CNTs are modified with dopants, coatings, or nanoparticles, allowing them to respond differently to different gases. Pattern matching supported by machine learning techniques allows specific gas "fingerprints" to be discerned from the combined sensor data. PARCs history of successfully enabling ultra-low-cost, high-performance deployable electronic systems for commercial applications will accelerate the development cycle for this technology. The system will have broad applicability beyond gas wells to pipelines, industrial and residential gas-sensing applications.

This SPHINCS project is part of a broad portfolio within the PARC Energy Technology Program aimed at developing practical solutions to make clean and abundant energy available across a wide range of applications. This includes a focus on improving chemical energy storage for EVs, consumer electronics, and electric grid support; advanced energy conversion devices, including medium temperature fuel cells; harsh-environment wireless sensors to improve the efficiency of coal gasification plants; and advanced analytics to maximize energy utilization.

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