Flexible, Graphene-Based Detector Arrays for Petrochemical Exposure Monitoring
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2017/05/09
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By Patel SV
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Series: Grant Final Reports
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Description:In Phase I of this SBIR program, Seacoast Science investigated the feasibility developing chemical vapor sensitive threads from a polymer-nanocomposite using the highly conduct nature of graphene and the selectivity of certain polymers toward specific chemical targets. Seacoast focused on determining what physical and chemical characteristics of these nanocomposites could be used to detect fuel-related hydrocarbons, specifically benzene and naphthalene, while excluding less noxious chemical vapors. The goal is developing an exposure monitor for workers who are commonly exposed to these chemicals. The ideal result of the project is a low-cost, easy-to-use, wearable chemical dosimeter in the form of threads sewn into badges or Velcro patches, that can be worn during work-shifts to log exposures in real time and simultaneously or subsequently transmit data. Phase I focused on the determining what characteristics of polymers are necessary to fabricate robust sensing threads, and how to best process these threads for optimal sensitivity and durability. We used polymers that Seacoast has previously shown to have good sensitivity to hydrocarbons, particularly benzene. We included other selected polymers that can be used in conjunction with pattern recognition techniques (in Phase II) for interferent rejection. To fabricate the threads, Seacoast employed common manufacturing techniques, including solution-extrusion, melt-extrusion, and solution-casting methods. Thread materials were exposed to vapors of 10 different chemicals to compare response characteristics. The Phase I work showed that the method of fabrication highly influenced both the sensitivity of the threads as well as physical properties of the threads. Early in Phase I, we discovered that the temperatures required for melt-extrusion were sufficiently high as to destroy the chemical sensing properties of the majority of the polymers. Based on this finding, the fabrication strategy and the work plan were modified. Because melt temperatures degraded the polymers, solution-extruded threads had better sensing characteristics than melt-extruded threads. Additionally, melt-extruded threads were very fragile, which is a concern that needs to be addressed before field-use of this technology will be practical. In contrast, solution-cast and solution-extruded threads had comparable sensitivity and both had better sensitivity than melt-extruded threads. Both were stronger than melt-extruded threads, but their thickness is more difficult to control when fabricating devices in small prototype quantities. In addition, a thermal annealing treatment markedly reduced signal-noise for one of the key benzene and naphthalene sensitive polymer-nanocomposites, vastly improving sensitivity for this application. In Phase II the materials will be optimized and a fully integrated readout system will be developed. Mechanical properties will be studied to improve ruggedness for field-use. These systems will be tested in Seacoast's controlled test room, on mannequins, to simulate various exposure conditions, and verify system performance. Algorithms to compensate for environmental factors will be developed and implemented in a robust electronics package. [Description provided by NIOSH]
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Pages in Document:1-35
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NIOSHTIC Number:nn:20052877
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NTIS Accession Number:PB2022-100442
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Citation:Atlanta, GA: U.S. Department of Health and Human Services, Public Health Service, Centers for Disease Control and Prevention, National Institute for Occupational Safety and Health, R43-OH-010881, 2017 May; :1-35
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Contact Point Address:Sanjay V. Patel, 2151 Las Palmas, Suite C, Carlsbad, CA 92011
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Email:sanjay@seacoastscience.com
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Federal Fiscal Year:2017
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Performing Organization:Seacoast Science, Inc., Carlsbad, California
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Peer Reviewed:False
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Start Date:20160901
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Source Full Name:National Institute for Occupational Safety and Health
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End Date:20170228
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Main Document Checksum:urn:sha-512:ef4228616dd73dec68cb7336d72133ccd910b434ef52feb6e218d5c3a578c0db572de0b1b64ec0075867c5da6d838b045dddf4e1d47545279d7ec22c4c39fea1
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