Optical Filter Selection for High Confidence Discrimination of Strongly Overlapping Infrared Chemical Spectra
Optical filter-based chemical sensing techniques provide a new avenue to develop low-cost infrared sensors. These methods utilize multiple infrared optical filters to selectively measure different response functions for various chemicals, dependent on each chemical’s infrared absorption. Rather than...
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Veröffentlicht in: | Analytical chemistry (Washington) 2015-09, Vol.87 (17), p.8798-8808 |
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creator | Major, Kevin J Poutous, Menelaos K Ewing, Kenneth J Dunnill, Kevin F Sanghera, Jasbinder S Aggarwal, Ishwar D |
description | Optical filter-based chemical sensing techniques provide a new avenue to develop low-cost infrared sensors. These methods utilize multiple infrared optical filters to selectively measure different response functions for various chemicals, dependent on each chemical’s infrared absorption. Rather than identifying distinct spectral features, which can then be used to determine the identity of a target chemical, optical filter-based approaches rely on measuring differences in the ensemble response between a given filter set and specific chemicals of interest. Therefore, the results of such methods are highly dependent on the original optical filter choice, which will dictate the selectivity, sensitivity, and stability of any filter-based sensing method. Recently, a method has been developed that utilizes unique detection vector operations defined by optical multifilter responses, to discriminate between volatile chemical vapors. This method, comparative-discrimination spectral detection (CDSD), is a technique which employs broadband optical filters to selectively discriminate between chemicals with highly overlapping infrared absorption spectra. CDSD has been shown to correctly distinguish between similar chemicals in the carbon–hydrogen stretch region of the infrared absorption spectra from 2800–3100 cm–1. A key challenge to this approach is how to determine which optical filter sets should be utilized to achieve the greatest discrimination between target chemicals. Previous studies used empirical approaches to select the optical filter set; however this is insufficient to determine the optimum selectivity between strongly overlapping chemical spectra. Here we present a numerical approach to systematically study the effects of filter positioning and bandwidth on a number of three-chemical systems. We describe how both the filter properties, as well as the chemicals in each set, affect the CDSD results and subsequent discrimination. These results demonstrate the importance of choosing the proper filter set and chemicals for comparative discrimination, in order to identify the target chemical of interest in the presence of closely matched chemical interferents. These findings are an integral step in the development of experimental prototype sensors, which will utilize CDSD. |
doi_str_mv | 10.1021/acs.analchem.5b01723 |
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These methods utilize multiple infrared optical filters to selectively measure different response functions for various chemicals, dependent on each chemical’s infrared absorption. Rather than identifying distinct spectral features, which can then be used to determine the identity of a target chemical, optical filter-based approaches rely on measuring differences in the ensemble response between a given filter set and specific chemicals of interest. Therefore, the results of such methods are highly dependent on the original optical filter choice, which will dictate the selectivity, sensitivity, and stability of any filter-based sensing method. Recently, a method has been developed that utilizes unique detection vector operations defined by optical multifilter responses, to discriminate between volatile chemical vapors. This method, comparative-discrimination spectral detection (CDSD), is a technique which employs broadband optical filters to selectively discriminate between chemicals with highly overlapping infrared absorption spectra. CDSD has been shown to correctly distinguish between similar chemicals in the carbon–hydrogen stretch region of the infrared absorption spectra from 2800–3100 cm–1. A key challenge to this approach is how to determine which optical filter sets should be utilized to achieve the greatest discrimination between target chemicals. Previous studies used empirical approaches to select the optical filter set; however this is insufficient to determine the optimum selectivity between strongly overlapping chemical spectra. Here we present a numerical approach to systematically study the effects of filter positioning and bandwidth on a number of three-chemical systems. We describe how both the filter properties, as well as the chemicals in each set, affect the CDSD results and subsequent discrimination. These results demonstrate the importance of choosing the proper filter set and chemicals for comparative discrimination, in order to identify the target chemical of interest in the presence of closely matched chemical interferents. These findings are an integral step in the development of experimental prototype sensors, which will utilize CDSD.</description><identifier>ISSN: 0003-2700</identifier><identifier>EISSN: 1520-6882</identifier><identifier>DOI: 10.1021/acs.analchem.5b01723</identifier><identifier>PMID: 26266761</identifier><identifier>CODEN: ANCHAM</identifier><language>eng</language><publisher>United States: American Chemical Society</publisher><subject>Chemicals ; Detection ; Discrimination ; Infrared ; Infrared absorption ; Optical filters ; Optics ; Prototypes ; Selectivity ; Sensitivity analysis ; Sensors ; Spectra ; Spectrum analysis</subject><ispartof>Analytical chemistry (Washington), 2015-09, Vol.87 (17), p.8798-8808</ispartof><rights>Copyright © American Chemical Society</rights><rights>Copyright American Chemical Society Sep 1, 2015</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-a512t-4d467327232ae8317c507b5903467e6bea451fd4f8990d6cb3991bf332d477173</citedby><cites>FETCH-LOGICAL-a512t-4d467327232ae8317c507b5903467e6bea451fd4f8990d6cb3991bf332d477173</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://pubs.acs.org/doi/pdf/10.1021/acs.analchem.5b01723$$EPDF$$P50$$Gacs$$H</linktopdf><linktohtml>$$Uhttps://pubs.acs.org/doi/10.1021/acs.analchem.5b01723$$EHTML$$P50$$Gacs$$H</linktohtml><link.rule.ids>315,781,785,2766,27081,27929,27930,56743,56793</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/26266761$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Major, Kevin J</creatorcontrib><creatorcontrib>Poutous, Menelaos K</creatorcontrib><creatorcontrib>Ewing, Kenneth J</creatorcontrib><creatorcontrib>Dunnill, Kevin F</creatorcontrib><creatorcontrib>Sanghera, Jasbinder S</creatorcontrib><creatorcontrib>Aggarwal, Ishwar D</creatorcontrib><title>Optical Filter Selection for High Confidence Discrimination of Strongly Overlapping Infrared Chemical Spectra</title><title>Analytical chemistry (Washington)</title><addtitle>Anal. Chem</addtitle><description>Optical filter-based chemical sensing techniques provide a new avenue to develop low-cost infrared sensors. These methods utilize multiple infrared optical filters to selectively measure different response functions for various chemicals, dependent on each chemical’s infrared absorption. Rather than identifying distinct spectral features, which can then be used to determine the identity of a target chemical, optical filter-based approaches rely on measuring differences in the ensemble response between a given filter set and specific chemicals of interest. Therefore, the results of such methods are highly dependent on the original optical filter choice, which will dictate the selectivity, sensitivity, and stability of any filter-based sensing method. Recently, a method has been developed that utilizes unique detection vector operations defined by optical multifilter responses, to discriminate between volatile chemical vapors. This method, comparative-discrimination spectral detection (CDSD), is a technique which employs broadband optical filters to selectively discriminate between chemicals with highly overlapping infrared absorption spectra. CDSD has been shown to correctly distinguish between similar chemicals in the carbon–hydrogen stretch region of the infrared absorption spectra from 2800–3100 cm–1. A key challenge to this approach is how to determine which optical filter sets should be utilized to achieve the greatest discrimination between target chemicals. Previous studies used empirical approaches to select the optical filter set; however this is insufficient to determine the optimum selectivity between strongly overlapping chemical spectra. Here we present a numerical approach to systematically study the effects of filter positioning and bandwidth on a number of three-chemical systems. We describe how both the filter properties, as well as the chemicals in each set, affect the CDSD results and subsequent discrimination. These results demonstrate the importance of choosing the proper filter set and chemicals for comparative discrimination, in order to identify the target chemical of interest in the presence of closely matched chemical interferents. These findings are an integral step in the development of experimental prototype sensors, which will utilize CDSD.</description><subject>Chemicals</subject><subject>Detection</subject><subject>Discrimination</subject><subject>Infrared</subject><subject>Infrared absorption</subject><subject>Optical filters</subject><subject>Optics</subject><subject>Prototypes</subject><subject>Selectivity</subject><subject>Sensitivity analysis</subject><subject>Sensors</subject><subject>Spectra</subject><subject>Spectrum analysis</subject><issn>0003-2700</issn><issn>1520-6882</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2015</creationdate><recordtype>article</recordtype><recordid>eNqNkU1rGzEQhkVpaVy3_6AUQS-5rDv6WGn3WNzmAwI-ODkvWq3kKGilrbQu5N9Xjp0Wegi5SCCeeTQzL0KfCawIUPJN6bxSQXl9b8ZV3QORlL1BC1JTqETT0LdoAQCsohLgDH3I-QGAECDiPTqjggohBVmgcTPNTiuPL5yfTcJb442eXQzYxoSv3O4er2OwbjBBG_zDZZ3c6IJ6QqLF2znFsPOPePPbJK-myYUdvg42qWQGvC69Pdm3U7Em9RG9s8pn8-l0L9Hdxc_b9VV1s7m8Xn-_qVRN6FzxgQvJaBmIKtMwInUNsq9bYOXdiN4oXhM7cNu0LQxC96xtSW8ZowOXkki2ROdH75Tir73JczeWzo33Kpi4zx2RNeOy5bx-BQpNC6RhB-vX_9CHuE8lggNFyq4pK8cS8SOlU8w5GdtNZWUqPXYEukNyXUmue06uOyVXyr6c5Pt-NMPfoueoCgBH4FD-7-OXnH8AHfqmig</recordid><startdate>20150901</startdate><enddate>20150901</enddate><creator>Major, Kevin J</creator><creator>Poutous, Menelaos K</creator><creator>Ewing, Kenneth J</creator><creator>Dunnill, Kevin F</creator><creator>Sanghera, Jasbinder S</creator><creator>Aggarwal, Ishwar D</creator><general>American Chemical Society</general><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7QF</scope><scope>7QO</scope><scope>7QQ</scope><scope>7SC</scope><scope>7SE</scope><scope>7SP</scope><scope>7SR</scope><scope>7TA</scope><scope>7TB</scope><scope>7TM</scope><scope>7U5</scope><scope>7U7</scope><scope>7U9</scope><scope>8BQ</scope><scope>8FD</scope><scope>C1K</scope><scope>F28</scope><scope>FR3</scope><scope>H8D</scope><scope>H8G</scope><scope>H94</scope><scope>JG9</scope><scope>JQ2</scope><scope>KR7</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>P64</scope><scope>7X8</scope></search><sort><creationdate>20150901</creationdate><title>Optical Filter Selection for High Confidence Discrimination of Strongly Overlapping Infrared Chemical Spectra</title><author>Major, Kevin J ; Poutous, Menelaos K ; Ewing, Kenneth J ; Dunnill, Kevin F ; Sanghera, Jasbinder S ; Aggarwal, Ishwar D</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-a512t-4d467327232ae8317c507b5903467e6bea451fd4f8990d6cb3991bf332d477173</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2015</creationdate><topic>Chemicals</topic><topic>Detection</topic><topic>Discrimination</topic><topic>Infrared</topic><topic>Infrared absorption</topic><topic>Optical filters</topic><topic>Optics</topic><topic>Prototypes</topic><topic>Selectivity</topic><topic>Sensitivity analysis</topic><topic>Sensors</topic><topic>Spectra</topic><topic>Spectrum analysis</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Major, Kevin J</creatorcontrib><creatorcontrib>Poutous, Menelaos K</creatorcontrib><creatorcontrib>Ewing, Kenneth J</creatorcontrib><creatorcontrib>Dunnill, Kevin F</creatorcontrib><creatorcontrib>Sanghera, Jasbinder S</creatorcontrib><creatorcontrib>Aggarwal, Ishwar D</creatorcontrib><collection>PubMed</collection><collection>CrossRef</collection><collection>Aluminium Industry Abstracts</collection><collection>Biotechnology Research Abstracts</collection><collection>Ceramic Abstracts</collection><collection>Computer and Information Systems Abstracts</collection><collection>Corrosion Abstracts</collection><collection>Electronics & Communications Abstracts</collection><collection>Engineered Materials Abstracts</collection><collection>Materials Business File</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Nucleic Acids Abstracts</collection><collection>Solid State and Superconductivity Abstracts</collection><collection>Toxicology Abstracts</collection><collection>Virology and AIDS Abstracts</collection><collection>METADEX</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ANTE: Abstracts in New Technology & Engineering</collection><collection>Engineering Research Database</collection><collection>Aerospace Database</collection><collection>Copper Technical Reference Library</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>Materials Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Civil Engineering Abstracts</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>MEDLINE - Academic</collection><jtitle>Analytical chemistry (Washington)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Major, Kevin J</au><au>Poutous, Menelaos K</au><au>Ewing, Kenneth J</au><au>Dunnill, Kevin F</au><au>Sanghera, Jasbinder S</au><au>Aggarwal, Ishwar D</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Optical Filter Selection for High Confidence Discrimination of Strongly Overlapping Infrared Chemical Spectra</atitle><jtitle>Analytical chemistry (Washington)</jtitle><addtitle>Anal. Chem</addtitle><date>2015-09-01</date><risdate>2015</risdate><volume>87</volume><issue>17</issue><spage>8798</spage><epage>8808</epage><pages>8798-8808</pages><issn>0003-2700</issn><eissn>1520-6882</eissn><coden>ANCHAM</coden><abstract>Optical filter-based chemical sensing techniques provide a new avenue to develop low-cost infrared sensors. These methods utilize multiple infrared optical filters to selectively measure different response functions for various chemicals, dependent on each chemical’s infrared absorption. Rather than identifying distinct spectral features, which can then be used to determine the identity of a target chemical, optical filter-based approaches rely on measuring differences in the ensemble response between a given filter set and specific chemicals of interest. Therefore, the results of such methods are highly dependent on the original optical filter choice, which will dictate the selectivity, sensitivity, and stability of any filter-based sensing method. Recently, a method has been developed that utilizes unique detection vector operations defined by optical multifilter responses, to discriminate between volatile chemical vapors. This method, comparative-discrimination spectral detection (CDSD), is a technique which employs broadband optical filters to selectively discriminate between chemicals with highly overlapping infrared absorption spectra. CDSD has been shown to correctly distinguish between similar chemicals in the carbon–hydrogen stretch region of the infrared absorption spectra from 2800–3100 cm–1. A key challenge to this approach is how to determine which optical filter sets should be utilized to achieve the greatest discrimination between target chemicals. Previous studies used empirical approaches to select the optical filter set; however this is insufficient to determine the optimum selectivity between strongly overlapping chemical spectra. Here we present a numerical approach to systematically study the effects of filter positioning and bandwidth on a number of three-chemical systems. We describe how both the filter properties, as well as the chemicals in each set, affect the CDSD results and subsequent discrimination. These results demonstrate the importance of choosing the proper filter set and chemicals for comparative discrimination, in order to identify the target chemical of interest in the presence of closely matched chemical interferents. These findings are an integral step in the development of experimental prototype sensors, which will utilize CDSD.</abstract><cop>United States</cop><pub>American Chemical Society</pub><pmid>26266761</pmid><doi>10.1021/acs.analchem.5b01723</doi><tpages>11</tpages></addata></record> |
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subjects | Chemicals Detection Discrimination Infrared Infrared absorption Optical filters Optics Prototypes Selectivity Sensitivity analysis Sensors Spectra Spectrum analysis |
title | Optical Filter Selection for High Confidence Discrimination of Strongly Overlapping Infrared Chemical Spectra |
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