Effect of layer thickness variation on sensitivity: An SPR based sensor for formalin detection

Food preservatives and additives are the universal concern of recent days. Particularly, formalin is a chemical compound that is being commonly mingled with food for the preservation purpose. The recurrent ingesting of formalin contaminated food causes uncompromising health sicknesses like chronic c...
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Autor*in:	Md. Moznuzzaman [verfasserIn] Md. Rafiqul Islam [verfasserIn] Imran Khan [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2021

Schlagwörter:	Surface plasmon resonance Formalin Numerical modeling Chitosan Sensitivity Quality factor

Übergeordnetes Werk:	In: Sensing and Bio-Sensing Research - Elsevier, 2016, 32(2021), Seite 100419-
Übergeordnetes Werk:	volume:32 ; year:2021 ; pages:100419-

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.1016/j.sbsr.2021.100419

Katalog-ID:	DOAJ057256594

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520			\|a Food preservatives and additives are the universal concern of recent days. Particularly, formalin is a chemical compound that is being commonly mingled with food for the preservation purpose. The recurrent ingesting of formalin contaminated food causes uncompromising health sicknesses like chronic cancer. Therefore, identification of formalin in food substances is an extreme need and day by day this need is growing as a general issue in the emerging terrains. In this article, a surface plasmon resonance (SPR) based sensor, comprised of graphene-PtSe2 combined layers associated with a ZnO nano-sheet is presented for the detection of formalin in liquid solution. The performance of the sensor has been analyzed through an analytical approach using MATLAB commercial software. Consequence due to incorporation of the Graphene-PtSe2 combined layer into the sensor structure along with ZnO layer has been studied. The observed sensitivity and quality factor are 155.33° RIU−1 and 88.89 RIU−1, respectively. This sensor senses the presence of formalin molecules by using attenuated total reflection (ATR) approach, assessing the reflectance vs SPR angle. It is found that the sensitivity of the conventional SPR based sensor is 128.33° RIU−1, whereas an improved sensitivity of 155.33° RIU−1 is obtained for this proposed amalgamated sensor structure. Later in time, a comparison of performance for different SPR sensor structures and the proposed sensor has been studied. Finally, another comparison study has been made with performance of the proposed sensor to other reported sensor in the literature.
650		4	\|a Surface plasmon resonance
650		4	\|a Formalin
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700	0		\|a Imran Khan \|e verfasserin \|4 aut
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allfieldsGer	10.1016/j.sbsr.2021.100419 doi (DE-627)DOAJ057256594 (DE-599)DOAJ2c5c045d78894198b1eeab83d19b5f99 DE-627 ger DE-627 rakwb eng TA1-2040 Md. Moznuzzaman verfasserin aut Effect of layer thickness variation on sensitivity: An SPR based sensor for formalin detection 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Food preservatives and additives are the universal concern of recent days. Particularly, formalin is a chemical compound that is being commonly mingled with food for the preservation purpose. The recurrent ingesting of formalin contaminated food causes uncompromising health sicknesses like chronic cancer. Therefore, identification of formalin in food substances is an extreme need and day by day this need is growing as a general issue in the emerging terrains. In this article, a surface plasmon resonance (SPR) based sensor, comprised of graphene-PtSe2 combined layers associated with a ZnO nano-sheet is presented for the detection of formalin in liquid solution. The performance of the sensor has been analyzed through an analytical approach using MATLAB commercial software. Consequence due to incorporation of the Graphene-PtSe2 combined layer into the sensor structure along with ZnO layer has been studied. The observed sensitivity and quality factor are 155.33° RIU−1 and 88.89 RIU−1, respectively. This sensor senses the presence of formalin molecules by using attenuated total reflection (ATR) approach, assessing the reflectance vs SPR angle. It is found that the sensitivity of the conventional SPR based sensor is 128.33° RIU−1, whereas an improved sensitivity of 155.33° RIU−1 is obtained for this proposed amalgamated sensor structure. Later in time, a comparison of performance for different SPR sensor structures and the proposed sensor has been studied. Finally, another comparison study has been made with performance of the proposed sensor to other reported sensor in the literature. Surface plasmon resonance Formalin Numerical modeling Chitosan Sensitivity Quality factor Engineering (General). Civil engineering (General) Md. Rafiqul Islam verfasserin aut Imran Khan verfasserin aut In Sensing and Bio-Sensing Research Elsevier, 2016 32(2021), Seite 100419- (DE-627)826105408 (DE-600)2821969-7 22141804 nnns volume:32 year:2021 pages:100419- https://doi.org/10.1016/j.sbsr.2021.100419 kostenfrei https://doaj.org/article/2c5c045d78894198b1eeab83d19b5f99 kostenfrei http://www.sciencedirect.com/science/article/pii/S2214180421000246 kostenfrei https://doaj.org/toc/2214-1804 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 AR 32 2021 100419-
allfieldsSound	10.1016/j.sbsr.2021.100419 doi (DE-627)DOAJ057256594 (DE-599)DOAJ2c5c045d78894198b1eeab83d19b5f99 DE-627 ger DE-627 rakwb eng TA1-2040 Md. Moznuzzaman verfasserin aut Effect of layer thickness variation on sensitivity: An SPR based sensor for formalin detection 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Food preservatives and additives are the universal concern of recent days. Particularly, formalin is a chemical compound that is being commonly mingled with food for the preservation purpose. The recurrent ingesting of formalin contaminated food causes uncompromising health sicknesses like chronic cancer. Therefore, identification of formalin in food substances is an extreme need and day by day this need is growing as a general issue in the emerging terrains. In this article, a surface plasmon resonance (SPR) based sensor, comprised of graphene-PtSe2 combined layers associated with a ZnO nano-sheet is presented for the detection of formalin in liquid solution. The performance of the sensor has been analyzed through an analytical approach using MATLAB commercial software. Consequence due to incorporation of the Graphene-PtSe2 combined layer into the sensor structure along with ZnO layer has been studied. The observed sensitivity and quality factor are 155.33° RIU−1 and 88.89 RIU−1, respectively. This sensor senses the presence of formalin molecules by using attenuated total reflection (ATR) approach, assessing the reflectance vs SPR angle. It is found that the sensitivity of the conventional SPR based sensor is 128.33° RIU−1, whereas an improved sensitivity of 155.33° RIU−1 is obtained for this proposed amalgamated sensor structure. Later in time, a comparison of performance for different SPR sensor structures and the proposed sensor has been studied. Finally, another comparison study has been made with performance of the proposed sensor to other reported sensor in the literature. Surface plasmon resonance Formalin Numerical modeling Chitosan Sensitivity Quality factor Engineering (General). Civil engineering (General) Md. Rafiqul Islam verfasserin aut Imran Khan verfasserin aut In Sensing and Bio-Sensing Research Elsevier, 2016 32(2021), Seite 100419- (DE-627)826105408 (DE-600)2821969-7 22141804 nnns volume:32 year:2021 pages:100419- https://doi.org/10.1016/j.sbsr.2021.100419 kostenfrei https://doaj.org/article/2c5c045d78894198b1eeab83d19b5f99 kostenfrei http://www.sciencedirect.com/science/article/pii/S2214180421000246 kostenfrei https://doaj.org/toc/2214-1804 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 AR 32 2021 100419-
language	English
source	In Sensing and Bio-Sensing Research 32(2021), Seite 100419- volume:32 year:2021 pages:100419-
sourceStr	In Sensing and Bio-Sensing Research 32(2021), Seite 100419- volume:32 year:2021 pages:100419-
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institution	findex.gbv.de
topic_facet	Surface plasmon resonance Formalin Numerical modeling Chitosan Sensitivity Quality factor Engineering (General). Civil engineering (General)
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container_title	Sensing and Bio-Sensing Research
authorswithroles_txt_mv	Md. Moznuzzaman @@aut@@ Md. Rafiqul Islam @@aut@@ Imran Khan @@aut@@
publishDateDaySort_date	2021-01-01T00:00:00Z
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callnumber-first	T - Technology
author	Md. Moznuzzaman
spellingShingle	Md. Moznuzzaman misc TA1-2040 misc Surface plasmon resonance misc Formalin misc Numerical modeling misc Chitosan misc Sensitivity misc Quality factor misc Engineering (General). Civil engineering (General) Effect of layer thickness variation on sensitivity: An SPR based sensor for formalin detection
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topic_title	TA1-2040 Effect of layer thickness variation on sensitivity: An SPR based sensor for formalin detection Surface plasmon resonance Formalin Numerical modeling Chitosan Sensitivity Quality factor
topic	misc TA1-2040 misc Surface plasmon resonance misc Formalin misc Numerical modeling misc Chitosan misc Sensitivity misc Quality factor misc Engineering (General). Civil engineering (General)
topic_unstemmed	misc TA1-2040 misc Surface plasmon resonance misc Formalin misc Numerical modeling misc Chitosan misc Sensitivity misc Quality factor misc Engineering (General). Civil engineering (General)
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title	Effect of layer thickness variation on sensitivity: An SPR based sensor for formalin detection
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title_full	Effect of layer thickness variation on sensitivity: An SPR based sensor for formalin detection
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title_sort	effect of layer thickness variation on sensitivity: an spr based sensor for formalin detection
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title_auth	Effect of layer thickness variation on sensitivity: An SPR based sensor for formalin detection
abstract	Food preservatives and additives are the universal concern of recent days. Particularly, formalin is a chemical compound that is being commonly mingled with food for the preservation purpose. The recurrent ingesting of formalin contaminated food causes uncompromising health sicknesses like chronic cancer. Therefore, identification of formalin in food substances is an extreme need and day by day this need is growing as a general issue in the emerging terrains. In this article, a surface plasmon resonance (SPR) based sensor, comprised of graphene-PtSe2 combined layers associated with a ZnO nano-sheet is presented for the detection of formalin in liquid solution. The performance of the sensor has been analyzed through an analytical approach using MATLAB commercial software. Consequence due to incorporation of the Graphene-PtSe2 combined layer into the sensor structure along with ZnO layer has been studied. The observed sensitivity and quality factor are 155.33° RIU−1 and 88.89 RIU−1, respectively. This sensor senses the presence of formalin molecules by using attenuated total reflection (ATR) approach, assessing the reflectance vs SPR angle. It is found that the sensitivity of the conventional SPR based sensor is 128.33° RIU−1, whereas an improved sensitivity of 155.33° RIU−1 is obtained for this proposed amalgamated sensor structure. Later in time, a comparison of performance for different SPR sensor structures and the proposed sensor has been studied. Finally, another comparison study has been made with performance of the proposed sensor to other reported sensor in the literature.
abstractGer	Food preservatives and additives are the universal concern of recent days. Particularly, formalin is a chemical compound that is being commonly mingled with food for the preservation purpose. The recurrent ingesting of formalin contaminated food causes uncompromising health sicknesses like chronic cancer. Therefore, identification of formalin in food substances is an extreme need and day by day this need is growing as a general issue in the emerging terrains. In this article, a surface plasmon resonance (SPR) based sensor, comprised of graphene-PtSe2 combined layers associated with a ZnO nano-sheet is presented for the detection of formalin in liquid solution. The performance of the sensor has been analyzed through an analytical approach using MATLAB commercial software. Consequence due to incorporation of the Graphene-PtSe2 combined layer into the sensor structure along with ZnO layer has been studied. The observed sensitivity and quality factor are 155.33° RIU−1 and 88.89 RIU−1, respectively. This sensor senses the presence of formalin molecules by using attenuated total reflection (ATR) approach, assessing the reflectance vs SPR angle. It is found that the sensitivity of the conventional SPR based sensor is 128.33° RIU−1, whereas an improved sensitivity of 155.33° RIU−1 is obtained for this proposed amalgamated sensor structure. Later in time, a comparison of performance for different SPR sensor structures and the proposed sensor has been studied. Finally, another comparison study has been made with performance of the proposed sensor to other reported sensor in the literature.
abstract_unstemmed	Food preservatives and additives are the universal concern of recent days. Particularly, formalin is a chemical compound that is being commonly mingled with food for the preservation purpose. The recurrent ingesting of formalin contaminated food causes uncompromising health sicknesses like chronic cancer. Therefore, identification of formalin in food substances is an extreme need and day by day this need is growing as a general issue in the emerging terrains. In this article, a surface plasmon resonance (SPR) based sensor, comprised of graphene-PtSe2 combined layers associated with a ZnO nano-sheet is presented for the detection of formalin in liquid solution. The performance of the sensor has been analyzed through an analytical approach using MATLAB commercial software. Consequence due to incorporation of the Graphene-PtSe2 combined layer into the sensor structure along with ZnO layer has been studied. The observed sensitivity and quality factor are 155.33° RIU−1 and 88.89 RIU−1, respectively. This sensor senses the presence of formalin molecules by using attenuated total reflection (ATR) approach, assessing the reflectance vs SPR angle. It is found that the sensitivity of the conventional SPR based sensor is 128.33° RIU−1, whereas an improved sensitivity of 155.33° RIU−1 is obtained for this proposed amalgamated sensor structure. Later in time, a comparison of performance for different SPR sensor structures and the proposed sensor has been studied. Finally, another comparison study has been made with performance of the proposed sensor to other reported sensor in the literature.
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title_short	Effect of layer thickness variation on sensitivity: An SPR based sensor for formalin detection
url	https://doi.org/10.1016/j.sbsr.2021.100419 https://doaj.org/article/2c5c045d78894198b1eeab83d19b5f99 http://www.sciencedirect.com/science/article/pii/S2214180421000246 https://doaj.org/toc/2214-1804
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Particularly, formalin is a chemical compound that is being commonly mingled with food for the preservation purpose. The recurrent ingesting of formalin contaminated food causes uncompromising health sicknesses like chronic cancer. Therefore, identification of formalin in food substances is an extreme need and day by day this need is growing as a general issue in the emerging terrains. In this article, a surface plasmon resonance (SPR) based sensor, comprised of graphene-PtSe2 combined layers associated with a ZnO nano-sheet is presented for the detection of formalin in liquid solution. The performance of the sensor has been analyzed through an analytical approach using MATLAB commercial software. Consequence due to incorporation of the Graphene-PtSe2 combined layer into the sensor structure along with ZnO layer has been studied. The observed sensitivity and quality factor are 155.33° RIU−1 and 88.89 RIU−1, respectively. This sensor senses the presence of formalin molecules by using attenuated total reflection (ATR) approach, assessing the reflectance vs SPR angle. It is found that the sensitivity of the conventional SPR based sensor is 128.33° RIU−1, whereas an improved sensitivity of 155.33° RIU−1 is obtained for this proposed amalgamated sensor structure. Later in time, a comparison of performance for different SPR sensor structures and the proposed sensor has been studied. Finally, another comparison study has been made with performance of the proposed sensor to other reported sensor in the literature.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Surface plasmon resonance</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Formalin</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Numerical modeling</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Chitosan</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Sensitivity</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Quality factor</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">Engineering (General). Civil engineering (General)</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Md. Rafiqul Islam</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Imran Khan</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">In</subfield><subfield code="t">Sensing and Bio-Sensing Research</subfield><subfield code="d">Elsevier, 2016</subfield><subfield code="g">32(2021), Seite 100419-</subfield><subfield code="w">(DE-627)826105408</subfield><subfield code="w">(DE-600)2821969-7</subfield><subfield code="x">22141804</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:32</subfield><subfield code="g">year:2021</subfield><subfield code="g">pages:100419-</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.1016/j.sbsr.2021.100419</subfield><subfield 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Effect of layer thickness variation on sensitivity: An SPR based sensor for formalin detection

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