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Silica and graphene mediate arsenic detection in mature rice grain by a newly patterned current–volt aptasensor
Arsenic is a major global threat to the ecosystem. Here we describe a highly accurate sensing platform using silica nanoparticles/graphene at the surface of aluminum interdigitated electrodes (Al IDE), able to detect trace amounts of arsenic(III) in rice grain samples. The morphology and electrical...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8289824/ https://www.ncbi.nlm.nih.gov/pubmed/34282233 http://dx.doi.org/10.1038/s41598-021-94145-0 |
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author | Uda, M. N. A. Gopinath, Subash C. B. Hashim, Uda Halim, N. H. Parmin, N. A. Uda, M. N. Afnan Adam, Tijjani Anbu, Periasamy |
author_facet | Uda, M. N. A. Gopinath, Subash C. B. Hashim, Uda Halim, N. H. Parmin, N. A. Uda, M. N. Afnan Adam, Tijjani Anbu, Periasamy |
author_sort | Uda, M. N. A. |
collection | PubMed |
description | Arsenic is a major global threat to the ecosystem. Here we describe a highly accurate sensing platform using silica nanoparticles/graphene at the surface of aluminum interdigitated electrodes (Al IDE), able to detect trace amounts of arsenic(III) in rice grain samples. The morphology and electrical properties of fabricated Al IDEs were characterized and standardized using AFM, and SEM with EDX analyses. Micrometer scale Al IDEs were fabricated with silicon, aluminum, and oxygen as primary elements. Validation of the bare Al IDE with electrolyte fouling was performed at different pH levels. The sensing surface was stable with no electrolyte fouling at pH 7. Each chemical modification step was monitored with current–volt measurement. The surface chemical bonds were characterized by fourier transform infrared spectroscopy (FTIR) and revealed different peaks when interacting with arsenic (1600–1000 cm(−1)). Both silica nanoparticles and graphene presented a sensitive limit of detection as measured by slope calibration curves at 0.0000001 pg/ml, respectively. Further, linear regression was established using ΔI (A) = 3.86 E(−09) log (Arsenic concentration) [g/ml] + 8.67 E(−08) [A] for silica nanoparticles, whereas for graphene Y = 3.73 E(−09) (Arsenic concentration) [g/ml] + 8.52 E(−08) on the linear range of 0.0000001 pg/ml to 0.01 pg/ml. The R(2) for silica (0.96) and that of graphene (0.94) was close to the maximum (1). Modification with silica nanoparticles was highly stable. The potential use of silica nanoparticles in the detection of arsenic in rice grain extract can be attributed to their size and stability. |
format | Online Article Text |
id | pubmed-8289824 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-82898242021-07-21 Silica and graphene mediate arsenic detection in mature rice grain by a newly patterned current–volt aptasensor Uda, M. N. A. Gopinath, Subash C. B. Hashim, Uda Halim, N. H. Parmin, N. A. Uda, M. N. Afnan Adam, Tijjani Anbu, Periasamy Sci Rep Article Arsenic is a major global threat to the ecosystem. Here we describe a highly accurate sensing platform using silica nanoparticles/graphene at the surface of aluminum interdigitated electrodes (Al IDE), able to detect trace amounts of arsenic(III) in rice grain samples. The morphology and electrical properties of fabricated Al IDEs were characterized and standardized using AFM, and SEM with EDX analyses. Micrometer scale Al IDEs were fabricated with silicon, aluminum, and oxygen as primary elements. Validation of the bare Al IDE with electrolyte fouling was performed at different pH levels. The sensing surface was stable with no electrolyte fouling at pH 7. Each chemical modification step was monitored with current–volt measurement. The surface chemical bonds were characterized by fourier transform infrared spectroscopy (FTIR) and revealed different peaks when interacting with arsenic (1600–1000 cm(−1)). Both silica nanoparticles and graphene presented a sensitive limit of detection as measured by slope calibration curves at 0.0000001 pg/ml, respectively. Further, linear regression was established using ΔI (A) = 3.86 E(−09) log (Arsenic concentration) [g/ml] + 8.67 E(−08) [A] for silica nanoparticles, whereas for graphene Y = 3.73 E(−09) (Arsenic concentration) [g/ml] + 8.52 E(−08) on the linear range of 0.0000001 pg/ml to 0.01 pg/ml. The R(2) for silica (0.96) and that of graphene (0.94) was close to the maximum (1). Modification with silica nanoparticles was highly stable. The potential use of silica nanoparticles in the detection of arsenic in rice grain extract can be attributed to their size and stability. Nature Publishing Group UK 2021-07-19 /pmc/articles/PMC8289824/ /pubmed/34282233 http://dx.doi.org/10.1038/s41598-021-94145-0 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Uda, M. N. A. Gopinath, Subash C. B. Hashim, Uda Halim, N. H. Parmin, N. A. Uda, M. N. Afnan Adam, Tijjani Anbu, Periasamy Silica and graphene mediate arsenic detection in mature rice grain by a newly patterned current–volt aptasensor |
title | Silica and graphene mediate arsenic detection in mature rice grain by a newly patterned current–volt aptasensor |
title_full | Silica and graphene mediate arsenic detection in mature rice grain by a newly patterned current–volt aptasensor |
title_fullStr | Silica and graphene mediate arsenic detection in mature rice grain by a newly patterned current–volt aptasensor |
title_full_unstemmed | Silica and graphene mediate arsenic detection in mature rice grain by a newly patterned current–volt aptasensor |
title_short | Silica and graphene mediate arsenic detection in mature rice grain by a newly patterned current–volt aptasensor |
title_sort | silica and graphene mediate arsenic detection in mature rice grain by a newly patterned current–volt aptasensor |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8289824/ https://www.ncbi.nlm.nih.gov/pubmed/34282233 http://dx.doi.org/10.1038/s41598-021-94145-0 |
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