journal article·2022-06

Recent Advances in the Applications of Carbon Nanostructures on Optical Sensing of Emerging Aquatic Pollutants

Arushi Gupta, Anu Kumari, Neha Kaushal, Anas Saifi, Girish Mohanta, Abhay Sachdev, Kamlesh Kumar, Akash Deep, Avishek Saha

ChemNanoMat· Volume 8· Issue 6
Publisher page

Abstract

Abstract In recent years, optical sensing based on nanomaterials has emerged as a prospective strategy for monitoring environmental pollution in water. In this context, carbon nanostructures have received increasing attention due to their unique optoelectronic and physiochemical properties. To this end, nanocarbon such as carbon nanotubes, graphene, and carbon dots have been used to develop proof‐of‐concept opto‐chemical sensors for emerging aquatic contaminants, including pesticides, bacterial pathogens, and pharmaceuticals residues. These optical sensors have attracted significant research interest in nanotechnology, material science, and the detection of aquatic pollutants. However, the practical application for detecting contaminants is still limited because of cost‐effectiveness, sensitivities, and selectivity toward the diverse pollutants. This review examines the current trends and challenges in designing and applying carbon nanostructure‐based optical sensors for detecting aquatic contaminants. Finally, a critical perspective on the field and future research directions is provided.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: Carbon and Quantum Dots Applications · Electrochemical sensors and biosensors · Advanced biosensing and bioanalysis techniques

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

CSIR-Central Scientific Instruments Organisation (CSIR-CSIO), Sector 30 C Chandigarh 160030 India

Academy of Scientific and Innovative Research (AcSIR) Ghaziabad 201002 India

Funding

Science and Engineering Research Board

References (100+)

Show source-provided references
1. Calvo-Flores F. G. · 2018 · 710.1002/9783527691203 ↗
2.
3. 10.1016/j.trac.2008.08.01110.1016/j.trac.2008.08.011 ↗
4. 10.1016/j.talanta.2019.03.12010.1016/j.talanta.2019.03.120 ↗
5. 10.1016/j.chroma.2020.46109010.1016/j.chroma.2020.461090 ↗
6.
7. 10.1021/acssensors.8b0023910.1021/acssensors.8b00239 ↗
8. 10.1021/acs.iecr.0c0495210.1021/acs.iecr.0c04952 ↗
9. 10.1021/acssensors.9b0037610.1021/acssensors.9b00376 ↗
10. 10.1016/j.trac.2017.10.01210.1016/j.trac.2017.10.012 ↗
11. 10.1007/s10311-021-01241-810.1007/s10311-021-01241-8 ↗
12. 10.1016/j.trac.2021.11634410.1016/j.trac.2021.116344 ↗
13. 10.1016/j.snb.2016.06.08110.1016/j.snb.2016.06.081 ↗
14.
15. 10.3390/s13101392810.3390/s131013928 ↗
16. 10.1021/acsami.0c1431210.1021/acsami.0c14312 ↗
17. 10.1021/cr500304f10.1021/cr500304f ↗
18.
19. 10.1016/j.trac.2019.01.00810.1016/j.trac.2019.01.008 ↗
20. 10.1016/j.foodchem.2018.08.11010.1016/j.foodchem.2018.08.110 ↗
21. 10.1016/j.trac.2019.03.02110.1016/j.trac.2019.03.021 ↗
22.
23. 10.1021/nl400176b10.1021/nl400176b ↗
24. 10.1002/anie.20130774010.1002/anie.201307740 ↗
25. 10.1002/ange.20130774010.1002/ange.201307740 ↗
26. 10.1016/j.carbon.2014.10.01710.1016/j.carbon.2014.10.017 ↗
27. 10.1021/acsami.7b0706310.1021/acsami.7b07063 ↗
28. 10.3389/fchem.2021.61516410.3389/fchem.2021.615164 ↗
29. 10.1016/S0379-6779(98)00278-110.1016/S0379-6779(98)00278-1 ↗
30. 10.1021/nl904286r10.1021/nl904286r ↗
31. 10.1126/science.107263110.1126/science.1072631 ↗
32. 10.1103/PhysRevLett.92.17740110.1103/PhysRevLett.92.177401 ↗
33. 10.1016/j.chempr.2016.09.00110.1016/j.chempr.2016.09.001 ↗
34. Bakry R. · Int. J. Nanomed. · 2007 · 2 · 639
35. 10.1016/j.snb.2019.12748310.1016/j.snb.2019.127483 ↗
36.
37. 10.1021/ac801034p10.1021/ac801034p ↗
38. 10.3390/s13121589810.3390/s131215898 ↗
39.
40. 10.1021/ja040082h10.1021/ja040082h ↗
41. 10.1039/C5CC07754K10.1039/C5CC07754K ↗
42. 10.1039/C8NR10059D10.1039/C8NR10059D ↗
43.
44. 10.1039/C8NR03602K10.1039/C8NR03602K ↗
45. 10.1016/j.nantod.2016.12.00610.1016/j.nantod.2016.12.006 ↗
46. Langer M. · Appl. Mater. Res. · 2021 · 22
47.
48. 10.1016/j.jhazmat.2019.12164310.1016/j.jhazmat.2019.121643 ↗
49. 10.1016/j.cej.2020.12684810.1016/j.cej.2020.126848 ↗
50. 10.37256/nat.112020124.1-1210.37256/nat.112020124.1-12 ↗
51. 10.1038/s41467-017-01463-x10.1038/s41467-017-01463-x ↗
52. 10.1126/science.107823910.1126/science.1078239 ↗
53. 10.1016/j.cossms.2016.08.00110.1016/j.cossms.2016.08.001 ↗
54.
55. 10.1016/j.diamond.2013.05.00610.1016/j.diamond.2013.05.006 ↗
56. 10.1007/s00216-015-8849-110.1007/s00216-015-8849-1 ↗
57. 10.1021/ja056708110.1021/ja0567081 ↗
58. 10.1039/C7QM00241F10.1039/C7QM00241F ↗
59.
60. 10.1016/j.jhazmat.2019.12151610.1016/j.jhazmat.2019.121516 ↗
61. 10.1021/acsami.9b0291110.1021/acsami.9b02911 ↗
62.
63. 10.2174/092986732566618100415224710.2174/0929867325666181004152247 ↗
64. 10.1002/adma.20180504310.1002/adma.201805043 ↗
65. 10.1016/j.bios.2019.11132410.1016/j.bios.2019.111324 ↗
66. 10.3390/photonics805015510.3390/photonics8050155 ↗
67. 10.3390/ma1212192810.3390/ma12121928 ↗
68.
69. 10.1007/s11082-014-9976-110.1007/s11082-014-9976-1 ↗
70. 10.1038/s41598-020-59388-310.1038/s41598-020-59388-3 ↗
71. 10.1021/acssensors.6b0021110.1021/acssensors.6b00211 ↗
72. 10.1021/acsami.0c1094310.1021/acsami.0c10943 ↗
73.
74. 10.1021/acsami.5b0019910.1021/acsami.5b00199 ↗
75. 10.1039/C7RA10710B10.1039/C7RA10710B ↗
76.
77. 10.1016/j.snb.2014.09.03810.1016/j.snb.2014.09.038 ↗
78. 10.1016/j.trac.2020.11594310.1016/j.trac.2020.115943 ↗
79.
80. 10.1002/chem.20170343810.1002/chem.201703438 ↗
81. 10.3390/bios1102004310.3390/bios11020043 ↗
82. 10.1016/j.aca.2004.08.07710.1016/j.aca.2004.08.077 ↗
83. 10.1155/2019/429307310.1155/2019/4293073 ↗
84. 10.1021/acsami.9b2045810.1021/acsami.9b20458 ↗
85. 10.1021/acs.analchem.9b0491710.1021/acs.analchem.9b04917 ↗
86. 10.1016/j.envpol.2014.01.01510.1016/j.envpol.2014.01.015 ↗
87. 10.1038/s41545-020-00087-x10.1038/s41545-020-00087-x ↗
88. 10.1016/j.cej.2019.12233410.1016/j.cej.2019.122334 ↗
89. 10.1021/es011055j10.1021/es011055j ↗
90. 10.1021/acs.chemrev.9b0079710.1021/acs.chemrev.9b00797 ↗
91. 10.1016/j.jenvman.2017.12.08310.1016/j.jenvman.2017.12.083 ↗
92. 10.1038/s41598-018-31706-w10.1038/s41598-018-31706-w ↗
93. 10.1021/acs.est.7b0338010.1021/acs.est.7b03380 ↗
94. 10.1016/B978-012373944-5.00183-810.1016/B978-012373944-5.00183-8 ↗
95. W. H. Organization WHO estimates of the global burden of foodborne diseases: foodborne disease burden epidemiology reference group 2007–2015 World Health Organization 2015 p. 72.
96. 10.3390/foods204058510.3390/foods2040585 ↗
97.
98. 10.1021/acsestwater.1c0014610.1021/acsestwater.1c00146 ↗
99. 10.1016/j.trac.2020.11612510.1016/j.trac.2020.116125 ↗
100. 10.1021/acsnano.1c0709410.1021/acsnano.1c07094 ↗