journal article·2026Open access

Design and fabrication of plasmonic hedgehog-shaped covalent organic framework nanocomposites for indirect SERS-based ultradetection of water contaminant terbutryn

Tolga Zorlu, Maedeh Anisi, Monica Quarato, Ana Vieira, Jesús Giráldez-Martínez, Carlos Gonçalves, Aitor Alvarez, Tania Prieto, Dana D. Medina, Lucas V. Besteiro, Miguel A. Correa-Duarte, Begoña Espiña, Laura M. Salonen, Laura Rodriguez-Lorenzo

Nanoscale· Volume 18· Issue 16

Abstract

Surface-enhanced Raman scattering (SERS) spectroscopy is an ultrasensitive analytical technique, the efficiency of which can be enhanced by developing plasmonic nanostructured substrates and sieving elements to capture target analytes near the plasmonic surface. This study reports the development of a plasmonic hedgehog-shaped colloidal covalent organic framework (SiO2@Au@ COFHedgehog) composite as an efficient SERS substrate. First, hedgehog-shaped COF particles were synthesized, fully characterized, and their development was studied over time to gain insight into their formation. Then, SiO2@Au@COFHedgehog composite was prepared, retaining the characteristics of the crystalline COF and the hedgehog-type morphology. The composite exhibited significantly enhanced SERS intensity for 4-nitrothiophenol (4-NTP), which has a strong affinity for the Au surface via S-Au bond formation, achieving a limit of detection (LoD) of 10-10 M. This demonstrated that molecules with high affinity for the Au surface and smaller than the COF pore size (<3 nm) can diffuse easily through the pore. Furthermore, an indirect SERS strategy for the detection of the toxic herbicide terbutryn was designed based on the reduction of the nitro group in 4-NTP to form 4,4-dimercaptoazobenzene (DMAB). This process is attributed to the proximity of terbutryn to the 4-NTP-coated AuNPs, facilitated by the high adsorption efficiency of the porous anisotropic COF shell for this herbicide (>50%). A strong correlation was found between the SERS intensity ratios of specific peaks, achieving an impressive LoD of 10-9 M (220 ng L-1). Overall, these findings underscore the potential of plasmonic hedgehog-shaped COF composites as innovative nanomaterials for SERS-based detection, highlighting the exciting possibilities for developing sensitive and selective sensors for various target molecules, with implications in environmental analysis, biomedicine, and fields requiring ultrasensitive analytical techniques.
Source: europepmc · Quality: candidate unverified · Source record ↗

Research context

OpenAlex topics: Gold and Silver Nanoparticles Synthesis and Applications · Covalent Organic Framework Applications · Solar-Powered Water Purification Methods

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

Affiliations

Department of Physical and Inorganic Chemistry, Universitat Rovira i Virgili, Carrer de Marcel·lí Domingo s/n, 43007 Tarragona, Spain

CINBIO, University of Vigo, 36310 Vigo, Spain

International Iberian Nanotechnology Laboratory (INL), Avenida Mestre José Veiga, 4715-330 Braga, Portugal

Department of Chemistry and Center for Nanoscience (CeNS), Ludwig-Maximilians-University, Butenandtstraße 11 (E), 81377 Munich, Germany

Funding

Xunta de Galicia · European Commission · Agencia Estatal de Investigación · Fundação para a Ciência e a Tecnologia

References (83)

Show source-provided references
1. Vörösmarty · Nature · 2010 · 467 · 55510.1038/nature09440 ↗
2. Farhan Hanafi · Mater. Today Proc. · 2020 · 31 · 14110.1016/j.matpr.2021.01.258 ↗
3. Rojas · Chem. Rev. · 2020 · 120 · 837810.1021/acs.chemrev.9b00797 ↗
4. Langer · ACS Nano · 2020 · 14 · 2810.1021/acsnano.9b04224 ↗
5. Liu · J. Mater. Chem. B · 2021 · 9 · 837810.1039/D1TB01299A ↗
6. Ouyang · Rev. Anal. Chem. · 2017 · 36 · 2016002710.1515/revac-2016-0027 ↗
7. Zorlu · J. Chem. Phys. · 2023 · 158 · 17100110.1063/5.0144695 ↗
8. Carrillo-Carrión · Angew. Chem., Int. Ed. · 2019 · 58 · 707810.1002/anie.201902817 ↗
9. Haidar · Phys. Chem. Chem. Phys. · 2016 · 18 · 3227210.1039/C6CP06218K ↗
10. Lai · Sci. Rep. · 2017 · 7 · 544610.1038/s41598-017-05939-0 ↗
11. Mariño-Lopez · ChemNanoMat · 2019 · 5 · 4610.1002/cnma.201800355 ↗
12. Huang · Small · 2020 · 16 · 200480210.1002/smll.202004802 ↗
13. Qin · Biosensors · 2023 · 13 · 47910.3390/bios13040479 ↗
14. Zorlu · Angew. Chem., Int. Ed. · 2023 · 62 · e20230529910.1002/anie.202305299 ↗
15. Wang · Crit. Rev. Food Sci. Nutr. · 2024 · 64 · 47210.1080/10408398.2022.2106547 ↗
16. Zhou · Chem. Rev. · 2012 · 112 · 67310.1021/cr300014x ↗
17. Zheng · SmartMat · 2021 · 2 · 44610.1002/smm2.1047 ↗
18. Li · ACS Appl. Mater. Interfaces · 2020 · 12 · 326510.1021/acsami.9b20837 ↗
19. Wei · Appl. Catal., B · 2020 · 272 · 11903510.1016/j.apcatb.2020.119035 ↗
20. Song · Angew. Chem., Int. Ed. · 2023 · 62 · e20221672410.1002/anie.202216724 ↗
21. Xia · Adv. Mater. Interfaces · 2021 · 8 · 200150710.1002/admi.202001507 ↗
22. Fernandes · Chem. – Eur. J. · 2019 · 25 · 646110.1002/chem.201806025 ↗
23. Liu · ACS Nano · 2024 · 18 · 1123410.1021/acsnano.4c00208 ↗
24. Yang · Food Chem. · 2024 · 446 · 13884610.1016/j.foodchem.2024.138846 ↗
25. Evans · Faraday Discuss. · 2021 · 225 · 22610.1039/D0FD00054J ↗
26. Wei · J. Food Meas. Charact. · 2024 · 18 · 290310.1007/s11694-024-02368-2 ↗
27. Tan · Food Chem. · 2024 · 457 · 14016610.1016/j.foodchem.2024.140166 ↗
28. Huang · ACS Sens. · 2024 · 9 · 242110.1021/acssensors.4c00103 ↗
29. Kandambeth · Nat. Commun. · 2015 · 6 · 678610.1038/ncomms7786 ↗
30. Smith · ACS Cent. Sci. · 2017 · 3 · 5810.1021/acscentsci.6b00331 ↗
31. Li · Chem. Sci. · 2019 · 10 · 379610.1039/C9SC00289H ↗
32. Zhao · J. Am. Chem. Soc. · 2017 · 139 · 1316610.1021/jacs.7b07457 ↗
33. Bahng · Nature · 2015 · 517 · 59610.1038/nature14092 ↗
34. Montjoy · J. Am. Chem. Soc. · 2018 · 140 · 783510.1021/jacs.8b02666 ↗
35. Das · ACS Appl. Nano Mater. · 2022 · 5 · 1374510.1021/acsanm.2c00746 ↗
36. Kim · Adv. Funct. Mater. · 2017 · 27 · 170092510.1002/adfm.201700925 ↗
37. Wen · Microporous Mesoporous Mater. · 2023 · 357 · 11262410.1016/j.micromeso.2023.112624 ↗
38. Deng · Mater. Today Chem. · 2022 · 26 · 10102710.1016/j.mtchem.2022.101027 ↗
39. Chen · Nat. Commun. · 2021 · 12 · 455610.1038/s41467-021-24838-7 ↗
40. Xu · Nat. Chem. · 2015 · 7 · 90510.1038/nchem.2352 ↗
41. Zhang · Talanta · 2018 · 188 · 57810.1016/j.talanta.2018.06.032 ↗
42. Chu · Colloids Surf., A · 2022 · 648 · 12923810.1016/j.colsurfa.2022.129238 ↗
43. Fang · Proc. Natl. Acad. Sci. U. S. A. · 2023 · 120 · e220867612010.1073/pnas.2208676120 ↗
44. Rotter · Chem. Mater. · 2019 · 31 · 1000810.1021/acs.chemmater.9b02286 ↗
45. Traxler · Chem. Sci. · 2024 · 15 · 754510.1039/D4SC01128G ↗
46. Ma · J. Am. Chem. Soc. · 2019 · 141 · 1827110.1021/jacs.9b09189 ↗
47. Gruber · Nature · 2024 · 630 · 87210.1038/s41586-024-07483-0 ↗
48. Deng · J. Am. Chem. Soc. · 2024 · 146 · 3542710.1021/jacs.4c14535 ↗
49. Li · J. Am. Chem. Soc. · 2025 · 147 · 2695510.1021/jacs.5c09081 ↗
50. Elewa · J. Mater. Chem. A · 2022 · 10 · 1237810.1039/D2TA00328G ↗
51. Bagheri · J. Mater. Sci. · 2021 · 56 · 111610.1007/s10853-020-05308-9 ↗
52. Ma · J. Am. Chem. Soc. · 2019 · 141 · 1827110.1021/jacs.9b09189 ↗
53. Smith · Chem. Commun. · 2016 · 52 · 369010.1039/C5CC10221A ↗
54. Lu · Chem. Eng. J. · 2024 · 499 · 15630810.1016/j.cej.2024.156308 ↗
55. Zorlu · ACS Nanosci. Au · 2023 · 3 · 22210.1021/acsnanoscienceau.2c00063 ↗
56. Lupa · Colloid Interface Sci. Commun. · 2019 · 33 · 10021910.1016/j.colcom.2019.100219 ↗
57. Li · Chem. Commun. · 2017 · 53 · 251110.1039/C6CC10188G ↗
58. Romero · Nanoscale · 2019 · 11 · 607210.1039/C9NR00388F ↗
59. Romero · CrystEngComm · 2023 · 25 · 245610.1039/D3CE00178D ↗
60. Yang · Anal. Chim. Acta · 2022 · 1218 · 34000010.1016/j.aca.2022.340000 ↗
61. Wang · ACS Appl. Mater. Interfaces · 2016 · 8 · 1559110.1021/acsami.6b02905 ↗
62. Chen · Anal. Chem. · 2022 · 94 · 1467510.1021/acs.analchem.2c02961 ↗
63. Innocenzi · TrAC, Trends Anal. Chem. · 2019 · 114 · 23310.1016/j.trac.2019.02.031 ↗
64. Lv · ACS Sens. · 2025 · 10 · 177810.1021/acssensors.4c02391 ↗
65. Quynh · J. Electron. Mater. · 2016 · 45 · 256310.1007/s11664-016-4421-9 ↗
66. Zheng · Small · 2016 · 12 · 393510.1002/smll.201600947 ↗
67. Gumilar · J. Mater. Chem. A · 2022 · 10 · 666210.1039/D1TA08741J ↗
68. Negrín-Montecelo · ACS Photonics · 2023 · 10 · 331010.1021/acsphotonics.3c00733 ↗
69. Stiles · Annu. Rev. Anal. Chem. · 2008 · 1 · 60110.1146/annurev.anchem.1.031207.112814 ↗
70. Förstner · J. Soils Sediments · 2009 · 9 · 8910.1007/s11368-009-0066-0 ↗
71. Min · Sci. Total Environ. · 2023 · 893 · 16483910.1016/j.scitotenv.2023.164839 ↗
72. Fernández-Calviño · Soil Biol. Biochem. · 2021 · 154 · 10813010.1016/j.soilbio.2021.108130 ↗
73. Xing · J. Appl. Phycol. · 2023 · 35 · 166310.1007/s10811-023-02991-4 ↗
74. Brix · J. Mass Spectrom. · 2009 · 44 · 33010.1002/jms.1509 ↗
75. Chatzipetrou · Electrochem. Commun. · 2016 · 64 · 4610.1016/j.elecom.2016.01.008 ↗
76. Booij · Environ. Sci. Technol. · 2014 · 48 · 800310.1021/es405428t ↗
77. Jang · Food Sci. Biotechnol. · 2018 · 27 · 152510.1007/s10068-018-0355-8 ↗
78. Montoya · Chem. Commun. · 2012 · 48 · 476710.1039/c2cc30730h ↗
79. Xie · J. Am. Chem. Soc. · 2013 · 135 · 165710.1021/ja309074a ↗
80. Junginger · Chemosphere · 2022 · 305 · 13532910.1016/j.chemosphere.2022.135329 ↗
81. Tang · J. Food Compos. Anal. · 2023 · 123 · 10563810.1016/j.jfca.2023.105638 ↗
82. Ramadan · Water, Air, Soil Pollut. · 2024 · 235 · 53710.1007/s11270-024-07342-8 ↗
83. Jang · Food Sci. Biotechnol. · 2018 · 27 · 152510.1007/s10068-018-0355-8 ↗