journal article·2025-05-23Open access

Shape-Induced Enhanced Raman Scattering (SIERS) Platforms Modified with Gold Nanorods for Ultradiluted Atrazine Pesticide Detection

Matheus Gomes Ferreira, Anerise de Barros, Flavio Makoto Shimizu, Fernando Aparecido Sigoli, Carlos César Bof Bufon, Italo Odone Mazali

ACS Applied Nano Materials· Volume 8· Issue 20

Abstract

High Resolution Image Download MS PowerPoint Slide Herein, we explored the shape-induced enhanced Raman scattering (SIERS) effect to detect Atrazine pesticides in different concentrations (1.6 × 10 –8 –1.6 × 10 –20 mol L –1 ). For this, the performance of the SIERS effect compared to the conventional Raman signal was evaluated using a silicon substrate with a V-shaped (Si–V) microchannel and a flat silicon substrate (flat Si). Experimental data free of metallic nanostructure show that the SIERS effect increases up to a 7-fold signal for the Atrazine molecule compared to the conventional Raman signal. Combining SIERS and surface-enhanced Raman scattering (SERS) effects (SIERS@SERS) using metallic nanostructures is the key feature used to achieve lower limit detection of the target molecule. The performance of SIERS@SERS was evaluated by using gold nanorods (AuNRs) metallic structure deposited onto Si–V and flat Si for the detection of Atrazine in different concentrations (1.6 × 10 –8 –1.6 × 10 –20 mol L –1 ). The geometric design of V-shaped microchannels also enables a “trap” for the molecule confinement and builds up an excellent electromagnetic field distribution by AuNR aggregates. The AuNRs aggregation is also favored by incubating a AuNRs colloidal suspension mixed with Atrazine using different solvents (water and methanol). In this sense, the results reveal that the solvent plays an important role in the signal intensity as well as spectra definition and band identification. The IDMAP statistical projection reveals good data discrimination with a silhouette coefficient of 0.64 for Si–V substrate (1.6 × 10 –8 –1.6 × 10 –20 mol L –1 ) against 0.51 for flat Si (1.6 × 10 –8 –1.6 × 10 –16 mol L –1 ), indicating that the SIERS@SERS effect provides more sensitivity for the sensor. The Si–V platforms are a robust option for commercial sensors, since they can be reusable with or without plasmonic nanostructures.
Source: openalex_inverted_index · Quality: baseline

Research context

OpenAlex topics: Gold and Silver Nanoparticles Synthesis and Applications · Advanced biosensing and bioanalysis techniques · Biosensors and Analytical Detection

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

Affiliations

Instituto de Química (IQ), Laboratório de Materiais Funcionais

Universidade Estadual de Campinas, UNICAMP

Instituto de Física Gleb Wataghin (IFGW), Departamento de Física Aplicada

Instituto de Geociências and Ciências Exatas (IGCE), Departamento de Física

Universidade Estadual Paulista “Julio de Mesquita Filho”, UNESP

Funding

Conselho Nacional de Desenvolvimento Cient?fico e Tecnol?gico · Funda??o de Amparo ? Pesquisa do Estado de S?o Paulo · Laborat?rio Nacional de Nanotecnologia · Coordena??o de Aperfei?oamento de Pessoal de N?vel Superior

References (36)

Show source-provided references
1. 10.1016/0009-2614(74)85388-110.1016/0009-2614(74)85388-1 ↗
2. 10.1021/acsnano.4c0147410.1021/acsnano.4c01474 ↗
3. 10.1021/acsnano.4c0267010.1021/acsnano.4c02670 ↗
4. 10.1021/acs.chemrev.2c0031610.1021/acs.chemrev.2c00316 ↗
5. 10.1039/D1TB01299A10.1039/D1TB01299A ↗
6. 10.1039/D1TC02134F10.1039/D1TC02134F ↗
7. Le Ru, E. C.; Etchegoing, P. Principles of Surface Enhanced Raman Spectroscopy and Related Plasmonic Effects; Elsevier: Amsterdam, 2009; pp 1–28.10.1016/B978-0-444-52779-0.00007-6 ↗
8. 10.1002/anie.20190815410.1002/anie.201908154 ↗
9. 10.1002/jrs.601410.1002/jrs.6014 ↗
10. 10.1080/10408347.2022.206368310.1080/10408347.2022.2063683 ↗
11. 10.1039/b904744a10.1039/b904744a ↗
12. 10.1039/b800340h10.1039/b800340h ↗
13. 10.1002/jrs.520310.1002/jrs.5203 ↗
14. 10.1016/j.talanta.2024.12664010.1016/j.talanta.2024.126640 ↗
15. 10.1039/D3CC04154A10.1039/D3CC04154A ↗
16. 10.1016/j.apsusc.2019.07.08010.1016/j.apsusc.2019.07.080 ↗
17. 10.1039/D0AN00999G10.1039/D0AN00999G ↗
18. 10.1109/JQE.2019.294683910.1109/JQE.2019.2946839 ↗
19. 10.1364/AO.38319810.1364/AO.383198 ↗
20. 10.1364/JOSAB.39497310.1364/JOSAB.394973 ↗
21. 10.1021/acsami.1c0848010.1021/acsami.1c08480 ↗
22. 10.1016/j.saa.2024.12390710.1016/j.saa.2024.123907 ↗
23. 10.1002/pssb.20084416310.1002/pssb.200844163 ↗
24. 10.1021/acsanm.0c0153010.1021/acsanm.0c01530 ↗
25. 10.1039/c0an00822b10.1039/c0an00822b ↗
26. 10.1109/TVCG.2020.303035410.1109/TVCG.2020.3030354 ↗
27. 10.1246/bcsj.2020035910.1246/bcsj.20200359 ↗
28. 10.1021/acs.jpclett.5b0212310.1021/acs.jpclett.5b02123 ↗
29. 10.1016/j.cossms.2009.06.00410.1016/j.cossms.2009.06.004 ↗
30. 10.1021/cg070394710.1021/cg0703947 ↗
31. 10.1039/D3CE01041D10.1039/D3CE01041D ↗
32. 10.1016/j.molliq.2023.12390810.1016/j.molliq.2023.123908 ↗
33. 10.1021/jp112021j10.1021/jp112021j ↗
34. 10.1007/s00396-014-3332-710.1007/s00396-014-3332-7 ↗
35. 10.1016/j.optmat.2022.11231010.1016/j.optmat.2022.112310 ↗
36. 10.1039/D0AN02215B10.1039/D0AN02215B ↗