journal article·2024-05-15

Microwave-Enabled Fast Preparation of a Metal–Organic Framework Hybrid Membrane for Filtration-Enhanced Simultaneous Separation and Detection of Aflatoxin B1

Tongtong Ma, Qi Zhang, Lei Yuan, Zhishang Li, Lin Zhang, Jie Zhang, Shugang Yan, Xiahong Xu, Yibin Ying, Yingchun Fu

ACS Applied Materials & Interfaces· Volume 16· Issue 19
Publisher page

Abstract

Mycotoxin contamination in food and the environment seriously harms human health. Sensitive and timely detection of mycotoxins is crucial. Here, we report a dual-functional hybrid membrane with absorptivity and responsiveness for fluorescent-quantitative detection of mycotoxin aflatoxin B 1 (AFB 1 ). A biomineralization-inspired and microwave-accelerated fabrication method was established to prepare a hybrid membrane with a metal–organic framework (MOF) loaded in high density. The MOF presented high efficiency in capturing AFB 1 and showed fluorescence intensity alteration simultaneously, enabling a dual adsorption–response mode. Deriving from the inherent porous structure of the hybrid membrane and the absorptive/responsive ability of the loaded MOF, a filtration-enhanced detection mode was elaborated to provide a 1.67-fold signal increase compared with the conventional soaking method. Therefore, the hybrid membrane exhibited a rapid response time of 10 min and a low detection limit of 0.757 ng mL –1, superior to most analogues in rapidity and sensitivity. The hybrid membrane also presented superior specificity, reproducibility, and anti-interference ability and even performed well in extreme environments such as strong acid or alkaline, satisfying the practical requirements for facile and in-field detection. Therefore, the membrane had strong applicability in chicken feed samples, with a detection recovery between 70.6% and 101%. The hybrid membrane should have significant prospects in the rapid and in-field inspection of mycotoxins for agriculture and food.
Source: openalex_inverted_index · Quality: baseline

Research context

OpenAlex topics: Advanced biosensing and bioanalysis techniques · Analytical chemistry methods development · Carbon and Quantum Dots Applications

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

Affiliations

Key Laboratory of Intelligent Equipment and Robotics for Agriculture of Zhejiang Province, College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou 310058, China

State Key Laboratory for Managing Biotic and Chemical Threats to the Quality and Safety of Agro-products, Institute of Agro-product Safety and Nutrition, Zhejiang Academy of Agricultural Sciences, Hangzhou 310021, China

Funding

Key Research and Development Program of Zhejiang Province

References (45)

Show source-provided references
1. 10.1021/acsnano.0c1081710.1021/acsnano.0c10817 ↗
2. 10.1016/j.foodchem.2022.13213910.1016/j.foodchem.2022.132139 ↗
3. 10.1016/j.jcis.2023.12.11810.1016/j.jcis.2023.12.118 ↗
4. 10.1016/j.foodchem.2020.12785710.1016/j.foodchem.2020.127857 ↗
5. 10.1039/D1TB00222H10.1039/D1TB00222H ↗
6. 10.1016/j.bios.2022.11405710.1016/j.bios.2022.114057 ↗
7. 10.1021/acs.jafc.0c0651310.1021/acs.jafc.0c06513 ↗
8. 10.1016/j.jcis.2024.01.17710.1016/j.jcis.2024.01.177 ↗
9. 10.1016/j.foodchem.2020.12794510.1016/j.foodchem.2020.127945 ↗
10. 10.1021/acsomega.7b0153610.1021/acsomega.7b01536 ↗
11. 10.1002/adma.20200544810.1002/adma.202005448 ↗
12. 10.1016/j.foodcont.2019.10701110.1016/j.foodcont.2019.107011 ↗
13. 10.1016/j.eng.2022.07.02210.1016/j.eng.2022.07.022 ↗
14. 10.1016/j.jcis.2024.01.19610.1016/j.jcis.2024.01.196 ↗
15. 10.1016/j.eng.2022.02.01710.1016/j.eng.2022.02.017 ↗
16. 10.1021/jacs.0c0218110.1021/jacs.0c02181 ↗
17. 10.1021/acsnano.2c0252010.1021/acsnano.2c02520 ↗
18. 10.1021/acs.nanolett.0c0376210.1021/acs.nanolett.0c03762 ↗
19. 10.1002/anie.20110127410.1002/anie.201101274 ↗
20. 10.1126/sciadv.abl965310.1126/sciadv.abl9653 ↗
21. 10.1016/j.cej.2021.13295610.1016/j.cej.2021.132956 ↗
22. 10.1002/adfm.20090234710.1002/adfm.200902347 ↗
23. 10.1039/C4CC08796H10.1039/C4CC08796H ↗
24. 10.1021/acsami.9b2224210.1021/acsami.9b22242 ↗
25. 10.1039/C8RA07804A10.1039/C8RA07804A ↗
26. 10.1016/j.cej.2020.12517410.1016/j.cej.2020.125174 ↗
27. 10.1016/0032-3861(96)85356-010.1016/0032-3861(96)85356-0 ↗
28. 10.1016/j.cej.2020.12826810.1016/j.cej.2020.128268 ↗
29. 10.1021/acsbiomaterials.0c0003510.1021/acsbiomaterials.0c00035 ↗
30. 10.1002/(SICI)1099-0488(20000201)38:3<369::AID-POLB3>3.0.CO;2-W10.1002/(SICI)1099-0488(20000201)38:3<369::AID-POLB3>3.0.CO;2-W ↗
31. 10.1016/0032-3861(93)90861-410.1016/0032-3861(93)90861-4 ↗
32. 10.1021/ma950954n10.1021/ma950954n ↗
33. 10.1016/j.jhazmat.2021.12517010.1016/j.jhazmat.2021.125170 ↗
34. 10.1016/j.jhazmat.2022.12942510.1016/j.jhazmat.2022.129425 ↗
35. 10.1016/j.jece.2020.10496610.1016/j.jece.2020.104966 ↗
36. 10.1016/j.seppur.2023.12537110.1016/j.seppur.2023.125371 ↗
37. 10.1016/j.desal.2017.12.04210.1016/j.desal.2017.12.042 ↗
38. 10.1016/j.foodchem.2022.13238910.1016/j.foodchem.2022.132389 ↗
39. 10.1016/j.mimet.2022.10641410.1016/j.mimet.2022.106414 ↗
40. 10.1016/j.microc.2021.10684710.1016/j.microc.2021.106847 ↗
41. 10.1016/j.snb.2021.13056110.1016/j.snb.2021.130561 ↗
42. 10.1021/jacs.5b1030810.1021/jacs.5b10308 ↗
43. 10.1016/j.aca.2023.34184410.1016/j.aca.2023.341844 ↗
44. 10.1016/j.snb.2023.13451610.1016/j.snb.2023.134516 ↗
45. 10.1080/09583157.2023.220561610.1080/09583157.2023.2205616 ↗