Co Nanoparticles Embedded in 2D N-Doped Porous Carbon Nanosheets for Evaluating Acetylcholinesterase Activity
Source abstract
Abstract
Here, we reported a facile strategy to prepare Co nanoparticles (NPs) encapsulated in two-dimensional (2D) N-doped porous carbon nanosheets (2D Co/NC) via pyrolyzing Zn/Co bimetallic metal–organic framework (MOF) nanosheets, which were prepared in aqueous solution. The successful synthesis of Zn/Co bimetallic MOF nanosheets and 2D Co/NC was demonstrated by various characterization techniques. The optimized 2D Co0.6/NC-700 and three-dimensional (3D) Co0.6/NC-700 show catalase- and oxidase-like activities. They can break down H2O2 into O2 and oxidize 3,3′,5,5′-tetramethylbenzidine (TMB) to a blue product, while the former displays superior performance to its 3D Co0.6/NC-700 aggregated nanoparticles. Specifically, the oxidase-mimicking activity and catalase-like activity of 2D Co0.6/NC-700 are 1.64-fold and 6.9-fold those of 3D Co0.6/NC-700, respectively. Relative to 3D Co0.6/NC-700 aggregates, the improvement of the catalytic activity of 2D Co0.6/NC-700 is likely ascribed to its 2D leaf-like structure with more accessible dispersed active sites and the interaction between Co NPs and N-doped carbon nanosheets. 2D Co0.6/NC-700 displayed superior oxidase-like activity with a low Michaelis–Menten constant (Km) of 0.35 mM. Interestingly, in the presence of both acetylcholinesterase (AChE) and acetylthiocholine (ATCh), the oxidase-like activity was suppressed because of the generation of thiocholine, which led to the fading of the TMB color reaction. On this basis, a colorimetric assay was developed for the determination of AChE activity. 2D Co0.6/NC-700 displayed excellent detection performance in AChE activity, with a linear detection range of 0.0002–0.8 U L–1 and a low detection limit of 0.0002 U L–1. Remarkably, the method showed good selectivity to AChE, and other coexisting substances had minor interference. The method was satisfactorily utilized to determine the AChE activity in real samples.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Advanced Nanomaterials in Catalysis · Electrochemical sensors and biosensors · Carbon and Quantum Dots Applications
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Key Laboratory of Luminescence Analysis and Molecular Sensing (Southwest University), Ministry of Education, College of Chemistry and Chemical Engineering, Southwest University, Chongqing 400715, China
The Key Laboratory of Chongqing Inorganic Special Functional Materials, College of Chemistry and Chemical Engineering, Yangtze Normal University, Chongqing 408100, China
Funding
Key Laboratory of Chongqing Inorganic Special Functional Materials
References (61)
Show source-provided references
1. 10.1021/acs.accounts.9b0014010.1021/acs.accounts.9b00140 ↗
2. 10.1038/nnano.2007.26010.1038/nnano.2007.260 ↗
3. 10.1021/acsami.7b1794510.1021/acsami.7b17945 ↗
4. 10.1002/adfm.20200193310.1002/adfm.202001933 ↗
5. 10.1021/acs.analchem.0c0525710.1021/acs.analchem.0c05257 ↗
6. 10.1016/j.bios.2020.11270710.1016/j.bios.2020.112707 ↗
7. 10.1016/j.snb.2018.12.13710.1016/j.snb.2018.12.137 ↗
8. 10.1021/acs.analchem.0c0298210.1021/acs.analchem.0c02982 ↗
9. 10.1021/acsanm.0c0311810.1021/acsanm.0c03118 ↗
10. 10.1021/acs.accounts.0c0026810.1021/acs.accounts.0c00268 ↗
11. 10.1021/cr300014x10.1021/cr300014x ↗
12. 10.1016/j.trac.2018.06.00110.1016/j.trac.2018.06.001 ↗
13. 10.1021/acs.chemmater.8b0334810.1021/acs.chemmater.8b03348 ↗
14. 10.1021/acsnano.8b0950110.1021/acsnano.8b09501 ↗
15. 10.1002/anie.20201071410.1002/anie.202010714 ↗
16. 10.1021/acsanm.1c0057410.1021/acsanm.1c00574 ↗
17. 10.1039/C8CS00457A10.1039/C8CS00457A ↗
18. 10.1016/j.apcatb.2019.11853110.1016/j.apcatb.2019.118531 ↗
19. 10.1016/j.cej.2019.12245610.1016/j.cej.2019.122456 ↗
20. 10.1016/j.jhazmat.2019.12106410.1016/j.jhazmat.2019.121064 ↗
21. 10.1038/s41598-019-50780-210.1038/s41598-019-50780-2 ↗
22. 10.1016/j.jcis.2019.10.00710.1016/j.jcis.2019.10.007 ↗
23. 10.1016/j.bios.2019.04.06110.1016/j.bios.2019.04.061 ↗
24. 10.1002/adma.20170010210.1002/adma.201700102 ↗
25. 10.1039/C8CS00268A10.1039/C8CS00268A ↗
26. 10.1039/C9TB02542A10.1039/C9TB02542A ↗
27. 10.1021/acs.analchem.9b0332110.1021/acs.analchem.9b03321 ↗
28. 10.1021/acscatal.0c0249010.1021/acscatal.0c02490 ↗
29. 10.1039/C9NH00095J10.1039/C9NH00095J ↗
30. 10.1039/c3cc44342f10.1039/c3cc44342f ↗
31. 10.1038/ncomms626110.1038/ncomms6261 ↗
32. 10.1002/anie.20181399410.1002/anie.201813994 ↗
33. 10.1002/ange.20160480210.1002/ange.201604802 ↗
34. 10.1002/anie.20190110910.1002/anie.201901109 ↗
35. 10.1039/C6EE03145E10.1039/C6EE03145E ↗
36. 10.1016/j.jpowsour.2016.03.02810.1016/j.jpowsour.2016.03.028 ↗
37. 10.1039/C9TB00797K10.1039/C9TB00797K ↗
38. 10.1021/acscatal.7b0167110.1021/acscatal.7b01671 ↗
39. 10.1039/C5CP06779K10.1039/C5CP06779K ↗
40. 10.1021/jacs.7b1019410.1021/jacs.7b10194 ↗
41. 10.1021/acscatal.7b0327010.1021/acscatal.7b03270 ↗
42. 10.1021/acssuschemeng.1c0263510.1021/acssuschemeng.1c02635 ↗
43. 10.1038/s41467-021-23737-110.1038/s41467-021-23737-1 ↗
44. 10.1039/C6NR08473G10.1039/C6NR08473G ↗
45. 10.1016/j.cbi.2010.01.04210.1016/j.cbi.2010.01.042 ↗
46. 10.1016/j.snb.2020.12787310.1016/j.snb.2020.127873 ↗
47. 10.1016/j.snb.2015.09.02310.1016/j.snb.2015.09.023 ↗
48. 10.1039/C9AY01815H10.1039/C9AY01815H ↗
49. 10.1016/j.bios.2019.02.03110.1016/j.bios.2019.02.031 ↗
50. 10.1016/j.snb.2018.09.09710.1016/j.snb.2018.09.097 ↗
51. 10.1016/j.bios.2015.08.06310.1016/j.bios.2015.08.063 ↗
52. 10.1016/j.talanta.2018.02.03410.1016/j.talanta.2018.02.034 ↗
53. 10.1016/j.bios.2011.03.03710.1016/j.bios.2011.03.037 ↗
54. 10.6023/A1707032110.6023/A17070321 ↗
55. 10.1016/j.bios.2015.11.09610.1016/j.bios.2015.11.096 ↗
56. 10.1002/smll.20190310810.1002/smll.201903108 ↗
57. 10.1002/smll.20180168010.1002/smll.201801680 ↗
58. 10.1016/j.snb.2019.04.02010.1016/j.snb.2019.04.020 ↗
59. 10.1007/s00604-018-2974-410.1007/s00604-018-2974-4 ↗
60. 10.1039/C8TB02616E10.1039/C8TB02616E ↗
61. 10.1385/JMN:20:3:36910.1385/JMN:20:3:369 ↗