High Specific Surface Area 2D/1D Hybrid Materials of Nb2CTx/CNT for Efficient VOCs Detection at Room Temperature
Source abstract
Abstract
Monitoring of volatile organic compounds (VOCs) is important in many fields. MXene, a class of two-dimensional materials, exhibits significant potential for high-sensitivity VOCs detection owing to its high specific surface area and abundant functional groups. However, MXene layers tend to restack or aggregate in practical applications due to van der Waals forces and hydrogen bonding, which leads to a decrease of surface area compared to theoretical performance. One-dimensional (1D) carbon nanotube (CNT)/two-dimensional (2D) MXene mixed-dimensional heterostructures have been proven to be effective in improving catalytic efficiency or battery performance. Therefore, in this study, CNT and MXene (Nb 2 CT x ) are constructed as hybrids, which effectively reduced the restack of MXene layers, thereby increasing the surface area available for VOCs binding. The sensitivity of the hybrids to ethanol and acetone is 3.9 and 5.6 times higher than that of pristine Nb 2 CT x, respectively. In addition, the sensor based on Nb 2 CT x /CNT hybrids shows a higher response to a variety of VOCs and exhibits good stability. It is an effective method for VOCs detection to take advantage of the high specific surface area of low-dimensional materials by constructing mixed-dimensional heterostructures.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: MXene and MAX Phase Materials · Gas Sensing Nanomaterials and Sensors · 2D Materials and Applications
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
Department of Mechanical and Energy Engineering, Southern University of Science and Technology, Shenzhen, Guangdong 518055, China
Funding
National Natural Science Foundation of China
References (54)
Show source-provided references
1. 10.1021/acsnano.1c1082710.1021/acsnano.1c10827 ↗
2. 10.1021/acs.chemrev.8b0040810.1021/acs.chemrev.8b00408 ↗
3. 10.1016/j.atmosenv.2016.05.03110.1016/j.atmosenv.2016.05.031 ↗
4. 10.1039/C8CS00317C10.1039/C8CS00317C ↗
5. 10.1002/admi.20190132910.1002/admi.201901329 ↗
6. 10.1021/acs.accounts.7b0004710.1021/acs.accounts.7b00047 ↗
7. 10.1007/s00216-016-9903-310.1007/s00216-016-9903-3 ↗
8. 10.1016/j.snb.2010.09.04310.1016/j.snb.2010.09.043 ↗
9. 10.1016/j.snb.2021.13106610.1016/j.snb.2021.131066 ↗
10. 10.1039/C9NR07699A10.1039/C9NR07699A ↗
11. 10.1016/j.ceramint.2016.06.14510.1016/j.ceramint.2016.06.145 ↗
12. 10.1021/acsnano.7b0746010.1021/acsnano.7b07460 ↗
13. 10.1002/adfm.20170216810.1002/adfm.201702168 ↗
14. 10.1016/j.aca.2015.02.00210.1016/j.aca.2015.02.002 ↗
15. 10.1021/acsami.1c1677610.1021/acsami.1c16776 ↗
16. 10.1002/smll.20220610010.1002/smll.202206100 ↗
17. 10.1063/5.015001810.1063/5.0150018 ↗
18. 10.1063/5.016740310.1063/5.0167403 ↗
19. 10.1002/adma.20110230610.1002/adma.201102306 ↗
20. 10.1126/science.abf158110.1126/science.abf1581 ↗
21. 10.1002/adma.20130413810.1002/adma.201304138 ↗
22. 10.1002/adma.20210339310.1002/adma.202103393 ↗
23. 10.1016/j.trechm.2019.04.00610.1016/j.trechm.2019.04.006 ↗
24. 10.1021/acssensors.2c0174810.1021/acssensors.2c01748 ↗
25. 10.1016/j.addr.2022.11417810.1016/j.addr.2022.114178 ↗
26. 10.1021/acssensors.9b0012710.1021/acssensors.9b00127 ↗
27. 10.1002/adma.20180477910.1002/adma.201804779 ↗
28. 10.1126/science.aba831110.1126/science.aba8311 ↗
29. 10.1002/adma.20200584610.1002/adma.202005846 ↗
30. 10.1016/j.snb.2023.13525810.1016/j.snb.2023.135258 ↗
31. 10.1016/j.snb.2024.13546410.1016/j.snb.2024.135464 ↗
32. 10.1016/j.ccr.2020.21351410.1016/j.ccr.2020.213514 ↗
33. 10.1016/j.trac.2018.05.02110.1016/j.trac.2018.05.021 ↗
34. 10.1021/acssensors.2c0104610.1021/acssensors.2c01046 ↗
35. 10.1002/admt.20210087210.1002/admt.202100872 ↗
36. 10.1007/s40820-022-00796-710.1007/s40820-022-00796-7 ↗
37. 10.1016/j.snb.2020.12882810.1016/j.snb.2020.128828 ↗
38. 10.1039/C8TA06928J10.1039/C8TA06928J ↗
39. 10.1021/acsnano.3c1147510.1021/acsnano.3c11475 ↗
40. 10.1002/cssc.20210161410.1002/cssc.202101614 ↗
41. 10.1021/acs.jpcc.6b0287810.1021/acs.jpcc.6b02878 ↗
42. 10.1002/adma.20200689710.1002/adma.202006897 ↗
43. 10.1002/adma.20150060410.1002/adma.201500604 ↗
44. 10.1039/D2MA00301E10.1039/D2MA00301E ↗
45. 10.1002/admi.20220041510.1002/admi.202200415 ↗
46. 10.1016/j.electacta.2021.13956610.1016/j.electacta.2021.139566 ↗
47. 10.1063/5.003080910.1063/5.0030809 ↗
48. 10.1016/j.carbon.2016.09.06410.1016/j.carbon.2016.09.064 ↗
49. 10.1021/acsami.7b1105510.1021/acsami.7b11055 ↗
50. 10.1021/acs.chemmater.7b0074510.1021/acs.chemmater.7b00745 ↗
51. 10.1021/acsnano.0c0389610.1021/acsnano.0c03896 ↗
52. 10.1063/5.017576710.1063/5.0175767 ↗
53. 10.1016/j.scib.2023.07.02210.1016/j.scib.2023.07.022 ↗
54. 10.1002/adma.20210147310.1002/adma.202101473 ↗