Interfacial Ammonia Selectivity, Atmospheric Passivation, and Molecular Identification in Graphene-Nanopored Activated Carbon Molecular-Sieve Gas Sensors
Source abstract
Abstract
Graphene's inherent nonselectivity and strong atmospheric doping render most graphene-based sensors unsuitable for atmospheric applications in environmental monitoring of pollutants and breath detection of biomarkers for noninvasive medical diagnosis. Hence, demonstrations of graphene's gas sensitivity are often in inert environments such as nitrogen, consequently of little practical relevance. Herein, target gas sensing at the graphene-activated carbon interface of a graphene-nanopored activated carbon molecular-sieve sensor obtained via the postlithographic pyrolysis of Novolac resin residues on graphene nanoribbons is shown to simultaneously induce ammonia selectivity and atmospheric passivation of graphene. Consequently, 500 parts per trillion (ppt) ammonia sensitivity in atmospheric air is achieved with a response time of ∼3 s. The similar graphene and a-C workfunctions ensure that the ambipolar and gas-adsorption-induced charge transfer characteristics of pristine graphene are retained. Harnessing the van der Waals bonding memory and electrically tunable charge-transfer characteristics of the adsorbed molecules on the graphene channel, a molecular identification technique (charge neutrality point disparity) is developed and demonstrated to be suitable even at parts per billion (ppb) gas concentrations. The selectivity and atmospheric passivation induced by the graphene-activated carbon interface enable atmospheric applications of graphene sensors in environmental monitoring and noninvasive medical diagnosis.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Gas Sensing Nanomaterials and Sensors · Graphene research and applications · Analytical Chemistry and Sensors
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
School of Materials Science, Japan Advanced Institute of Science and Technology, Nomi 923-1211, Japan
Physics Department, Faculty of Science, Minia University, 11432 Main Road-Shalaby Land, Minia 61519, Egypt
TAIYO YUDEN CO., LTD. R&D Center, 5607-2, Nakamuroda-machi, Takasaki-shi, Gunma 370-3347, Japan
Hitachi Cambridge Laboratory, Hitachi Europe Ltd., J.J. Thomson Avenue, Cambridge CB3 0HE, U.K.
Funding
Japan Society for the Promotion of Science · TAIYO YUDEN Co., Ltd.
References (58)
Show source-provided references
1. 10.1021/nl300129310.1021/nl3001293 ↗
2. 10.1126/sciadv.150151810.1126/sciadv.1501518 ↗
3. 10.1038/nmat196710.1038/nmat1967 ↗
4. 10.1103/PhysRevB.101.19540610.1103/PhysRevB.101.195406 ↗
5. 10.1021/acsnano.9b0293510.1021/acsnano.9b02935 ↗
6. 10.1016/j.carbon.2019.07.03610.1016/j.carbon.2019.07.036 ↗
7. 10.1016/J.CARBON.2011.12.00810.1016/J.CARBON.2011.12.008 ↗
8. 10.1038/s41378-020-0161-310.1038/s41378-020-0161-3 ↗
9. 10.1021/cr300041210.1021/cr3000412 ↗
10. 10.1007/s00216-003-2453-510.1007/s00216-003-2453-5 ↗
11. 10.1166/jnn.2018.1547410.1166/jnn.2018.15474 ↗
12. 10.1016/J.APSUSC.2018.11.23610.1016/J.APSUSC.2018.11.236 ↗
13. 10.1039/b908183f10.1039/b908183f ↗
14. 10.1016/j.memsci.2007.06.05510.1016/j.memsci.2007.06.055 ↗
15. 10.1016/B978-0-12-409547-2.12241-310.1016/B978-0-12-409547-2.12241-3 ↗
16. 10.1021/es203093v10.1021/es203093v ↗
17. 10.1021/acssensors.6b0009310.1021/acssensors.6b00093 ↗
18. 10.1021/ie010402v10.1021/ie010402v ↗
19. 10.1016/S1872-5805(13)60063-310.1016/S1872-5805(13)60063-3 ↗
20. 10.1039/C4TA06161F10.1039/C4TA06161F ↗
21. 10.1016/j.ymgme.2015.04.00410.1016/j.ymgme.2015.04.004 ↗
22. 10.1016/J.SNB.2004.11.05410.1016/J.SNB.2004.11.054 ↗
23. 10.1073/pnas.07105759810.1073/pnas.071057598 ↗
24. 10.1021/ACS.ANALCHEM.1C0017110.1021/ACS.ANALCHEM.1C00171 ↗
25. 10.1038/s41598-021-86686-110.1038/s41598-021-86686-1 ↗
26. 10.1039/D1RA02554F10.1039/D1RA02554F ↗
27. 10.1021/acs.nanolett.5b0365310.1021/acs.nanolett.5b03653 ↗
28. 10.1002/admi.20170164010.1002/admi.201701640 ↗
29. 10.1016/j.biosx.2019.10001610.1016/j.biosx.2019.100016 ↗
30. 10.1063/5.002450810.1063/5.0024508 ↗
31. 10.1021/acssensors.0c0040310.1021/acssensors.0c00403 ↗
32. 10.1038/s41467-018-05407-x10.1038/s41467-018-05407-x ↗
33. 10.1038/srep2285810.1038/srep22858 ↗
34. 10.1016/j.ijhydene.2015.02.11210.1016/j.ijhydene.2015.02.112 ↗
35. 10.1016/j.polymdegradstab.2014.12.02010.1016/j.polymdegradstab.2014.12.020 ↗
36. 10.1039/C6CS00915H10.1039/C6CS00915H ↗
37. 10.1038/srep0186810.1038/srep01868 ↗
38. 10.1088/1367-2630/12/12/12501110.1088/1367-2630/12/12/125011 ↗
39. 10.1063/1.131487410.1063/1.1314874 ↗
40. 10.1002/adma.20110266310.1002/adma.201102663 ↗
41. 10.1038/nature0971810.1038/nature09718 ↗
42. 10.1038/ncomms591110.1038/ncomms5911 ↗
43. 10.1126/sciadv.aar517010.1126/sciadv.aar5170 ↗
44. 10.3390/S15122981410.3390/S151229814 ↗
45. 10.1039/C9RA05439A10.1039/C9RA05439A ↗
46. 10.1016/J.JCIS.2016.07.00410.1016/J.JCIS.2016.07.004 ↗
47. 10.1016/J.SYNTHMET.2020.11648210.1016/J.SYNTHMET.2020.116482 ↗
48. 10.1007/S10854-017-7235-510.1007/S10854-017-7235-5 ↗
49. 10.1002/PC.2491710.1002/PC.24917 ↗
50. 10.1016/j.orgel.2014.08.04410.1016/j.orgel.2014.08.044 ↗
51. 10.1039/C9RA08707A10.1039/C9RA08707A ↗
52. 10.1016/J.SYNTHMET.2013.09.03410.1016/J.SYNTHMET.2013.09.034 ↗
53. 10.1039/C8RA07509C10.1039/C8RA07509C ↗
54. 10.1186/S11671-015-1072-310.1186/S11671-015-1072-3 ↗
55. 10.1109/JSEN.2018.286920310.1109/JSEN.2018.2869203 ↗
56. 10.1021/acsaelm.9b0053210.1021/acsaelm.9b00532 ↗
57. 10.1016/j.snb.2017.06.11610.1016/j.snb.2017.06.116 ↗
58. 10.1016/j.vacuum.2016.08.00610.1016/j.vacuum.2016.08.006 ↗