journal article·2026-07-22Open access

Electric-Field Sensor Based on Multilayer-MoS 2 /Multilayer-Graphene Heterostructure with Built-In Tensile Strain

Jiali Hu, Mohammad Razzakul Islam, Afsal Kareekunnan, Takeshi Kudo, Takeshi Maruyama, Masashi Akabori, Hiroshi Mizuta

ACS Applied Materials & Interfaces· Volume 18· Issue 28

Abstract

High Resolution Image Download MS PowerPoint Slide We report a highly sensitive electric field (E-field) sensor based on a multilayer MoS 2 /multilayer graphene (ML-MoS 2 /MLG) heterostructure with built-in tensile strain. The MLG functions as a bottom source-drain contact, thereby enhancing the charge injection into the ML-MoS 2 channel. The unique device geometry further induces tensile strain in the ML-MoS 2 channel by bending it over the MLG edge, which improves the carrier mobility through reduced electron–phonon scattering. As a result, the ML-MoS 2 /MLG device achieves an average carrier mobility of 75.7 cm 2 V –1 s –1, with values up to ∼108 cm 2 V –1 s –1 at room temperature, significantly exceeding that of conventional metal-contacted MoS 2 devices. Upon exposure to external E-fields, the device exhibits polarity-dependent variations in the drain current arising from field-induced carrier transfer between the ML-MoS 2 channel and trap states at the SiO 2 /channel interface. The E-field sensitivity, defined as the relative change in drain current, increases linearly with the E-field magnitude. Owing to the enhanced charge injection and improved carrier mobility, the ML-MoS 2 /MLG device demonstrates superior E-field sensing performance, achieving a sensitivity around three times that of metal-contacted MoS 2 devices. Notably, the minimum detectable E-field reaches ∼100 V/m, highlighting its potential for atmospheric E-field monitoring toward lightning detection applications.
Source: openalex_inverted_index · Quality: baseline

Research context

OpenAlex topics: 2D Materials and Applications · Graphene research and applications · Advanced Sensor and Energy Harvesting Materials

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

Affiliations

School of Materials Science

Japan Advanced Institute of Science and Technology

Otowa Electric Co., Ltd.

School of Electronics and Computer Science

University of Southampton

Funding

Japan Society for the Promotion of Science · Support for Pioneering Research Initiated by the Next Generation · OTOWA ELECTRIC CO., LTD. · Earth Inclusive Sensing Empathizing with Silent Voices (EISESiV) consortium

References (50)

Show source-provided references
1. 10.1038/s41586-021-03472-910.1038/s41586-021-03472-9 ↗
2. 10.1002/adfm.20220915110.1002/adfm.202209151 ↗
3. 10.1038/nnano.2015.11810.1038/nnano.2015.118 ↗
4. 10.1002/adfm.20200202310.1002/adfm.202002023 ↗
5. 10.1002/adfm.20210683010.1002/adfm.202106830 ↗
6. 10.1002/adma.20221159810.1002/adma.202211598 ↗
7. 10.1029/2020EA00130910.1029/2020EA001309 ↗
8. 10.1109/TIM.2024.350273210.1109/TIM.2024.3502732 ↗
9. 10.1109/ICSENS.2015.737026810.1109/ICSENS.2015.7370268 ↗
10. 10.1109/MIE.2020.304622610.1109/MIE.2020.3046226 ↗
11. 10.1088/0960-1317/23/5/05500210.1088/0960-1317/23/5/055002 ↗
12. 10.1109/JMEMS.2022.319082910.1109/JMEMS.2022.3190829 ↗
13. 10.1109/LED.2017.271678410.1109/LED.2017.2716784 ↗
14. 10.1021/acsomega.1c0553010.1021/acsomega.1c05530 ↗
15. 10.1063/5.009544910.1063/5.0095449 ↗
16. Afsal K. · 2021 · 1
17. 10.1021/acsomega.4c0335010.1021/acsomega.4c03350 ↗
18. 10.1021/am506921y10.1021/am506921y ↗
19. 10.1021/acs.jpcc.1c0161210.1021/acs.jpcc.1c01612 ↗
20. 10.1002/aelm.20220051310.1002/aelm.202200513 ↗
21. 10.1109/LED.2014.231334010.1109/LED.2014.2313340 ↗
22. 10.1002/smll.20130390810.1002/smll.201303908 ↗
23. 10.1021/nl504957p10.1021/nl504957p ↗
24. 10.1038/s41699-024-00471-y10.1038/s41699-024-00471-y ↗
25. 10.1103/PhysRevB.80.07340810.1103/PhysRevB.80.073408 ↗
26. 10.1021/nl401474810.1021/nl4014748 ↗
27. 10.1021/acs.nanolett.8b0092810.1021/acs.nanolett.8b00928 ↗
28. 10.1039/D1MA00806D10.1039/D1MA00806D ↗
29. 10.1021/acsami.3c1349710.1021/acsami.3c13497 ↗
30. 10.1002/adma.20241742810.1002/adma.202417428 ↗
31. 10.1002/aelm.20190080310.1002/aelm.201900803 ↗
32. 10.1021/acsnano.3c0362610.1021/acsnano.3c03626 ↗
33. 10.1021/acsnano.4c0145710.1021/acsnano.4c01457 ↗
34. 10.1038/s41467-024-51165-410.1038/s41467-024-51165-4 ↗
35. 10.1021/acsnano.3c0899610.1021/acsnano.3c08996 ↗
36. 10.1103/PhysRevB.99.19540110.1103/PhysRevB.99.195401 ↗
37. 10.1021/acsnano.7b0701510.1021/acsnano.7b07015 ↗
38. 10.1103/PhysRevB.85.16140310.1103/PhysRevB.85.161403 ↗
39. 10.1021/nn500676t10.1021/nn500676t ↗
40. 10.1021/nl901572a10.1021/nl901572a ↗
41. 10.1038/nmat351810.1038/nmat3518 ↗
42. 10.1038/ncomms265210.1038/ncomms2652 ↗
43. 10.1021/nl500212s10.1021/nl500212s ↗
44. Schroder D. K. · 2006
45. 10.1016/j.vacuum.2018.04.02810.1016/j.vacuum.2018.04.028 ↗
46. 10.1063/1.486853610.1063/1.4868536 ↗
47. 10.1088/2053-1583/acb21c10.1088/2053-1583/acb21c ↗
48. 10.1186/s40562-023-00299-210.1186/s40562-023-00299-2 ↗
49. 10.1038/nnano.2013.10010.1038/nnano.2013.100 ↗
50. 10.1021/acsami.3c0932210.1021/acsami.3c09322 ↗