The DOI matches its Crossref record.
High‐Performance Sensors Based on Molybdenum Disulfide Thin Films
Open accessAbstract
High-performance sensors based on molybdenum disulfide (MoS2 ) grown by sulfurization of sputtered molybdenum layers are presented. Using a simple integration scheme, it is found that the electrical conductivity of MoS2 films is highly sensitive to NH3 adsorption, consistent with n-type semiconducting behavior. A sensitivity of 300 ppb at room temperature is achieved, showing the high potential of 2D transition metal-dichalcogenides for sensing.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cited by
Emerging Device Applications for Semiconducting Two-Dimensional Transition Metal Dichalcogenides
Jariwala, D., Sangwan, V. K., Lauhon, L. J., Marks, T. J., & Hersam, M. C. (2014) · ACS Nano · doi:10.1021/nn500064s · Cited by 2,753
Electrically-Transduced Chemical Sensors Based on Two-Dimensional Nanomaterials
Meng, Z., Stolz, R. M., Mendecki, L., & Mirica, K. A. (2019) · Chemical Reviews · doi:10.1021/acs.chemrev.8b00311 · Cited by 773
Recent advances in energy-saving chemiresistive gas sensors: A review
Majhi, S. M., Mirzaei, A., Kim, H. W., Kim, S. S., & Kim, T. W. (2021) · Nano Energy · doi:10.1016/j.nanoen.2020.105369 · Cited by 653
Charge-transfer-based Gas Sensing Using Atomic-layer MoS2
Cho, B., Hahm, M. G., Choi, M., Yoon, J., Kim, A. R., Lee, Y.-J., Park, S.-G., Kwon, J.-D., Kim, C. S., Song, M., et al. (2015) · Scientific Reports · doi:10.1038/srep08052 · Cited by 649
High Surface Area MoS 2 /Graphene Hybrid Aerogel for Ultrasensitive NO 2 Detection
Long, H., Harley‐Trochimczyk, A., Pham, T., Tang, Z., Shi, T., Zettl, A., Carraro, C., Worsley, M. A., & Maboudian, R. (2016) · Advanced Functional Materials · doi:10.1002/adfm.201601562 · Cited by 479
Metadata
- Authors
- Lee, K., Gatensby, R., McEvoy, N., Hallam, T., & Duesberg, G. S.
- Venue
- Advanced Materials
- Publisher
- Wiley
- Published
- 2013-09-12
- Volume
- 25
- Issue
- 46
- Pages
- 6699-6702
- ISSN
- 0935-9648 (ISSN-L)
- 1521-4095
- OpenAlex
- W2025015431
- Cited by
- 499
- References
- 0
- FWCI
- 20.57
- Type
- journal article
- Language
- en
- Open access
- green
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: High‐Performance Sensors Based on Molybdenum Disulfide Thin Films. https://app.cochat.ai/papers/10.1002/adma.201303230
- The paper
- Lee, K., Gatensby, R., McEvoy, N., Hallam, T., & Duesberg, G. S. (2013). High‐Performance Sensors Based on Molybdenum Disulfide Thin Films. Advanced Materials. https://doi.org/10.1002/adma.201303230
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.