The DOI matches its Crossref record; 111 of the 111 references it cites were found in a registry or an index.
Detection principles of biological and chemical FET sensors
Open accessAbstract
The seminal importance of detecting ions and molecules for point-of-care tests has driven the search for more sensitive, specific, and robust sensors. Electronic detection holds promise for future miniaturized in-situ applications and can be integrated into existing electronic manufacturing processes and technology. The resulting small devices will be inherently well suited for multiplexed and parallel detection. In this review, different field-effect transistor (FET) structures and detection principles are discussed, including label-free and indirect detection mechanisms. The fundamental detection principle governing every potentiometric sensor is introduced, and different state-of-the-art FET sensor structures are reviewed. This is followed by an analysis of electrolyte interfaces and their influence on sensor operation. Finally, the fundamentals of different detection mechanisms are reviewed and some detection schemes are discussed. In the conclusion, current commercial efforts are briefly considered.
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
Cites
Intermolecular and Surface Forces
(2011) · Intermolecular and Surface Forces · doi:10.1016/b978-0-12-391927-4.10024-6 · Cited by 16,923
Intermolecular and Surface Forces
(2011) · Elsevier eBooks · doi:10.1016/c2011-0-05119-0 · Cited by 8,968
Functional Nanoscale Electronic Devices Assembled Using Silicon Nanowire Building Blocks
Cui, Y., & Lieber, C. M. (2001) · Science · doi:10.1126/science.291.5505.851 · Cited by 3,258
An integrated semiconductor device enabling non-optical genome sequencing
Rothberg, J. M., Hinz, W., Rearick, T. M., Schultz, J., Mileski, W., Davey, M., Leamon, J. H., Johnson, K., Milgrew, M. J., Edwards, M., et al. (2011) · Nature · doi:10.1038/nature10242 · Cited by 2,172
Development of an Ion-Sensitive Solid-State Device for Neurophysiological Measurements
Bergveld, P. (1970) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.1970.4502688 · Cited by 2,134
Ronkainen, N. J., Halsall, H. B., & Heineman, W. R. (2010) · Chemical Society Reviews · doi:10.1039/b714449k · Cited by 1,945
Bergveld, P. (2003) · Sensors and Actuators B: Chemical · doi:10.1016/s0925-4005(02)00301-5 · Cited by 1,582
Solid state electronic devices
Streetman, B. G. (1972) · CERN Document Server (European Organization for Nuclear Research) · Cited by 1,475
Making it stick: convection, reaction and diffusion in surface-based biosensors
Squires, T. M., Messinger, R. J., & Manalis, S. R. (2008) · Nature Biotechnology · doi:10.1038/nbt1388 · Cited by 986
Bobacka, J., Ivaska, A., & Lewenstam, A. (2008) · Chemical Reviews · doi:10.1021/cr068100w · Cited by 975
Cited by
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
From Diagnosis to Treatment: Recent Advances in Patient-Friendly Biosensors and Implantable Devices
Li, P., Lee, G.-H., Kim, S. Y., Kwon, S. Y., Kim, H.-R., & Park, S. (2021) · ACS Nano · doi:10.1021/acsnano.0c06688 · Cited by 359
The Era of Digital Health: A Review of Portable and Wearable Affinity Biosensors
Tu, J., Torrente‐Rodríguez, R. M., Wang, M., & Gao, W. (2020) · Advanced Functional Materials · doi:10.1002/adfm.201906713 · Cited by 357
Wang, L., Wang, X., Wu, Y., Guo, M., Gu, C., Dai, C., Kong, D., Wang, Y., Zhang, C., Qu, D., et al. (2022) · Nature Biomedical Engineering · doi:10.1038/s41551-021-00833-7 · Cited by 334
Review—Field-Effect Transistor Biosensing: Devices and Clinical Applications
Syu, Y.-C., Hsu, W.-E., & Lin, C.-T. (2018) · ECS Journal of Solid State Science and Technology · doi:10.1149/2.0291807jss · Cited by 284
Metadata
- Authors
- Kaisti, M.
- Venue
- Biosensors and Bioelectronics
- Publisher
- Elsevier BV
- Published
- 2017-12
- Volume
- 98
- Pages
- 437-448
- ISSN
- 0956-5663 (ISSN-L)
- OpenAlex
- W2725266022
- Cited by
- 577
- References
- 111
- FWCI
- 35.86
- Type
- journal article
- Language
- en
- Open access
- hybrid
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: Detection principles of biological and chemical FET sensors. https://app.cochat.ai/papers/10.1016/j.bios.2017.07.010
- The paper
- Kaisti, M. (2017). Detection principles of biological and chemical FET sensors. Biosensors and Bioelectronics. https://doi.org/10.1016/j.bios.2017.07.010
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.
