The DOI matches its Crossref record; 195 of the 195 references it cites were found in a registry or an index.
Electrolyte-gated transistors for synaptic electronics, neuromorphic computing, and adaptable biointerfacing
Open accessAbstract
Functional emulation of biological synapses using electronic devices is regarded as the first step toward neuromorphic engineering and artificial neural networks (ANNs). Electrolyte-gated transistors (EGTs) are mixed ionic–electronic conductivity devices capable of efficient gate-channel capacitance coupling, biocompatibility, and flexible architectures. Electrolyte gating offers significant advantages for the realization of neuromorphic devices/architectures, including ultralow-voltage operation and the ability to form parallel-interconnected networks with minimal hardwired connectivity. In this review, the most recent developments in EGT-based electronics are introduced with their synaptic behaviors and detailed mechanisms, including short-/long-term plasticity, global regulation phenomena, lateral coupling between device terminals, and spatiotemporal correlated functions. Analog memory phenomena allow for the implementation of perceptron-based ANNs. Due to their mixed-conductivity phenomena, neuromorphic circuits based on EGTs allow for facile interfacing with biological environments. We also discuss the future challenges in implementing low power, high speed, and reliable neuromorphic computing for large-scale ANNs with these neuromorphic devices. The advancement of neuromorphic devices that rely on EGTs highlights the importance of this field for neuromorphic computing and for novel healthcare technologies in the form of adaptable or trainable biointerfacing.
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
Strukov, D. B., Snider, G. S., Stewart, D. R., & Williams, R. S. (2008) · Nature · doi:10.1038/nature06932 · Cited by 11,828
Memristor—The Missing Circuit Element
Chua, L. (1971) · IEEE Transactions on Circuit Theory · doi:10.1109/tct.1971.1083337 · Cited by 10,268
Short-Term Synaptic Plasticity
Zucker, R. S., & Regehr, W. G. (2002) · Annual Review of Physiology · doi:10.1146/annurev.physiol.64.092501.114547 · Cited by 5,068
Nanoionics-based resistive switching memories
Waser, R., & Aono, M. (2007) · Nature Materials · doi:10.1038/nmat2023 · Cited by 4,923
A million spiking-neuron integrated circuit with a scalable communication network and interface
Merolla, P. A., Arthur, J. V., Alvarez-Icaza, R., Cassidy, A. S., Sawada, J., Akopyan, F., Jackson, B. L., Imam, N., Guo, C., Nakamura, Y., et al. (2014) · Science · doi:10.1126/science.1254642 · Cited by 4,147
Malenka, R. C., & Bear, M. F. (2004) · Neuron · doi:10.1016/j.neuron.2004.09.012 · Cited by 3,968
Loihi: A Neuromorphic Manycore Processor with On-Chip Learning
Davies, M., Srinivasa, N., Lin, T.-H., Chinya, G., Cao, Y., Choday, S. H., Dimou, G., Joshi, P., Imam, N., Jain, S., et al. (2018) · IEEE Micro · doi:10.1109/mm.2018.112130359 · Cited by 3,897
Artificial neural networks: fundamentals, computing, design, and application
Basheer, I. A., & Hajmeer, M. (2000) · Journal of Microbiological Methods · doi:10.1016/s0167-7012(00)00201-3 · Cited by 3,231
Memristive switching mechanism for metal/oxide/metal nanodevices
Yang, J. J., Pickett, M. D., Li, X., Ohlberg, D. A. A., Stewart, D. R., & Williams, R. S. (2008) · Nature Nanotechnology · doi:10.1038/nnano.2008.160 · Cited by 2,987
Evolving artificial neural networks
Yao, X. (1999) · Proceedings of the IEEE · doi:10.1109/5.784219 · Cited by 2,981
Cited by
Pham, P. V., Bodepudi, S. C., Shehzad, K., Liu, Y., Xu, Y., Yu, B., & Duan, X. (2022) · Chemical Reviews · doi:10.1021/acs.chemrev.1c00735 · Cited by 708
Electrolyte-gated transistors for enhanced performance bioelectronics
Torricelli, F., Adrahtas, D. Z., Bao, Z., Berggren, M., Biscarini, F., Bonfiglio, A., Bortolotti, C. A., Frisbie, C. D., Macchia, E., Malliaras, G. G., et al. (2021) · Nature Reviews Methods Primers · doi:10.1038/s43586-021-00065-8 · Cited by 422
Hardware Implementation of Neuromorphic Computing Using Large‐Scale Memristor Crossbar Arrays
Li, Y., & Ang, K.-W. (2021) · Advanced Intelligent Systems · doi:10.1002/aisy.202000137 · Cited by 220
Dong, T., Matos Pires, N. M., Yang, Z., & Jiang, Z. (2023) · Advanced Science · doi:10.1002/advs.202205429 · Cited by 104
Metadata
- Authors
- Ling, H., Koutsouras, D. A., Kazemzadeh, S., van de Burgt, Y., Yan, F., & Gkoupidenis, P.
- Venue
- Applied Physics Reviews
- Publisher
- AIP Publishing
- Published
- 2020-01-16
- Volume
- 7
- Issue
- 1
- ISSN
- 1931-9401 (ISSN-L)
- OpenAlex
- W3000591787
- Cited by
- 294
- References
- 195
- FWCI
- 13.84
- Type
- journal article
- Language
- en
- Open access
- bronze
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: Electrolyte-gated transistors for synaptic electronics, neuromorphic computing, and adaptable biointerfacing. https://app.cochat.ai/papers/10.1063/1.5122249
- The paper
- Ling, H., Koutsouras, D. A., Kazemzadeh, S., van de Burgt, Y., Yan, F., & Gkoupidenis, P. (2020). Electrolyte-gated transistors for synaptic electronics, neuromorphic computing, and adaptable biointerfacing. Applied Physics Reviews. https://doi.org/10.1063/1.5122249
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.
