The DOI matches its Crossref record; 32 of the 32 references it cites were found in a registry or an index.
Two-dimensional ferroelectric channel transistors integrating ultra-fast memory and neural computing
Open accessAbstract
With the advent of the big data era, applications are more data-centric and energy efficiency issues caused by frequent data interactions, due to the physical separation of memory and computing, will become increasingly severe. Emerging technologies have been proposed to perform analog computing with memory to address the dilemma. Ferroelectric memory has become a promising technology due to field-driven fast switching and non-destructive readout, but endurance and miniaturization are limited. Here, we demonstrate the α-In 2 Se 3 ferroelectric semiconductor channel device that integrates non-volatile memory and neural computation functions. Remarkable performance includes ultra-fast write speed of 40 ns, improved endurance through the internal electric field, flexible adjustment of neural plasticity, ultra-low energy consumption of 234/40 fJ per event for excitation/inhibition, and thermally modulated 94.74% high-precision iris recognition classification simulation. This prototypical demonstration lays the foundation for an integrated memory computing system with high density and energy efficiency.
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Cites
Memristors with diffusive dynamics as synaptic emulators for neuromorphic computing
Wang, Z., Joshi, S., Savel’ev, S. E., Jiang, H., Midya, R., Lin, P., Hu, M., Ge, N., Strachan, J. P., Li, Z., et al. (2017) · Nature Materials · doi:10.1038/nmat4756 · Cited by 2,358
In-memory computing with resistive switching devices
Ielmini, D., & Wong, H.-S. P. (2018) · Nature Electronics · doi:10.1038/s41928-018-0092-2 · Cited by 2,298
Mesopelagic fish biomass and trophic efficiency of the open ocean
Irigoien, X., Klevjer, J., Røstad, A., Martínez, U., Boyra, G., Acuña, J. L., Bode, A., Echevarrı́a, F., González-Gordillo, J. L., Hernández‐León, S., et al. (2014) · DIGITAL.CSIC (Spanish National Research Council (CSIC)) · Cited by 1,813
Memristive crossbar arrays for brain-inspired computing
Xia, Q., & Yang, J. J. (2019) · Nature Materials · doi:10.1038/s41563-019-0291-x · Cited by 1,800
Graphene and two-dimensional materials for silicon technology
Akinwande, D., Huyghebaert, C., Wang, C.-H., Serna, M. I., Goossens, S., Li, L.-J., Wong, H.-S. P., & Koppens, F. H. L. (2019) · Nature · doi:10.1038/s41586-019-1573-9 · Cited by 1,713
Analogue signal and image processing with large memristor crossbars
Li, C., Hu, M., Li, Y., Jiang, H., Ge, N., Montgomery, E., Zhang, J., Song, W., Dávila, N., Graves, C. E., et al. (2017) · Nature Electronics · doi:10.1038/s41928-017-0002-z · Cited by 1,292
First draft of a report on the EDVAC
von Neumann, J. (1993) · IEEE Annals of the History of Computing · doi:10.1109/85.238389 · Cited by 1,112
Stochastic phase-change neurons
Tuma, T., Pantazi, A., Le Gallo, M., Sebastian, A., & Eleftheriou, E. (2016) · Nature Nanotechnology · doi:10.1038/nnano.2016.70 · Cited by 1,109
Two-dimensional materials for next-generation computing technologies
Liu, C., Chen, H., Wang, S., Liu, Q., Jiang, Y.-G., Zhang, D. W., Liu, M., & Zhou, P. (2020) · Nature Nanotechnology · doi:10.1038/s41565-020-0724-3 · Cited by 1,045
Self-citationMemory leads the way to better computing
Wong, H.-S. P., & Salahuddin, S. (2015) · Nature Nanotechnology · doi:10.1038/nnano.2015.29 · Cited by 956
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
Huang, J., Yang, S., Tang, X., Yang, L., Chen, W., Chen, Z., Li, X., Zeng, Z., Tang, Z., & Gui, X. (2023) · Advanced Materials · doi:10.1002/adma.202303737 · Cited by 101
Metadata
- Authors
- Wang, S., Liu, L., Gan, L., Chen, H., Hou, X., Ding, Y., Ma, S., Zhang, D. W., & Zhou, P.
- Venue
- Nature Communications
- Published
- 2021-01-04
- Volume
- 12
- Issue
- 1
- Pages
- 53-53
- ISSN
- 2041-1723 (ISSN-L)
- OpenAlex
- W3120893773
- Cited by
- 346
- References
- 32
- FWCI
- 15.70
- Type
- journal article
- Language
- en
- Open access
- gold
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- Wang, S., Liu, L., Gan, L., Chen, H., Hou, X., Ding, Y., Ma, S., Zhang, D. W., & Zhou, P. (2021). Two-dimensional ferroelectric channel transistors integrating ultra-fast memory and neural computing. Nature Communications. https://doi.org/10.1038/s41467-020-20257-2
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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