The DOI matches its Crossref record; 45 of the 45 references it cites were found in a registry or an index.
Extremely Low Operating Current Resistive Memory Based on Exfoliated 2D Perovskite Single Crystals for Neuromorphic Computing
Abstract
Extremely low energy consumption neuromorphic computing is required to achieve massively parallel information processing on par with the human brain. To achieve this goal, resistive memories based on materials with ionic transport and extremely low operating current are required. Extremely low operating current allows for low power operation by minimizing the program, erase, and read currents. However, materials currently used in resistive memories, such as defective HfO x, AlO x, TaO x, etc., cannot suppress electronic transport ( i . e ., leakage current) while allowing good ionic transport. Here, we show that 2D Ruddlesden–Popper phase hybrid lead bromide perovskite single crystals are promising materials for low operating current nanodevice applications because of their mixed electronic and ionic transport and ease of fabrication. Ionic transport in the exfoliated 2D perovskite layer is evident via the migration of bromide ions. Filaments with a diameter of approximately 20 nm are visualized, and resistive memories with extremely low program current down to 10 pA are achieved, a value at least 1 order of magnitude lower than conventional materials. The ionic migration and diffusion as an artificial synapse is realized in the 2D layered perovskites at the pA level, which can enable extremely low energy neuromorphic computing.
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
Low trap-state density and long carrier diffusion in organolead trihalide perovskite single crystals
Shi, D., Adinolfi, V., Comin, R., Yuan, M., Alarousu, E., Buin, A., Chen, Y., Hoogland, S., Rothenberger, A., Katsiev, K., et al. (2015) · Science · doi:10.1126/science.aaa2725 · Cited by 5,139
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
High-efficiency two-dimensional Ruddlesden–Popper perovskite solar cells
Tsai, H., Nie, W., Blancon, J.-C., Stoumpos, C. C., Asadpour, R., Harutyunyan, B., Neukirch, A. J., Verduzco, R., Crochet, J. J., Tretiak, S., et al. (2016) · Nature · doi:10.1038/nature18306 · Cited by 3,384
Training and operation of an integrated neuromorphic network based on metal-oxide memristors
Prezioso, M., Merrikh-Bayat, F., Hoskins, B. D., Adam, G. C., Likharev, K. K., & Strukov, D. B. (2015) · Nature · doi:10.1038/nature14441 · Cited by 3,001
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
Resistive switching in transition metal oxides
Sawa, A. (2008) · Materials Today · doi:10.1016/s1369-7021(08)70119-6 · Cited by 2,948
Wong, H.-S. P., Lee, H.-Y., Yu, S., Chen, Y.-S., Wu, Y., Chen, P.-S., Lee, B., Chen, F. T., & Tsai, M.-J. (2012) · Proceedings of the IEEE · doi:10.1109/jproc.2012.2190369 · Cited by 2,757
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
Lee, M.-J., Lee, C. B., Lee, D., Lee, S. R., Chang, M., Hur, J. H., Kim, Y.-B., Kim, C.-J., Seo, D. H., Seo, S., et al. (2011) · Nature Materials · doi:10.1038/nmat3070 · Cited by 2,228
Atomic structure of conducting nanofilaments in TiO2 resistive switching memory
Kwon, D.-H., Kim, K. M., Jang, J. H., Jeon, J. M., Lee, M. H., Kim, G. H., Li, X.-S., Park, G.-S., Lee, B., Han, S., et al. (2010) · Nature Nanotechnology · doi:10.1038/nnano.2009.456 · Cited by 2,092
van de Burgt, Y., Lubberman, E., Fuller, E. J., Keene, S. T., Faria, G. C., Agarwal, S., Marinella, M. J., Alec Talin, A., & Salleo, A. (2017) · Nature Materials · doi:10.1038/nmat4856 · Cited by 1,872
Perovskite light-emitting diodes based on solution-processed self-organized multiple quantum wells
Wang, N., Cheng, L., Ge, R., Zhang, S., Miao, Y., Zou, W., Yi, C., Sun, Y., Cao, Y., Yang, R., et al. (2016) · Nature Photonics · doi:10.1038/nphoton.2016.185 · Cited by 1,845
Self-citationShort-term plasticity and long-term potentiation mimicked in single inorganic synapses
Ohno, T., Hasegawa, T., Tsuruoka, T., Terabe, K., Gimzewski, J. K., & Aono, M. (2011) · Nature Materials · doi:10.1038/nmat3054 · Cited by 1,793
Abbott, L. F., & Regehr, W. G. (2004) · Nature · doi:10.1038/nature03010 · Cited by 1,684
Giant switchable photovoltaic effect in organometal trihalide perovskite devices
Xiao, Z., Yuan, Y., Shao, Y., Wang, Q., Dong, Q., Bi, C., Sharma, P., Gruverman, A., & Huang, J. (2015) · Nature Materials · doi:10.1038/nmat4150 · Cited by 1,625
Efficient perovskite light-emitting diodes featuring nanometre-sized crystallites
Xiao, Z., Kerner, R. A., Zhao, L., Tran, N. L., Lee, K. M., Koh, T.-W., Scholes, G. D., & Rand, B. P. (2017) · Nature Photonics · doi:10.1038/nphoton.2016.269 · Cited by 1,374
Self-citationAtomically thin two-dimensional organic-inorganic hybrid perovskites
Dou, L., Wong, A. B., Yu, Y., Lai, M., Kornienko, N., Eaton, S. W., Fu, A., Bischak, C. G., Ma, J., Ding, T., et al. (2015) · Science · doi:10.1126/science.aac7660 · Cited by 1,372
Grain boundary dominated ion migration in polycrystalline organic–inorganic halide perovskite films
Shao, Y., Fang, Y., Li, T., Wang, Q., Dong, Q., Deng, Y., Yuan, Y., Wei, H., Wang, M., Gruverman, A., et al. (2016) · Energy & Environmental Science · doi:10.1039/c6ee00413j · Cited by 1,231
Towards stable and commercially available perovskite solar cells
Park, N.-G., Grätzel, M., Miyasaka, T., Zhu, K., & Emery, K. (2016) · Nature Energy · doi:10.1038/nenergy.2016.152 · Cited by 1,182
The metabolic cost of neural information
Laughlin, S. B., de Ruyter van Steveninck, R. R., & Anderson, J. C. (1998) · Nature Neuroscience · doi:10.1038/236 · Cited by 1,166
Gate-tunable memristive phenomena mediated by grain boundaries in single-layer MoS2
Sangwan, V. K., Jariwala, D., Kim, I. S., Chen, K.-S., Marks, T. J., Lauhon, L. J., & Hersam, M. C. (2015) · Nature Nanotechnology · doi:10.1038/nnano.2015.56 · Cited by 709
Yoo, E. J., Lyu, M., Yun, J., Kang, C. J., Choi, Y. J., & Wang, L. (2015) · Advanced Materials · doi:10.1002/adma.201502889 · Cited by 567
Flexible Hybrid Organic–Inorganic Perovskite Memory
Gu, C., & Lee, J.-S. (2016) · ACS Nano · doi:10.1021/acsnano.6b01643 · Cited by 566
Organometal Halide Perovskite Artificial Synapses
Xu, W., Cho, H., Kim, Y., Kim, Y., Wolf, C., Park, C., & Lee, T. (2016) · Advanced Materials · doi:10.1002/adma.201506363 · Cited by 448
Energy‐Efficient Hybrid Perovskite Memristors and Synaptic Devices
Xiao, Z., & Huang, J. (2016) · Advanced Electronic Materials · doi:10.1002/aelm.201600100 · Cited by 413
Guan, X., Yu, S., & Wong, H.-S. P. (2012) · IEEE Transactions on Electron Devices · doi:10.1109/ted.2012.2184545 · Cited by 355
Zhao, L., Kerner, R. A., Xiao, Z., Lin, Y. L., Lee, K. M., Schwartz, J., & Rand, B. P. (2016) · ACS Energy Letters · doi:10.1021/acsenergylett.6b00320 · Cited by 270
Self-citationYu, S., Guan, X., & Wong, H.-S. P. (2011) · 2011 International Electron Devices Meeting · doi:10.1109/iedm.2011.6131572 · Cited by 204
Ji, Y., Zeigler, D. F., Lee, D. S., Choi, H., Jen, A. K.-Y., Ko, H. C., & Kim, T.-W. (2013) · Nature Communications · doi:10.1038/ncomms3707 · Cited by 177
Tuning Ionic Transport in Memristive Devices by Graphene with Engineered Nanopores
Lee, J., Du, C., Sun, K., Kioupakis, E., & Lu, W. D. (2016) · ACS Nano · doi:10.1021/acsnano.5b07943 · Cited by 176
Zhao, L., Yeh, Y.-W., Tran, N. L., Wu, F., Xiao, Z., Kerner, R. A., Lin, Y. L., Scholes, G. D., Yao, N., & Rand, B. P. (2017) · ACS Nano · doi:10.1021/acsnano.7b00404 · Cited by 175
Self-citationLi, C., Gao, B., Yao, Y., Guan, X., Shen, X., Wang, Y., Huang, P., Liu, L., Liu, X., Li, J., et al. (2017) · Advanced Materials · doi:10.1002/adma.201602976 · Cited by 173
Yoo, E., Lyu, M., Yun, J.-H., Kang, C., Choi, Y., & Wang, L. (2016) · Journal of Materials Chemistry C · doi:10.1039/c6tc02503j · Cited by 171
Wu, Y., Lee, B., & Wong, H.-S. P. (2010) · IEEE Electron Device Letters · doi:10.1109/led.2010.2074177 · Cited by 161
Tian, H., Chen, H.-Y., Gao, B., Yu, S., Liang, J., Yang, Y., Xie, D., Kang, J., Ren, T.-L., Zhang, Y., et al. (2013) · Nano Letters · doi:10.1021/nl304246d · Cited by 129
Self-citationElectrical Stress Influences the Efficiency of CH3NH3PbI3 Perovskite Light Emitting Devices
Zhao, L., Gao, J., Lin, Y. L., Yeh, Y., Lee, K. M., Yao, N., Loo, Y., & Rand, B. P. (2017) · Advanced Materials · doi:10.1002/adma.201605317 · Cited by 125
Self-citationTian, H., Chen, H.-Y., Ren, T., Li, C., Xue, Q.-T., Mohammad, M., Wu, C., Yang, Y., & Wong, H. ‐. P. (2014) · Nano Letters · doi:10.1021/nl5005916 · Cited by 123
Self-citationVery Low-Programming-Current RRAM With Self-Rectifying Characteristics
Zhou, J., Cai, F., Wang, Q., Chen, B., Gaba, S., & Lu, W. D. (2016) · IEEE Electron Device Letters · doi:10.1109/led.2016.2530942 · Cited by 122
One Transistor–One Resistor Devices for Polymer Non‐Volatile Memory Applications
Kim, T., Choi, H., Oh, S., Wang, G., Kim, D., Hwang, H., & Lee, T. (2009) · Advanced Materials · doi:10.1002/adma.200803798 · Cited by 108
Resistive switching memory based on organic/inorganic hybrid perovskite materials
Liu, Y., Li, F., Chen, Z., Guo, T., Wu, C., & Kim, T. W. (2016) · Vacuum · doi:10.1016/j.vacuum.2016.05.010 · Cited by 91
Ho, C., Hsu, C.-L., Chen, C., Liu, J.-T., Wu, C.-S., Huang, C.-C., Hu, C. C., & Yang, F.-L. (2010) · Technical digest - International Electron Devices Meeting/Technical digest · doi:10.1109/iedm.2010.5703389 · Cited by 82
Tian, H., Zhao, H., Wang, X., Xie, Q., Chen, H.-Y., Mohammad, M., Li, C., Mi, W., Bie, Z., Yeh, C., et al. (2015) · Advanced Materials · doi:10.1002/adma.201503125 · Cited by 62
Self-citationUltralow Sub-1-nA Operating Current Resistive Memory With Intrinsic Non-Linear Characteristics
Gaba, S., Cai, F., Zhou, J., & Lu, W. D. (2014) · IEEE Electron Device Letters · doi:10.1109/led.2014.2363618 · Cited by 40
Ultra-low power Al2O3-based RRAM with 1μA reset current
Wu, Y., Lee, B., & Wong, H. ‐. P. (2010) · International Symposium on VLSI Technology, Systems and Applications (VLSI-TSA) · doi:10.1109/vtsa.2010.5488916 · Cited by 26
Cited by
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
A comprehensive review on emerging artificial neuromorphic devices
Zhu, J., Zhang, T., Yang, Y., & Huang, R. (2020) · Applied Physics Reviews · doi:10.1063/1.5118217 · Cited by 758
Low‐Dimensional Metal Halide Perovskite Photodetectors
Wang, H., Li, S., Liu, X., Shi, Z., Fang, X., & He, J. (2021) · Advanced Materials · doi:10.1002/adma.202003309 · Cited by 574
Wang, S., Chen, C., Yu, Z., He, Y., Chen, X., Wan, Q., Shi, Y., Zhang, D. W., Zhou, H., Wang, X., et al. (2019) · Advanced Materials · doi:10.1002/adma.201806227 · Cited by 489
Self-citationTwo-dimensional halide perovskite nanomaterials and heterostructures
Shi, E., Gao, Y., Finkenauer, B. P., Akriti, A., Coffey, A. H., & Dou, L. (2018) · Chemical Society Reviews · doi:10.1039/c7cs00886d · Cited by 445
Metadata
- Authors
- Tian, H., Zhao, L., Wang, X., Yeh, Y.-W., Yao, N., Rand, B. P., & Ren, T.-L.
- Venue
- ACS Nano
- Publisher
- American Chemical Society (ACS)
- Published
- 2017-12-11
- Volume
- 11
- Issue
- 12
- Pages
- 12247-12256
- ISSN
- 1936-0851 (ISSN-L)
- 1936-086X
- OpenAlex
- W2775001084
- Cited by
- 371
- References
- 45
- FWCI
- 15.10
- Type
- journal article
- Language
- en
- Open access
- closed
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
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.
