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Memristor based on two-dimensional titania nanosheets for multi-level storage and information processing

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Abstract

A huge amount of data requires the non-volatile memory (NVM) technology to exhibit large-capacity storage and fast calculation speed. To further solve the bottleneck of storage capacity and speed, nano-memristors based on two-dimensional (2D) layered materials are expected to realize NVM. This study proposes the fabrication of an Ag/2D-TiOx/Pt high-performance memristor device based on the 2D titania nanosheet material. The device demonstrates stable electrical characteristics under the direct current (DC) mode, including bipolar resistive switching (RS) behavior, multi-level memristive modes, and retention property. Also, it exhibits low switching voltage (0.42 V/−0.2 V), high ROFF/RON resistance ratio (105), low switching power (10−9 W/10−5 W), and fast response speed. More importantly, the device realizes information encoding and decoding through a multi-level storage performed by different compliance currents. Multiple devices are connected to the actual circuit to realize a storage function with information processing and programmable characteristics. This work provides a powerful platform for the 2D titania nanosheet application in NVM and information processing.

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References

  1. Barabási, A. L. Scale-free networks: A decade and beyond. Science 2009, 325, 412–413.

    Article  Google Scholar 

  2. Wong, H. S. P.; Salahuddin, S. Memory leads the way to better computing. Nat. Nanotechnol. 2015, 10, 191–194.

    Article  CAS  Google Scholar 

  3. Kandel, E. R. The molecular biology of memory storage: A dialogue between genes and synapses. Science 2001, 294, 1030–1038.

    Article  CAS  Google Scholar 

  4. Zidan, M. A.; Strachan, J. P.; Lu, W. D. The future of electronics based on memristive systems. Nat. Electron. 2018, 1, 22–29.

    Article  Google Scholar 

  5. Moore, G. E. Cramming more components onto integrated circuits. Electronics 1965, 38, 114–117.

    Google Scholar 

  6. Yoon, J. H.; Zhang, J. M.; Ren, X. C.; Wang, Z. R.; Wu, H. Q.; Li, Z. Y.; Barnell, M.; Wu, Q.; Lauhon, L. J.; **a, Q. F. et al. Truly electroforming-free and low-energy memristors with preconditioned conductive tunneling paths. Adv. Funct. Mater. 2017, 27, 1702010.

    Article  Google Scholar 

  7. Wu, C. X.; Kim, T. W.; Guo, T. L.; Li, F. S.; Lee, D. U.; Yang, J. J. Mimicking classical conditioning based on a single flexible memristor. Adv. Mater. 2017, 29, 1602890.

    Article  Google Scholar 

  8. Yan, X. B.; Wang, K. Y.; Zhao, J. H.; Zhou, Z. Y.; Wang, H.; Wang, J. J.; Zhang, L.; Li, X. Y.; **ao, Z. A.; Zhao, Q. L. et al. A new memristor with 2D Ti3C2Tx MXene flakes as an artificial biosynapse. Small 2019, 15, 1900107.

    Article  Google Scholar 

  9. Cheng, C. D.; Wang, Y. H.; Xu, L. Y.; Liu, K. Q.; Dang, B. J.; Lu, Y. M.; Yan, X. Q.; Huang, R.; Yang, Y. C. Artificial astrocyte memristor with recoverable linearity for neuromorphic computing. Adv. Electron. Mater., in press, DOI: https://doi.org/10.1002/aelm.202100669.

  10. Cheng, C. D.; Tiw, P. J.; Cai, Y. M.; Yan, X. Q.; Yang, Y. C.; Huang, R. In-memory computing with emerging nonvolatile memory devices. Sci. China Inf. Sci. 2021, 64, 221402.

    Article  Google Scholar 

  11. Kim, K. M.; Lee, S. R.; Kim, S.; Chang, M.; Hwang, C. S. Self-limited switching in Ta2O5/TaOx memristors exhibiting uniform multilevel changes in resistance. Adv. Funct. Mater. 2015, 25, 1527–1534.

    Article  CAS  Google Scholar 

  12. 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. Atomic structure of conducting nanofilaments in TiO2 resistive switching memory. Nat. Nanotechnol. 2010, 5, 148–153.

    Article  CAS  Google Scholar 

  13. Yuan, J. T.; Lou, J. Memristor goes two-dimensional. Nat. Nanotechnol. 2015, 10, 389–390.

    Article  CAS  Google Scholar 

  14. Ji, F. X.; Ren, X. P.; Zheng, X. Y.; Liu, Y. C.; Pang, L. Q.; Jiang, J. X.; Liu, S. Z. 2D-MoO3 nanosheets for superior gas sensors. Nanoscale 2016, 8, 8696–8703.

    Article  CAS  Google Scholar 

  15. Koppens, F. H. L.; Mueller, T.; Avouris, P.; Ferrari, A. C.; Vitiello, M. S.; Polini, M. Photodetectors based on graphene, other two-dimensional materials and hybrid systems. Nat Nanotechnol. 2014, 9, 780–793.

    Article  CAS  Google Scholar 

  16. Liu, S.; Lu, N. D.; Zhao, X. L.; Xu, H.; Banerjee, W.; Lv, H. B.; Long, S. B.; Li, Q. J.; Liu, Q.; Liu, M. Eliminating negative-SET behavior by suppressing nanofilament overgrowth in cation-based memory. Adv. Mater. 2016, 28, 10623–10629.

    Article  CAS  Google Scholar 

  17. Yalagala, B. P.; Sahatiya, P.; Kolli, C. S. R.; Khandelwal, S.; Mattela, V.; Badhulika, S. V2O5 nanosheets for flexible memristors and broadband photodetectors. ACS Appl. Nano Mater. 2019, 2, 937–947.

    Article  CAS  Google Scholar 

  18. Sheng, L. Y.; Liao, T.; Kou, L. Z.; Sun, Z. Q. Single-crystalline ultrathin 2D TiO2 nanosheets: A bridge towards superior photovoltaic devices. Mater. Today Energy 2017, 3, 32–39.

    Article  Google Scholar 

  19. Tang, K.; Wang, Y.; Gong, C. H.; Yin, C. J.; Zhang, M.; Wang, X. F.; **ong, J. Electronic and photoelectronic memristors based on 2D materials. Adv. Electron. Mater. 2022, 8, 2101099.

    Article  CAS  Google Scholar 

  20. Neto, A. C.; Guinea, F.; Peres, N. M.; Novoselov, K. S.; Geim, A. K. The electronic properties of graphene. Rev. Mod. Phys. 2009, 81, 109–162.

    Article  Google Scholar 

  21. Zhao, Q. L.; **e, Z. J.; Peng, Y. P.; Wang, K. Y.; Wang, H. D.; Li, X. N.; Wang, H. W.; Chen, J. S.; Zhang, H.; Yan, X. B. Current status and prospects of memristors based on novel 2D materials. Mater. Horiz. 2020, 7, 1495–1518.

    Article  CAS  Google Scholar 

  22. Krishnaprasad, A.; Dev, D.; Han, S. S.; Shen, Y. Q.; Chung, H. S.; Bae, T. S.; Yoo, C.; Jung, Y.; Lanza, M.; Roy, T. MoS2 synapses with ultra-low variability and their implementation in Boolean logic. ACS Nano 2022, 16, 2866–2876.

    Article  CAS  Google Scholar 

  23. Mao, J. Y.; Wu, S.; Ding, G. L.; Wang, Z. P.; Qian, F. S.; Yang, J. Q.; Zhou, Y.; Han, S. T. A van der Waals integrated damage-free memristor based on layered 2D hexagonal boron nitride. Small 2022, 18, 2106253.

    Article  CAS  Google Scholar 

  24. Hou, J. Y.; Zheng, Y. C.; Su, Y. L.; Zhang, W. K.; Hoshide, T.; **a, F. F.; Jie, J. S.; Li, Q. W.; Zhao, Z. G.; Ma, R. Z. et al. Macroscopic and strong ribbons of functionality-rich metal oxides from highly ordered assembly of unilamellar sheets. J. Am. Chem. Soc. 2015, 137, 13200–13208.

    Article  CAS  Google Scholar 

  25. Wang, K. Y.; Li, L. T.; Zhao, R. J.; Zhao, J. H.; Zhou, Z. Y.; Wang, J. J.; Wang, H.; Tang, B. K.; Lu, C.; Lou, J. Z. et al. A pure 2H-MoS2 nanosheet-based memristor with low power consumption and linear multilevel storage for artificial synapse emulator. Adv. Electron. Mater. 2020, 6, 1901342.

    Article  CAS  Google Scholar 

  26. Yan, X. B.; Pei, Y. F.; Chen, H. W.; Zhao, J. H.; Zhou, Z. Y.; Wang, H.; Zhang, L.; Wang, J. J.; Li, X. Y.; Qin, C. Y. et al. Self-assembled networked PbS distribution quantum dots for resistive switching and artificial synapse performance boost of memristors. Adv. Mater. 2019, 31, 1805284.

    Article  Google Scholar 

  27. Pan, C. B.; Ji, Y. F.; **ao, N.; Hui, F.; Tang, K. C.; Guo, Y. Z.; **e, X. M.; Puglisi, F. M.; Larcher, L.; Miranda, E. et al. Coexistence of grain-boundaries-assisted bipolar and threshold resistive switching in multilayer hexagonal boron nitride. Adv. Funct. Mater. 2017, 27, 1604811.

    Article  Google Scholar 

  28. Liu, J. Q.; Zeng, Z. Y.; Cao, X. H.; Lu, G.; Wang, L. H.; Fan, Q. L.; Huang, W.; Zhang, H. Preparation of MoS2-polyvinylpyrrolidone nanocomposites for flexible nonvolatile rewritable memory devices with reduced graphene oxide electrodes. Small 2012, 8, 3517–3522.

    Article  CAS  Google Scholar 

  29. Liu, Y. Q.; Wang, H.; Shi, W. X.; Zhang, W. N.; Yu, J. C.; Chandran, B. K.; Cui, C. L.; Zhu, B. W.; Liu, Z. Y.; Li, B. et al. Alcohol-mediated resistance-switching behavior in metal-organic framework-based electronic devices. Angew. Chem., Int. Ed. 2016, 128, 9030–9034.

    Article  Google Scholar 

  30. Ding, G. L.; Wang, Y. X.; Zhang, G. X.; Zhou, K.; Zeng, K. L.; Li, Z. X.; Zhou, Y.; Zhang, C.; Chen, X. L.; Han, S. T. 2D metal-organic framework nanosheets with time-dependent and multilevel memristive switching. Adv. Funct. Mater. 2019, 29, 1806637.

    Article  Google Scholar 

  31. Yan, X. B.; Cao, G.; Wang, J. J.; Man, M. H.; Zhao, J. H.; Zhou, Z. Y.; Wang, H.; Pei, Y. F.; Wang, K. Y.; Gao, C. et al. Memristors based on multilayer graphene electrodes for implementing a low-power neuromorphic electronic synapse. J. Mater. Chem. C 2020, 8, 4926–4933.

    Article  CAS  Google Scholar 

  32. Merced-Grafals, E. J.; Dávila, N.; Ge, N.; Williams, R. S.; Strachan, J. P. Repeatable, accurate, and high speed multi-level programming of memristor 1T1R arrays for power efficient analog computing applications. Nanotechnology 2016, 27, 365202.

    Article  Google Scholar 

  33. Yan, X. B.; Zhang, L.; Chen, H. W.; Li, X. Y.; Wang, J. J.; Liu, Q.; Lu, C.; Chen, J. S.; Wu, H. Q.; Zhou, P. Graphene oxide quantum dots based memristors with progressive conduction tuning for artificial synaptic learning. Adv. Funct. Mater. 2018, 28, 1803728.

    Article  Google Scholar 

  34. Sjöström, P. J.; Turrigiano, G. G.; Nelson, S. B. Rate, timing, and cooperativity jointly determine cortical synaptic plasticity. Neuron 2001, 32, 1149–1164.

    Article  Google Scholar 

  35. Zhou, L.; Yang, S. W.; Ding, G. Q.; Yang, J. Q.; Ren, Y.; Zhang, S. R.; Mao, J. Y.; Yang, Y. C.; Zhou, Y.; Han, S. T. Tunable synaptic behavior realized in C3N composite based memristor. Nano Energy 2019, 58, 293–303.

    Article  CAS  Google Scholar 

  36. Zucker, R. S. Calcium- and activity-dependent synaptic plasticity. Curr. Opin. Neurobiol. 1999, 9, 305–313.

    Article  CAS  Google Scholar 

  37. Zucker, R. S.; Regehr, W. G. Short-term synaptic plasticity. Annu. Rev. Physiol. 2002, 64, 355–405.

    Article  CAS  Google Scholar 

  38. Yan, X. B.; Zhao, Q. L.; Chen, A. P.; Zhao, J. H.; Zhou, Z. Y.; Wang, J. J.; Wang, H.; Zhang, L.; Li, X. Y.; **ao, Z. A. et al. Vacancy-induced synaptic behavior in 2D WS2 nanosheet-based memristor for low-power neuromorphic computing. Small 2019, 15, 1901423.

    Article  Google Scholar 

  39. McGaugh, J. L. Memory-a century of consolidation. Science 2000, 287, 248–251.

    Article  CAS  Google Scholar 

  40. Ríos, C.; Stegmaier, M.; Hosseini, P.; Wang, D.; Scherer, T.; Wright, C. D.; Bhaskaran, H.; Pernice, W. H. P. Integrated all-photonic nonvolatile multi-level memory. Nat. Photonics 2015, 9, 725–732.

    Article  Google Scholar 

  41. Irmanova, A.; James, A. P. Neuron inspired data encoding memristive multi-level memory cell. Analog Integr. Circuits Signal Process. 2018, 95, 429–434.

    Article  Google Scholar 

  42. Tan, H. W.; Liu, G.; Zhu, X. J.; Yang, H. L.; Chen, B.; Chen, X. X.; Shang, J.; Lu, W. D.; Wu, Y. H.; Li, R. W. An optoelectronic resistive switching memory with integrated demodulating and arithmetic functions. Adv. Mater. 2015, 27, 2797–2803.

    Article  CAS  Google Scholar 

  43. Huang, C. H.; Huang, J. S.; Lai, C. C.; Huang, H. W.; Lin, S. J.; Chueh, Y. L. Manipulated transformation of filamentary and homogeneous resistive switching on ZnO thin film memristor with controllable multistate. ACS Appl. Mater. Interfaces 2013, 5, 6017–6023.

    Article  CAS  Google Scholar 

  44. Chen, Y.; Liu, G.; Wang, C.; Zhang, W. B.; Li, R. W.; Wang, L. X. Polymer memristor for information storage and neuromorphic applications. Mater. Horiz. 2014, 1, 489–506.

    Article  CAS  Google Scholar 

  45. Choi, S.; Jang, S.; Moon, J. H.; Kim, J. C.; Jeong, H. Y.; Jang, P.; Lee, K. J.; Wang, G. A self-rectifying TaOy/nanoporous TaOx memristor synaptic array for learning and energy-efficient neuromorphic systems. NPG Asia Mater. 2018, 10, 1097–1106.

    Article  CAS  Google Scholar 

  46. Bayat, F. M.; Prezioso, M.; Chakrabarti, B.; Nili, H.; Kataeva, I.; Strukov, D. Implementation of multilayer perceptron network with highly uniform passive memristive crossbar circuits. Nat. Commun. 2018, 9, 2331.

    Article  Google Scholar 

  47. Cheng, L.; Li, J. C.; Zheng, H. X.; Yuan, P.; Yin, J. H.; Yang, L.; Luo, Q.; Li, Y.; Lv, H. B.; Chang, T. C. et al. In-memory hamming weight calculation in a 1T1R memristive array. Adv. Electron. Mater. 2020, 6, 2000457.

    Article  CAS  Google Scholar 

  48. Hu, S. G.; Liu, Y.; Liu, Z.; Chen, T. P.; Wang, J. J.; Yu, Q.; Deng, L. J.; Yin, Y.; Hosaka, S. Associative memory realized by a reconfigurable memristive Hopfield neural network. Nat. Commun. 2015, 6, 7522.

    Article  CAS  Google Scholar 

  49. Chang, C. F.; Chen, J. Y.; Huang, C. W.; Chiu, C. H.; Lin, T. Y.; Yeh, P. H.; Wu, W. W. Direct observation of dual-filament switching behaviors in Ta2O5-based memristors. Small 2017, 13, 1603116.

    Article  Google Scholar 

  50. Yan, X. B.; Qin, C. Y.; Lu, C.; Zhao, J. H.; Zhao, R. J.; Ren, D. L.; Zhou, Z. Y.; Wang, H.; Wang, J. J.; Zhang, L. et al. Robust Ag/ZrO2/WS2/Pt memristor for neuromorphic computing. ACS Appl. Mater. Interfaces 2019, 11, 48029–48038.

    Article  CAS  Google Scholar 

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Acknowledgements

This work was financially supported by the National key R & D plan “nano frontier” key special project (No. 2021YFA1200502) Cultivation projects of national major R & D project (No. 92164109) National Natural Science Foundation of China (Nos. 61674050 and 61874158), Special project of strategic leading science and technology of Chinese Academy of Sciences (No. XDB44000000-7), Hebei Basic Research Special Key Project (No. F2021201045), the Project of Distinguished Young of Hebei Province (No. A2018201231), the Support Program for the Top Young Talents of Hebei Province (No. 70280011807), the Hundred Persons Plan of Hebei Province (Nos. E2018050004 and E2018050003), the Supporting Plan for 100 Excellent Innovative Talents in Colleges and Universities of Hebei Province (No. SLRC2019018), outstanding young scientific research and innovation team of Hebei University (No. 605020521001), Special support funds for national high level talents (No. 041500120001) High-level Talent Research Startup Project of Hebei University (No. 521000981426), Funded by Science and Technology Project of Hebei Education Department (Nos. QN2020178 and QN2021026), Interdisciplinary Key Research Program of Natural Science of Hebei University (DXK202101), Project of Institute of Life Sciences and Green Development (521100311).

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Cao, G., Gao, C., Wang, J. et al. Memristor based on two-dimensional titania nanosheets for multi-level storage and information processing. Nano Res. 15, 8419–8427 (2022). https://doi.org/10.1007/s12274-022-4437-9

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