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Diverse spike-timing-dependent plasticity based on multilevel HfO x memristor for neuromorphic computing

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Abstract

Memristors have emerged as promising candidates for artificial synaptic devices, serving as the building block of brain-inspired neuromorphic computing. In this letter, we developed a Pt/HfO x /Ti memristor with nonvolatile multilevel resistive switching behaviors due to the evolution of the conductive filaments and the variation in the Schottky barrier. Diverse state-dependent spike-timing-dependent-plasticity (STDP) functions were implemented with different initial resistance states. The measured STDP forms were adopted as the learning rule for a three-layer spiking neural network which achieves a 75.74% recognition accuracy for MNIST handwritten digit dataset. This work has shown the capability of memristive synapse in spiking neural networks for pattern recognition application.

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References

  1. S.H. Jo, T. Chang, I. Ebong, B. Bhavitavya, P. Mazumder, W. Lu, Nano Lett. 10(4), 1297 (2010)

    Article  ADS  Google Scholar 

  2. D.S. Jeong, I. Kim, M. Ziegler, H. Kohlstedt, RSC Adv. 3(10), 3169 (2013)

    Article  Google Scholar 

  3. Y. Li, Y. Zhong, L. Xu, J. Zhang, X. Xu, H. Sun, Sci. Rep. 3, 1619 (2013)

    Article  ADS  Google Scholar 

  4. M. Prezioso, F. Merrikh-Bayat, B.D. Hoskins, G.C. Adam, K.K. Likharev, D.B. Strukov, Nature 521(7550), 61 (2015)

    Article  ADS  Google Scholar 

  5. Z. Wang, S. Joshi, S.E. Savel’ev, H. Jiang, R. Midya, P. Lin, M. Hu, N. Ge, J.P. Strachan, and Z. Li, Nat. Mater. 16(1), 101 (2017)

    Article  ADS  Google Scholar 

  6. G.Q. Bi and M.M. Poo, Annu. Rev. Neurosci. 24(1), 139 (2001)

    Article  Google Scholar 

  7. T. Serrano-Gotarredona, T. Masquelier, T. Prodromakis, G. Indiveri, and B. Linares-Barranco, Front. Neurosci. 7, 2 (2013)

    Article  Google Scholar 

  8. Y. Li, Y. Zhong, J. Zhang, L. Xu, Q. Wang, H. Sun, H. Tong, X. Cheng, and X. Miao, Sci. Rep. 4, 4906 (2014)

    Article  ADS  Google Scholar 

  9. N. Du, M. Kiani, C.G. Mayr, T. You, D. Bürger, I. Skorupa, O.G. Schmidt, and H. Schmidt, Front. Neurosci. 9, 227 (2015)

    Google Scholar 

  10. Y. Li, L. Xu, Y.-P. Zhong, Y.-X. Zhou, S.-J. Zhong, Y.-Z. Hu, L.O. Chua, and X.-S. Miao, Adv. Electron. Mater. 1(8), 1500125 (2015)

    Article  Google Scholar 

  11. Y. Yang, B. Chen, W.D. Lu, Adv. Mater. 27(47), 7720 (2015)

    Article  Google Scholar 

  12. C. Zhang, Y.-T. Tai, J. Shang, G. Liu, K.-L. Wang, C. Hsu, X. Yi, X. Yang, W. Xue, and H. Tan, J. Mater. Chem. C 4(15), 3217 (2016)

    Article  Google Scholar 

  13. Y. Shun, Y.S. Chen, J.R. Sun, and B.G. Shen, Adv. Electron. Mater. 2(4), 1500359 (2016)

    Article  Google Scholar 

  14. Z.H. Tan, R. Yang, K. Terabe, X.B. Yin, X.-D. Zhang, and X. Guo, Adv. Mater. 28(2), 377 (2016)

    Article  Google Scholar 

  15. V. Kornijcuk, O. Kavehei, H. Lim, J.Y. Seok, S.K. Kim, I. Kim, W.S. Lee, B.J. Choi, and D.S. Jeong, Nanoscale 6(24), 15151 (2014)

    Article  ADS  Google Scholar 

  16. K.A. Campbell, K.T. Drake, E. Barney Smith, Front. Bioeng. Biotechnol. 4, 97 (2016)

    Article  Google Scholar 

  17. W. Xu, S.-Y. Min, H. Hwang, T.-W. Lee, Sci. Adv. 2(6), e1501326 (2016)

    Article  ADS  Google Scholar 

  18. T. Werner, E. Vianello, O. Bichler, D. Garbin, D. Cattaert, B. Yvert, B. De Salvo, and L. Perniola, Front. Neurosci. 10 474 (2016)

    Article  Google Scholar 

  19. E. Covi, S. Brivio, A. Serb, T. Prodromakis, M. Fanciulli, and S. Spiga, Front. Neurosci. 10 482 (2016)

    Article  Google Scholar 

  20. S. Ambrogio, S. Balatti, V. Milo, R. Carboni, Z. Wang, A. Calderoni, N. Ramaswamy, D. Ielmini, in presented at the VLSI Technology, 2016 IEEE Symposium on, 2016

  21. Y. van de Burgt, E. Lubberman, E.J. Fuller, S.T. Keene, G.C. Faria, S. Agarwal, M.J. Marinella, A.A. Talin, and A. Salleo. Nat. Mater. 16(4), 414 (2017)

    Article  ADS  Google Scholar 

  22. S. Choi, J.H. Shin, J. Lee, P. Sheridan, W.D. Lu, Nano Lett. 17(5), 3113 (2017)

    Article  ADS  Google Scholar 

  23. P. Yao, H. Wu, B. Gao, S.B. Eryilmaz, X. Huang, W. Zhang, Q. Zhang, N. Deng, H.-S. Philip, and S. Wong, Nat. Commun. 8, 15199 (2017)

    Article  ADS  Google Scholar 

  24. M. Prezioso, F.M. Bayat, B. Hoskins, K. Likharev, D. Strukov, Sci. Rep. 6, 21331 (2016)

    Article  ADS  Google Scholar 

  25. S. Ambrogio, S. Balatti, V. Milo, R. Carboni, Z.-Q. Wang, A. Calderoni, N. Ramaswamy, A.S. Spinelli, D. Ielmini, Sci. Rep. 7, 5288 (2017)

    Article  ADS  Google Scholar 

  26. G. Pedretti, V. Milo, S. Ambrogio, R. Carboni, S. Bianchi, A. Calderoni, N. Ramaswamy, D. Ielmini, IEEE Trans. Electron Dev. 63(4), 1508 (2016)

    Article  ADS  Google Scholar 

  27. C.C. Hsieh, A. Roy, Y.F. Chang, D. Shahrjerdi, S.K. Banerjee, Appl. Phys. Lett. 109(22), 223501 (2016)

    Article  ADS  Google Scholar 

  28. V.V. Kaichev, E.V. Ivanova, M.V. Zamoryanskaya, T.P. Smirnova, L.V. Yakovkina, V.A. Gritsenko, Eur. Phys. J. Appl. Phys. 64(1), 10302 (2013)

    Article  ADS  Google Scholar 

  29. P.-H. Chen, T.-C. Chang, K.C. Chang, T.M. Tsai, C.-H. Pan, M.-C. Chen, Y.-T. Su, C.-Y. Lin, Y.-T. Tseng, and H.-C. Huang, ACS Appl. Mater. Interfaces 9(3), 3149 (2017)

    Article  Google Scholar 

  30. K.H. Xue, P. Blaise, L.R. Fonseca, and Y. Nishi. Phys. Rev. Lett. 110, 065502 (2013)

    Article  ADS  Google Scholar 

  31. F.-C. Chiu, Adv. Mater. Sci. Eng. (2014). https://doi.org/10.1155/2014/578168

    Google Scholar 

  32. C.-H. Pan, T.-C. Chang, T.-M. Tsai, K.-C. Chang, P.-H. Chen, S.-W. Chang-Chien, M.-C. Chen, H.-C. Huang, H. Wu, and N. Deng, Appl. Phys. Lett. 109(18), 183509 (2016)

    Article  ADS  Google Scholar 

  33. N. Panwar, B. Rajendran, U. Ganguly, IEEE Electron Device Lett. 38(6), 740 (2017)

    Article  ADS  Google Scholar 

  34. H.Y. Lee, P.S. Chen, T.Y. Wu, Y.S. Chen, C.C. Wang, P.J. Tzeng, C.H. Lin, F. Chen, C.H. Lien, and M.-J. Tsai, in presented at the Electron Devices Meeting, 2008. IEDM 2008. IEEE International, 2008

  35. S. Boyn, J. Grollier, G. Lecerf, B. Xu, N. Locatelli, S. Fusil, S. Girod, C. Carrétéro, K. Garcia, S. Xavier, J. Tomas, L. Bellaiche, M. Bibes, A. Barthélémy, S. Saïghi, V. Garcia, Nat. Commun. 8, 14736 (2016)

    Article  ADS  Google Scholar 

  36. P.U. Diehl, M. Cook, Front. Comput. Neurosci. 9, 99 (2015)

    Article  Google Scholar 

  37. F. Ponulak, A. Kasiński, Neural Comput. 22(2), 467–510 (2010)

    Article  MathSciNet  Google Scholar 

  38. Q. Yu, H. Tang, K.C. Tan, H. Li, IEEE Trans. Neural Netw. Learn. Syst. 24(10), 1539–1552 (2013)

    Article  Google Scholar 

  39. G. Srinivasan, A. Sengupta, and K. Roy, in presented at the Design, Automation & Test in Europe Conference & Exhibition, 2017. DATE 2017. IEEE International, 2017

  40. S. Sidler, A. Pantazi, S. Woźniak, Y. Leblebici, and E. Eleftheriou, in presented at the International Conference on Artificial Neural Networks, (Springer, Cham, 2017)

  41. H. Kim, S. Hwang, J. Park, B.G. Park, Nanotechnology 28(40), 405202 (2017)

    Article  Google Scholar 

  42. Y. Zeng, K. Devincentis, Y. Xiao, Z.I. Ferdous, X. Guo, Z. Yan, Y. Berdichevsky, arXiv preprint arXiv:1710.10944 (2017)

  43. D. Querlioz, O. Bichler, P. Dollfus, C. Gamrat, IEEE Trans. Nanotechnol. 12(3), 288–295 (2013)

    Article  ADS  Google Scholar 

  44. N. Zheng, P. Mazumder, IEEE Trans. Neural Netw. Learn. Syst. (2017). https://doi.org/10.1109/TNNLS.2017.2761335

  45. Y. Wang, T. Tang, L. Xia, B. Li, P. Gu, H. Yang, and Y. Xie, in presented in proceedings of the 25th edition on Great Lakes Symposium on VLSI. ACM, 2015

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Acknowledgements

This work was supported by the National Natural Science Foundation of China (Grant nos. 61504045, 51732003, 61376130), the National Key Research and Development Plan of the MOST of China (2016YFA0203800), and Wuhan Science and Technology Plan (2016010101010005).

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Authors and Affiliations

  1. School of Optical and Electronic Information, Huazhong University of Science and Technology (HUST), Wuhan, 430074, China

    Ke Lu, Yi Li, Wei-Fan He, Jia Chen, Ya-Xiong Zhou, Nian Duan, Miao-Miao Jin, Wei Gu, Kan-Hao Xue, Hua-Jun Sun & Xiang-Shui Miao

  2. Wuhan National Research Center for Optoelectronics, Huazhong University of Science and Technology, Wuhan, 430074, China

    Ke Lu, Yi Li, Wei-Fan He, Jia Chen, Ya-Xiong Zhou, Nian Duan, Miao-Miao Jin, Wei Gu, Kan-Hao Xue, Hua-Jun Sun & Xiang-Shui Miao

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  1. Ke Lu
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Correspondence to Yi Li.

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Lu, K., Li, Y., He, WF. et al. Diverse spike-timing-dependent plasticity based on multilevel HfO x memristor for neuromorphic computing. Appl. Phys. A 124, 438 (2018). https://doi.org/10.1007/s00339-018-1847-3

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