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随着忆阻器研究的不断深入, 忆阻器的研究已经进入微观阶段, 包括忆阻器内部结构的探究、内部粒子间的运动规律、各参数对忆阻器特性的影响等. 然而, 这些成果中没有关于尺寸参数对忆阻器特性影响的研究, 而尺寸参数是忆阻器成功制备的关键因素之一, 这大大限制了忆阻器的发展和实际应用. 本文从欧姆电阻定律入手, 从理论角度详细分析了尺寸参数对惠普忆阻器以及自旋忆阻器的性能影响. 在此基础上进行了一系列电路仿真实验, 得到不同尺寸参数下忆阻器的相关特性曲线. 文中各选取其中最具代表性的四组实验结果进行展示, 对这些结果进行了详细分析, 得到了惠普忆阻器工作的最佳尺寸范围在8-12 nm之间以及自旋忆阻器工作的最佳尺寸范围在500-600 nm 之间的结论. 实验结果不仅可为实际运用提供有力的支持, 同时也将为进一步研制钛氧化物忆阻器器件和相关理论工作提供重要的实验基础和理论依据.According to the completeness theory of circuit, Chua [Chua L O 1971 IEEE Trans. Circ. Theor. 1971 18 507] put forward the fourth basic circuit element memristor besides resistor, inductor and capacitor in 1971. And memorisistance is defined as the ratio of the flux to the charge passing through it. With the emergence and development of nanoscale semiconductor technology, HP laboratoty successfully fabricated a physical memristor in 2008. The successful fabrication of memristive device caused a stir in the whole electronic field and thus a vast number of researchers were involved in the research, owing to its superior properties, i.e., nanoscale dimension, continuous input and output property, switching characteristics and unique non-volatile memory capacity. With all these extraordinary properties, memristors possess many possibilities for the development of future integrated circuits and analog computer. With the gradually in-depth study of memristor, memristor is being microsized, and its internal structure, motion law among its internal particles and influences resulting from the parameters are further explored. In recent years, the memristor has made significant achievement in the areas of non-volatile solid-state memory, intelligent storage, very-large-scale integrated circuitry, programmable analog circuits, and artificial neural networks. So far, the influence of size parameter on the memristor has been little studied, although the size parameter is one of the key factors in the memristor fabrication technology, which severely restricts the memristor development and its practical application. In the paper, we theoretically analyze the influences of size parameter on two practical memristor models (i.e., the HP memristor and spintronic memristor) in detail based on the Ohm’s law. On this basis, a series of circuit experimental simulation is carried out, and the corresponding memristor characteristic curves are thus obtained. Furthermore, we choose 4 most representative experimental results, and make specific analysis on them. Those results indicate that the optimal length of HP memristor is in a range from 8 nm to 12 nm, while the proper range of spintronic memristor is from 500 nm to 600 nm. The final results can not only contribute to memristor physical implementation and its applications, but also provide theoretical references and reliable experiment basis for the further development of the titanium oxide memristor devices and the relevant research.
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Keywords:
- memristor /
- length parameter /
- u-i curve /
- influence
[1] Chua L O 1971 IEEE Trans. Circ. Theor. 18 507
[2] Strukov D B, Snider G S, Stewart D R, Williams R S 2008 Nature 453 80
[3] Williams R S 2008 IEEE Spectr. 45 28
[4] Itoh M, Chua L O 2008 Int. J. Bifurc. Chaos 18 3183
[5] Chen Y R, Wang X B 2009 IEEE/ACM International Symposium on Nanoscale Architectures San Francisco, CA, USA July 30-31, 2009
[6] Chang T, Jo S H, Kim K H, Sheridan P, Gaba S, Lu W 2011 Appl. Phys. A 102 857
[7] Pickett M D, Strukov D B, Borghetti J L, Yang J J, Snider G S, Stewart D R, Williams R S 2009 Appl. Phys. 106 074508
[8] Kvatinsky S, Friedman E G, Kolodny A, Weiser U C 2013 IEEE Trans. Circ. Theor. 60 211
[9] Kim H, Sah M P, Yang C, Roska T, Chua L O 2012 IEEE Trans. Circ. Theor. 159 148
[10] Adhikari S P, Yang C, Kim H, Chua L O 2012 IEEE Trans. Neural Netw. Learn. Syst. 23 1426
[11] Hu X F, Duan S K, Wang L D 2011 Sci. China F: Inform. Sci. 41 500 (in Chinese) [胡小方, 段书凯, 王丽丹 2011 中国科学F辑:信息科学 41 500]
[12] Dong Z K, Duan S K, Hu X F, Wang L D 2014 Acta Phys. Sin. 63 128502 (in Chinese) [董哲康, 段书凯, 胡小方, 王丽丹 2014 63 128502]
[13] Snider G S 2010 Nanotechnology 22 015201
[14] Wu H G, Bao B C, Chen M 2014 Chin. Phys. B 23 118401
[15] Yu D S, Liang Y, Herbert H C I, Hu Y H 2014 Chin. Phys. B 23 070702
[16] Zhang L, Chen Z, Yang J J, Wysocki B, Mcdonald N, Chen Y R 2013 Appl. Phys. Lett. 102 153503
[17] Tian X B, Xu H, Li Q J 2014 Acta Phys. Sin. 63 048401 (in Chinese) [田晓波, 徐晖, 李清江 2014 63 048401]
[18] Xu H, Tian X B, Bu K, Li Q J 2014 Acta Phys. Sin. 63 098402 (in Chinese) [徐晖, 田晓波, 步凯, 李清江 2014 63 098402]
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[1] Chua L O 1971 IEEE Trans. Circ. Theor. 18 507
[2] Strukov D B, Snider G S, Stewart D R, Williams R S 2008 Nature 453 80
[3] Williams R S 2008 IEEE Spectr. 45 28
[4] Itoh M, Chua L O 2008 Int. J. Bifurc. Chaos 18 3183
[5] Chen Y R, Wang X B 2009 IEEE/ACM International Symposium on Nanoscale Architectures San Francisco, CA, USA July 30-31, 2009
[6] Chang T, Jo S H, Kim K H, Sheridan P, Gaba S, Lu W 2011 Appl. Phys. A 102 857
[7] Pickett M D, Strukov D B, Borghetti J L, Yang J J, Snider G S, Stewart D R, Williams R S 2009 Appl. Phys. 106 074508
[8] Kvatinsky S, Friedman E G, Kolodny A, Weiser U C 2013 IEEE Trans. Circ. Theor. 60 211
[9] Kim H, Sah M P, Yang C, Roska T, Chua L O 2012 IEEE Trans. Circ. Theor. 159 148
[10] Adhikari S P, Yang C, Kim H, Chua L O 2012 IEEE Trans. Neural Netw. Learn. Syst. 23 1426
[11] Hu X F, Duan S K, Wang L D 2011 Sci. China F: Inform. Sci. 41 500 (in Chinese) [胡小方, 段书凯, 王丽丹 2011 中国科学F辑:信息科学 41 500]
[12] Dong Z K, Duan S K, Hu X F, Wang L D 2014 Acta Phys. Sin. 63 128502 (in Chinese) [董哲康, 段书凯, 胡小方, 王丽丹 2014 63 128502]
[13] Snider G S 2010 Nanotechnology 22 015201
[14] Wu H G, Bao B C, Chen M 2014 Chin. Phys. B 23 118401
[15] Yu D S, Liang Y, Herbert H C I, Hu Y H 2014 Chin. Phys. B 23 070702
[16] Zhang L, Chen Z, Yang J J, Wysocki B, Mcdonald N, Chen Y R 2013 Appl. Phys. Lett. 102 153503
[17] Tian X B, Xu H, Li Q J 2014 Acta Phys. Sin. 63 048401 (in Chinese) [田晓波, 徐晖, 李清江 2014 63 048401]
[18] Xu H, Tian X B, Bu K, Li Q J 2014 Acta Phys. Sin. 63 098402 (in Chinese) [徐晖, 田晓波, 步凯, 李清江 2014 63 098402]
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