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Journal of Computational Electronics
Erschienen in: Journal of Computational Electronics 4/2017

27.10.2017 | S.I. : Computational Electronics of Emerging Memory Elements

Review of physics-based compact models for emerging nonvolatile memories

verfasst von: Nuo Xu, Pai-Yu Chen, Jing Wang, Woosung Choi, Keun-Ho Lee, Eun Seung Jung, Shimeng Yu

Erschienen in: Journal of Computational Electronics | Ausgabe 4/2017

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Abstract

A generic compact modeling methodology for emerging nonvolatile memories is proposed by coupling comprehensive physical equations from multiple domains (e.g., electrical, thermal, magnetic, phase transitions). This concept has been applied to three most promising emerging memory candidates: PCM, STT-MRAM, and RRAM to study their device physics as well as to evaluate their circuit-level performance. The models’ good predictability to experiments and their effectiveness in large-scale circuit simulation suggest their unique role in emerging memory research and development.
Vorheriger Artikel A computational study of hafnia-based ferroelectric memories: from ab initio via physical modeling to circuit models of ferroelectric device

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Literatur
1.
Yu, S., Chen, P.-Y.: Emerging memory technologies: recent trends and prospects. IEEE Solid State Circuits Mag. 8(2), 43–56 (2016)CrossRef
2.
Ovshinsky, S.R.: Reversible electrical switching phenomena in disordered structures. Phys. Rev. Lett. 21(20), 1450–1455 (1968)CrossRef
3.
Wong, H.-S.P., et al.: Phase change memory. Proc. IEEE 98(12), 2201–2227 (2010)CrossRef
4.
Lai, S.: Current status of the phase change memory and its future. In: IEEE International Electron Device Meeting (IEDM), 10.1 (2003)
5.
Burr, G.W., et al.: Overview of candidate device technologies for storage-class memory. IBM J. Res. Dev. 52(4), 449–464 (2008)CrossRef
6.
Song, Y.J., et al.: Highly reliable 256 Mb PRAM with advanced ring contact technology and novel encapsulating technology. In: IEEE symposium on VLSI technology, pp. 118–119 (2006)
7.
Tehrani, S., et al.: Magnetoresistive random access memory using magnetic tunnel junctions. Proc. IEEE 91, 703–714 (2003)CrossRef
8.
Albrecht, T.R., et al.: Bit-patterned magnetic recording: theory, media fabrication, and recording performance. IEEE Trans. Magn. 51(5), 0800342 (2015)CrossRef
9.
Slonczewski, J.C.: Current-driven excitation of magnetic multilayers. J. Magn. Magn. Mater. 159, L1–7 (1996)CrossRef
10.
Berger, L.: Emission of spin waves by a magnetic multilayer traversed by a current. Phys. Rev. B 54, 9353–9358 (1996)CrossRef
11.
Katine, J., et al.: Current-driven magnetization reversal and spin-wave excitations in Co/Cu/Co pillars. Phys. Rev. Lett. 84, 3149–3152 (2000)CrossRef
12.
Chen, E., et al.: Advances and future prospects of spin-transfer torque random access memory. IEEE Trans. Magn. 46(6), 1873–1878 (2010)CrossRef
13.
Yoda, H., et al.: Progress of STT-MRAM technology and the effect on normally-off computing systems. In: IEEE International Electron Device Meeting (IEDM), pp. 259–262 (2012)
14.
Watanabe, Y., et al.: Current-driven insulator–conductor transition and nonvolatile memory in chromium-doped SrTiO\(_{3}\) single crystals. Appl. Phys. Lett. 78, 3738–3740 (2001)CrossRef
15.
Wong, H.S.-P., et al.: Metal-oxide RRAM. Proc. IEEE 100(6), 1951–1970 (2012)CrossRef
16.
Waser, R., et al.: Nanoionics-based resistive switching memories. Nat. Mater. 6(11), 833–840 (2007)CrossRef
17.
Xu, N., et al.: Characteristics and mechanism of conduction/set process in TiN/ZnO/Pt resistance switching random-access memories. Appl. Phys. Lett. 92(23), 232112 (2008)CrossRef
18.
19.
20.
21.
Gao B., et al.: Oxide-based RRAM switching mechanism: a new ion-transport-recombination model. In: IEEE International Electron Devices Meeting (IEDM). (2008)
22.
Makarov, A., et al.: Stochastic modeling hysteresis and resistive switching in bipolar oxide-based memory. In: IEEE Simulation of Semiconductor Devices and Process (SISPAD), pp. 237–240 (2010)
23.
Lu, D.: Compact models for future generation CMOS. University of California, Berkeley, Ph.D. Thesis (2011)
24.
Simulation Program with Integrated Circuit Emphasis (SPICE), University of California, Berkeley, (1973)
25.
Toshiyoshi H., et al.: A multi-physics simulation technique for integrated MEMS. In: IEEE International Electron Devices Meeting (IEDM), pp. 123–126 (2012)
26.
An RRE is a Langevin equation without the Gaussian white noise term. Refer to P. Langevin, On the Theory of Brownian Motion, C. R. Acad. Sci., 146, pp. 530–533 (1908)
27.
28.
Ielmini, D., et al.: Analytical model for subthreshold conduction and threshold switching in chalcogenide-based memory devices. J. Appl. Phys. 102, 054517 (2007)CrossRef
29.
Ventrice, D., et al.: A phase change memory compact model for multilevel applications. IEEE Electron Dev. Lett. 28(11), 973–975 (2007)CrossRef
30.
Chen, I.-R., et al.: Compact thermal model for vertical nanowire phase-change memory cells. IEEE Trans. Electron Dev. 56(7), 1523–1528 (2009)CrossRef
31.
Xu, N., et al.: Multi-domain compact modeling for GeSbTe-based memory and selector devices and simulation for large-scale 3-D cross-point memory arrays. In: IEEE International Electron Device Meeting (IEDM), pp. 192–195 (2015)
32.
Anbarasu, M., et al.: Nanosecond threshold switching of GeTe\(_{6}\) cells and their potential as selector devices. Appl. Phys. Lett. 100, 143505 (2012)CrossRef
33.
Schmithusen, B., et al.: Phase-change memory simulations using an analytical phase space model. IEEE Simulation of Semiconductor Devices and Process (SISPAD), 3.6.1 (2008)
34.
Radaelli, A., et al.: Threshold switching and phase transition numerical models for phase change memory simulations. J. Appl. Phys. 103, 111101 (2008)CrossRef
35.
Peng, C., et al.: Experimental and theoretical investigations of laser-induced crystallization and amorphization in phase-change optical recording media. J. Appl. Phys. 82, 4183–4191 (1997)CrossRef
36.
Senkadar, S., et al.: Model for phase-change of Ge\(_{2}\)Sb\(_{2}\)Te\(_{5}\) in optical and electrical memory devices. J. Appl. Phys. 95, 504–511 (2004)CrossRef
37.
Zhang, L., et al.: One-selector one-resistor cross-point array with threshold switching selector. IEEE Trans. Electron Dev. 62(10), 3250–3257 (2015)CrossRef
38.
International Technology Roadmap for Semiconductors (ITRS), 2014 edition
39.
Kim, S.-B., et al.: Thermal disturbance and its impact on reliability of phase-change memory studied by the micro-thermal stage. In: IEEE Reliability Physics Symposium, pp. 99–103 (2010)
40.
Panagopoulos, G.D., et al.: Physics-based SPICE-compatible compact model for simulating hybrid MTJ/CMOS circuits. IEEE Trans. Electron Dev. 60(9), 2808–2814 (2013)CrossRef
41.
Fong, X.: et al.: KNACK: a hybrid spin-charge mixed-mode simulator for evaluating different genres of spin-transfer torque MRAM bit-cells. In: IEEE simulation of semiconductor devices and process (SISPAD), pp. 51–54 (2011)
42.
Kazemi, M., et al.: Adaptive compact magnetic tunnel junction model. IEEE Trans. Electron Dev. 61(11), 3883–3891 (2014)CrossRef
43.
Madec, M., et al.: Compact modeling of a magnetic tunnel junction—Part II: tunneling current model. IEEE Trans. Electron Dev. 57(6), 1416–1424 (2010)CrossRef
44.
Xu, N.: et al.: Physics-based compact modeling framework for state-of-the-art and emerging STT-MRAM technology. In: IEEE international electron device meeting (IEDM), pp. 735–738 (2015)
45.
Kim, J.-H., et al.: Verification on the extreme scalability of STT-MRAM without loss of thermal stability below 15 nm MTJ cell. In: IEEE symposium on VLSI technology, pp. 60–61 (2014)
46.
Slonczewski, J.C.: Conductance and exchange coupling of two ferromagnets separated by a tunneling barrier. Phys. Rev. B 39, 6995–7002 (1989)CrossRef
47.
Brinkman, W.F., et al.: Tunneling conductance of asymmetrical barriers. J. Appl. Phys. 41, 1915–1921 (1970)CrossRef
48.
Hiramatsu, Y., et al.: NEGF simulation of spin-transfer torque in magnetic tunnel junctions. In: IMFEDK, pp. 102–103 (2011)
49.
Zhu, Z.-G., et al.: Effect of spin-flip scattering on electrical transport in magnetic tunnel junctions. Phys. Lett. A 300, 658–665 (2002)CrossRef
50.
Beleggia, M., et al.: Demagnetization factors for elliptic cylinders. J. Phys. D 38, 3333–3342 (2005)CrossRef
51.
Khalkovski, A.V., et al.: Basic principles of STT-MRAM cell operation in memory arrays. J. Phys. D 46, 074001 (2013)CrossRef
52.
Guan, X., et al.: A SPICE compact model of metal oxide resistive switching memory with variations. IEEE Electron Dev. Lett. 33(10), 1405–1407 (2012)CrossRef
53.
Huang, P., et al.: A physics-based compact model of metal-oxide-based RRAM DC and AC operations. IEEE Trans. Electron Dev. 60(12), 4090–4097 (2013)CrossRef
54.
Bocquet, M., et al.: Robust compact model for bipolar oxide-based resistive switching memories. IEEE Trans. Electron Dev. 61(3), 674–681 (2014)CrossRef
55.
56.
Chen, Y.Y., et al.: Balancing SET/RESET pulse for endurance in 1T1R bipolar RRAM. IEEE Trans. Electron Dev. 59(12), 3243–3249 (2012)CrossRef
57.
Chen, Y.Y., et al.: Improvement of data retention in HfO\(_{2}\)/Hf 1T1R RRAM cell under low operating current. In: IEEE International Electron Devices Meeting (IEDM), pp. 252–255 (2013)
58.
Xu, N., et al.: A unified physical model of switching behavior in oxide-based RRAM. In: IEEE Symposium on VLSI Technology, pp. 100–101 (2008)
59.
Fantini, A., et al.: Intrinsic switching variability in HfO\(_{2}\) RRAM. IEEE International Memory Workshop (IMW), pp. 30–33 (2013)
60.
Yu, S., et al.: A neuromorphic visual system using RRAM synaptic devices with sub-pJ energy and tolerance to variability: experimental characterization and large-scale modeling. In: IEEE International Electron Device Meeting (IEDM), pp. 239–242 (2012)
61.
62.
Yalon, E., et al.: Thermometry of filamentary RRAM devices. IEEE Trans. Electron Dev. 62(9), 2972–2977 (2015)CrossRef
63.
Guan, X., et al.: On the switching parameter variation of metal oxide RRAM—part I: physical modeling and simulation methodology. IEEE Trans. Electron Dev. 59(4), 1172–1182 (2012)CrossRef
64.
Boniardi, M., et al.: A physics-based model of electrical conduction decrease with time in amorphous Ge\(_{2}\)Sb\(_{2}\)Te\(_{5}\). J. Appl. Phys. 105, 084506 (2009)CrossRef
65.
Chien, W.C., et al.: Reliability study of a 128 Mb phase-change memory chip implemented with doped Ga–Sb–Ge with extraordinary thermal stability. In: IEEE international electron devices meeting (IEDM), pp. 552–555 (2016)
66.
Zhang, S.: Spin hall effect in the presence of spin diffusion. Phys. Rev. Lett. 85, 393–396 (2000)CrossRef
67.
Ciocchini, N., et al.: Impact of thermoelectric effects on phase change memory characteristics. IEEE Trans. Electron Dev. 62(10), 3264–3271 (2015)CrossRef
68.
Hsu, C.W., et al.: Homogeneous barrier modulation of TaO\(_{x}\)/TiO\(_{2}\) bilayer for ultra-high endurance three-dimensional storage-class memory. Nanotechnology 25, 165202 (2014)CrossRef
Metadaten
Titel
Review of physics-based compact models for emerging nonvolatile memories
verfasst von
Nuo Xu
Pai-Yu Chen
Jing Wang
Woosung Choi
Keun-Ho Lee
Eun Seung Jung
Shimeng Yu
Publikationsdatum
27.10.2017
Verlag
Springer US
Erschienen in
Journal of Computational Electronics / Ausgabe 4/2017
Print ISSN: 1569-8025
Elektronische ISSN: 1572-8137
DOI
https://doi.org/10.1007/s10825-017-1098-0

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