Incremental resistance programming of programmable metallization cells for use as electronic synapses

Mahalanabis, D.; Barnaby, Hugh; Gonzalez-Velo, Y.; Kozicki, M.; Vrudhula, Sarma; Dandamudi, Pradeep

doi:10.1016/j.sse.2014.07.002

Cited by 37 publications

(25 citation statements)

References 11 publications

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“…Memristors are promising candidates for both neuromorphic computing and next generation nonvolatile memory applications [1][2][3][4][5][6][7] because of their scalability [3,8] , 3D stacking potential [9][10][11] , and a close resemblance to the operating characteristics of synapses [1,4,7,12,13] . These applications typically require a large crossbar array of memristors, in which sneak path currents from neighboring cells during a write or read of a target cell can severely impede the proper operation of the array.…”

Section: Introductionmentioning

confidence: 99%

Anatomy of Ag/Hafnia‐Based Selectors with 10¹⁰ Nonlinearity

et al. 2017

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A novel Ag/oxide‐based threshold switching device with attractive features including ≈1010 nonlinearity is developed. High‐resolution transmission electron microscopic analysis of the nanoscale crosspoint device suggests that elongation of an Ag nanoparticle under voltage bias followed by spontaneous reformation of a more spherical shape after power off is responsible for the observed threshold switching.

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Section: Introductionmentioning

confidence: 99%

Anatomy of Ag/Hafnia‐Based Selectors with 10¹⁰ Nonlinearity

et al. 2017

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“…The spike-timing dependent plasticity (STDP) synaptic learning rule, inspired from the behavior of the biological neural system (Dayan and Abbott, 2001) and dominant in the brain, has been proposed and experimentally demonstrated with memristors acting as synapses by several groups over the past few years in many material systems, such as oxides (Yu et al, 2011; Wang et al, 2012a,b, 2016; Wu et al, 2012; Pickett et al, 2013; Mandal et al, 2014; Kim et al, 2015), chalcogenides (Li et al, 2013b; Mahalanabis et al, 2014a,b, 2016; La Barbera et al, 2015), silicon (Jo et al, 2010; Subramaniam et al, 2013), organic materials (Alibart et al, 2012; Li et al, 2013a; Cabaret et al, 2014; Luo et al, 2015), and even magnetic tunnel junctions (Krzysteczko et al, 2012). Illustrations of memristor effectiveness have also been shown in simulation and with transistor and/or complementary metal oxide semiconductor (CMOS)-based memristors (Rachmuth et al, 2011; Rose et al, 2011a,b; Cruz-Albrecht et al, 2012; Noack et al, 2015) and graphics processing units (Snider et al, 2011).…”

Section: Introductionmentioning

confidence: 99%

“…A layer of ternary GeSeAg is the ion source during operation. In contrast to other Ag-based GeSe or GeS ion-conducting device types (Mitkova and Kozicki, 2002; Kozicki and Mitkova, 2006; Kamalanathan et al, 2009; Waser et al, 2009; Wang et al, 2011; Mahalanabis et al, 2014a,b; Rajabi et al, 2015; Ielmini and Waser, 2016), no photodoping or thermal annealing steps are required, simplifying the fabrication steps, and producing more consistent device operation. These differences also enable the device used in this work to withstand higher fabrication (at least 300°C) and operating temperatures (operation at 150°C is routinely performed).…”

Section: Introductionmentioning

confidence: 99%

Pulse Shape and Timing Dependence on the Spike-Timing Dependent Plasticity Response of Ion-Conducting Memristors as Synapses

Campbell

Drake

Smith

2016

Front. Bioeng. Biotechnol.

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Ion-conducting memristors comprised of the layered materials Ge2Se3/SnSe/Ag are promising candidates for neuromorphic computing applications. Here, the spike-timing dependent plasticity (STDP) application is demonstrated for the first time with a single memristor type operating as a synapse over a timescale of 10 orders of magnitude, from nanoseconds through seconds. This large dynamic range allows the memristors to be useful in applications that require slow biological times, as well as fast times such as needed in neuromorphic computing, thus allowing multiple functions in one design for one memristor type—a “one size fits all” approach. This work also investigated the effects of varying the spike pulse shapes on the STDP response of the memristors. These results showed that small changes in the pre- and postsynaptic pulse shape can have a significant impact on the STDP. These results may provide circuit designers with insights into how pulse shape affects the actual memristor STDP response and aid them in the design of neuromorphic circuits and systems that can take advantage of certain features in the memristor STDP response that are programmable via the pre- and postsynaptic pulse shapes. In addition, the energy requirement per memristor is approximated based on the pulse shape and timing responses. The energy requirement estimated per memristor operating on slower biological timescales (milliseconds to seconds) is larger (nanojoules range), as expected, than the faster (nanoseconds) operating times (~0.1 pJ in some cases). Lastly, the memristors responded in a similar manner under normal STDP conditions (pre- and post-spikes applied to opposite memristor terminals) as they did to the case where a waveform corresponding to the difference between pre- and post-spikes was applied to only one electrode, with the other electrode held at ground potential. By applying the difference signal to only one terminal, testing of the memristor in various applications can be achieved with a simplified test set-up, and thus be easier to accomplish in most laboratories.

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“…PMC also shows promise beyond von-Neumann computing. 17 Still early in its development, and with clear prospects for scaling down, PMC performance is likely to improve significantly in next-generation devices.…”

Section: Introductionmentioning

confidence: 99%

Reversible migration of silver on memorized pathways in Ag-Ge40S60 films

et al. 2015

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Reversible and reproducible formation and dissolution of silver conductive filaments are studied in Ag-photodoped thin-film Ge 40 S 60 subjected to electric fields. A tip-planar geometry is employed, where a conductive-atomic-force microscopy tip is the tip electrode and a silver patch is the planar electrode. We highlight an inherent "memory" effect in the amorphous chalcogenide solid-state electrolyte, in which particular silver-ion migration pathways are preserved "memorized" during writing and erasing cycles. The "memorized" pathways reflect structural changes in the photodoped chalcogenide film. Structural changes due to silver photodoping, and electrically-induced structural changes arising from silver migration, are elucidated using Raman spectroscopy. Conductive filament formation, dissolution, and electron (reduction) efficiency in a lateral device geometry are related to operation of the nano-ionic Programmable Metallization Cell memory and to newly emerging chalcogenide-based lateral geometry MEMS technologies. The methods in this work can also be used for qualitative multi-parameter sampling of metal/amorphous-chalcogenide combinations, characterizing the growth/dissolution rates, retention and endurance of fractal conductive filaments, with the aim of optimizing devices. C 2015 Author(s). All article content, except where otherwise noted, is licensed under a Creative Commons Attribution 3.0 Unported License.

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Incremental resistance programming of programmable metallization cells for use as electronic synapses

Cited by 37 publications

References 11 publications

Anatomy of Ag/Hafnia‐Based Selectors with 10¹⁰ Nonlinearity

Anatomy of Ag/Hafnia‐Based Selectors with 10¹⁰ Nonlinearity

Pulse Shape and Timing Dependence on the Spike-Timing Dependent Plasticity Response of Ion-Conducting Memristors as Synapses

Reversible migration of silver on memorized pathways in Ag-Ge40S60 films

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Incremental resistance programming of programmable metallization cells for use as electronic synapses

Cited by 37 publications

References 11 publications

Anatomy of Ag/Hafnia‐Based Selectors with 1010 Nonlinearity

Anatomy of Ag/Hafnia‐Based Selectors with 1010 Nonlinearity

Pulse Shape and Timing Dependence on the Spike-Timing Dependent Plasticity Response of Ion-Conducting Memristors as Synapses

Reversible migration of silver on memorized pathways in Ag-Ge40S60 films

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Anatomy of Ag/Hafnia‐Based Selectors with 10¹⁰ Nonlinearity

Anatomy of Ag/Hafnia‐Based Selectors with 10¹⁰ Nonlinearity