Processes and Limitations during Filament Formation and

The SET and RESET switching kinetics of Ag–GeSx-based ECM memory ... (1) But ultimate physical size limitations set a barrier for an ever-continuing...
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Processes and Limitations during Filament Formation and Dissolution in GeSx‑based ReRAM Memory Cells Jan van den Hurk,† Stephan Menzel,‡ Rainer Waser,†,‡ and Ilia Valov*,‡ †

Institut für Werkstoffe der Elektrotechnik II, RWTH Aachen University, 52074 Aachen, Germany Peter Grünberg Institut 7, Forschungszentrum Jülich GmbH, 52425 Jülich, Germany

‡

ABSTRACT: The SET and RESET switching kinetics of Ag−GeSx-based ECM memory cells are experimentally investigated. The results were qualitatively and quantitatively reproduced by our simulation model, accounting for a tunneling gap between the tip of the growing filament and the active electrode. Key processes are the nucleation, the electron transfer at the interfaces, and ionic hopping in the electrolyte. Current−voltage sweeps and pulse measurements were used to study the switching kinetics with respect to variety of factors like voltage, current, resistance, time, electrolyte thickness, and stoichiometry. Multilevel operations through the adjustability of the ON resistance by current compliance and sweep rate were confirmed. The SET kinetics for low voltages was limited by the nucleation process. SET time and SET voltage strongly depend on the Ag-ion normalized concentration in the electrolyte. The RESET behavior was mostly independent of the current compliance and the ON resistance. However, lower ON resistances require higher RESET currents but at the same time the RESET time was independent of the ON resistance for nearly 2 orders of magnitude. By pulsed measurements of the RESET kinetics two voltage ranges in the RESET time versus RESET voltage behavior were identified for the first time. Limiting factors in these two ranges were found to be the electron transfer and the ion migration for low and high voltages, respectively.

1. INTRODUCTION

In this work, we present extended analysis and modeling of SET and RESET switching kinetics in Ag−GeSx-Pt-type ECM memory cells during I−V sweeps and pulse measurements. We provide a detailed discussion focused on the RESET process, and its rate-limiting step as a function of the chemical composition and operation conditions. Beyond the investigation of the memory device behavior in the voltage, current, resistance, and time domain, we additionally studied the influence of the electrolyte’s thickness on the switching kinetics of the aforementioned parameters. Furthermore, we adapted the recently developed simulation model17 to offer an interpretation of the underlying physicochemical processes during both SET and RESET and the resulting limitations.

Memory architectures face the same scaling trend for better performance, lower energy consumption, and lower cost as all other electronic circuits try to follow Moore’s law as selffulfilling prophecy.1 But ultimate physical size limitations set a barrier for an ever-continuing miniaturization and redox-based resistively switching elements (ReRAM) are most likely to replace nowadays FLASH memory and possibly also DRAM devices according to the International Technology Roadmap for Semiconductors (ITRS) by using alternative architectures and materials.2−4 Ag/GeSx-based electrochemical metallization (ECM) memory cells have proven to exhibit promising characteristics in the class of ReRAM devices and are usable in complementary resistive switch (CRS) devices for application in high-density memory and logic architectures, too.5−14 ECM memory cells feature nonlinear switching kinetics that are essential to overcome the voltage−time dilemma. This includes SET duration in the nanosecondregime at reasonably high SET voltage pulses and at the same time adequate data retention times, whereas the memory cell is read by a voltage pulse that is as small and short as possible. The switching kinetics of ECM memory cells is commonly explained by the voltage-driven formation and dissolution of a conducting metal filament. In both events, different physicochemical processes (steps) are involved and may become rate-limiting. Previous work gave a first insight into the ultrafast switching kinetics for SET operations as well as into the exceptionally large ROFF to RON ratio.15,16 However, a detailed study of the RESET kinetics/mechanism is still missing so far. © 2015 American Chemical Society

2. EXPERIMENTAL SECTION 2.1. Sample Preparation. The sample devices (Ag/GeSx/ Pt-configuration) in this study use Ag and Pt as active and counter electrodes, respectively and GeSx films as solid electrolyte. A key deposition technique for preparation of GeSx with variable stoichiometry was RF sputtering. The GeSx thin-films were deposited with S to Ge ratios of 1.6, 1.9, and 2.2. The stoichiometries were adjusted by variation of the chamber pressure during the RF sputtering. Details on the manufacturing are provided in previous studies.11,18 A planar design and a microcrossbar design were used as two different stack constructions in this study. The planar design Received: April 15, 2015 Revised: June 28, 2015 Published: July 16, 2015 18678

DOI: 10.1021/acs.jpcc.5b03622 J. Phys. Chem. C 2015, 119, 18678−18685

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The Journal of Physical Chemistry C was produced on platinized Si ⟨100⟩ wafers with a full GeSx thin film and a structurized Ag electrode with a Pt protection layer (base area: 10 μm × 10 μm). The electrodes were structured by a lithographical lift-off process. The microcrossbar design’s bottom electrode was produced as a 50 nm thick and 2 μm wide Pt finger, acting as the inert electrode in the ECM cell. The active electrode was fabricated as a 50 nm thick and 2 μm wide Ag finger perpendicular to the bottom electrode, resulting in a cross-point area of 4 μm2. The Ag electrode was covered with a 50 nm film of Pt for protection. The GeSx thin-film was placed between the inert electrode and the active electrode. Ion beam etching was used to structure the inert electrode at the bottom of the stacks, whereas the contact hole in the GeSx thinfilm and the topmost active electrode were structured by a lithographical lift-off process. Dimensions and stoichiometry deviating from these specifications are individually described in the text. 2.2. Electrical Characterization. All measurements were performed in a four-needle electrode microprobe station equipped with coaxial probes, micromanipulators, and an optical microscope. A Keithley 6430 Sub-Femtoamp Remote SourceMeter was used for the current−voltage (I−V) sweep measurements. The pulse measurements were conducted in the same probe station and the pulses were generated with a Wavetek 395 100 MHz Arbitrary Waveform Generator. A Tektronix TDS 684A oscilloscope with input impedance set to 50 Ω was used to record the high-speed voltage measurements. A two stage transimpedance amplifier was used as a current-tovoltage converter with a transimpedance gain of 260. After fabrication, the memory cells need a forming step to exit the very high initial HRS in the GΩ-range. This initialization can be achieved by applying several positive voltage pulses/sweeps to switch the memory cell to an LRS and subsequently negative voltage pulses/sweeps to RESET the cell back to HRS.

Figure 1. Schematic of the switching model with equivalent circuit diagram. A switching layer of thickness L is sandwiched between the active top electrode and the inert bottom electrode. A cylindrical filament (the form is arbitrarily chosen for simplicity) grows within the electrolyte film and modulates the tunneling gap x between the filament and the active electrode. In the switching layer, both ionic and electronic current paths are present, respectively. This figure is a reworked version.17 (Reproduced by permission of the PCCP Owner Societies.)

where MAg is the silver atomic mass, z is the Ag ion charge number, and ρm,Ag is the silver mass density. The ionic current density can be calculated using the equivalent circuit diagram. The voltage controlled currents represent the electron transfer reactions at the metal/switching layer interfaces (active electrode/electrolyte and filament/electrolyte, respectively) and the ionic hopping current with the corresponding voltage drops Δφac, Δφfil, and Δφhop, respectively. The net current due to the electron transfer reaction at the filament/switching layer and the active electrode/switching layer interface is calculated using the Butler−Volmer equation

3. SIMULATION MODEL To analyze the results of the switching kinetics experiments we used the simulation model introduced by Menzel et al.17 The corresponding equivalent circuit diagram is shown in Figure 1. In this model, a cylindrical filament with area Afil is considered that grows from the inert electrode toward the active electrode. The state variable that describes this dynamic process is the tunneling gap x between the tip of the growing filament and the active electrode. The corresponding tunneling current is calculated according to ITu = C

⎡ ⎛ (1 − α)ze ⎞ ⎛ αze ⎞⎤ Ifil/ac = ±j0,et ⎢exp⎜ Δφfil/ac⎟ − exp⎜ − Δφfil/ac⎟⎥A fil/ac ⎢⎣ ⎝ kBT k T ⎠ ⎝ B ⎠⎥⎦

(3)

Here, kB denotes the Boltzmann constant, T is the temperature, and α is the charge transfer coefficient. The areas Afil and Aac describe the effective interface areas involved in the electron transfer reaction. By geometric considerations, it follows that Afil < Aac. This geometric asymmetry in combination with a charge transfer coefficient differing from the classical α = 0.5 leads to an asymmetry in the SET/RESET current.21 The exchange current density j0.et in eq 3 depends on the ion concentration c, the activation barrier ΔG≠et, and a rate constant k0,et according to

3 2meff ΔW0 ⎛ e ⎞2 ⎛ 4πx ⎞ ⎜ ⎟ exp⎜ − 2meff ΔW0 ⎟A fil VTu ⎝h⎠ ⎝ h ⎠ 2x (1)

⎛ ΔG≠ ⎞ j0,et = zeck 0,et exp⎜⎜ − et ⎟⎟ ⎝ kBT ⎠

Here, meff denotes the electron mass within the switching layer, ΔW0 is the tunneling barrier height, e is the electronic charge, h is Planck’s constant, and a fitting factor C = 2.9.19 On the basis of simulations, it was suggested that a tunneling gap remains after the SET operation corresponding to the used current compliance.19,20 In this way, multilevel switching observed in the sweep measurements is explained by a variation of the tunneling gap. The growth/dissolution of the filament is modeled according to Faraday’s law MAg ∂x =− j ∂t zeρm,Ag ion

(4)

The ionic hopping current is modeled using the Mott − Gurney law ⎛ ΔG ≠ ⎞ ⎛ ⎞ hop ⎟sinh⎜ aze E⎟Ahop Ihop = 2zecaf exp⎜⎜ − ⎟ ⎝ 2kBT ⎠ ⎝ kBT ⎠

(5)

and depends on the attempt frequency f, the hopping barrier ΔG≠hop, the hopping distance a, the effective area Ahop, and the electric field E = Δφhop/x. By solving the equation system eqs

(2) 18679

DOI: 10.1021/acs.jpcc.5b03622 J. Phys. Chem. C 2015, 119, 18678−18685

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The Journal of Physical Chemistry C 1−5, the dynamics of the filament growth/dissolution can be simulated. Prior to the filamentary growth in the SET operation, a stable nucleus has to be formed. The corresponding nucleation time depends on the overpotential Δφnuc and is calculated according to ⎛ ΔG ≠ ⎞ ⎛ (N + α)ze ⎞ nuc ⎟⎟exp⎜ − c Δφnuc⎟ tnuc = t0,nuc exp⎜⎜ kBT ⎠ ⎝ kBT ⎠ ⎝

(6)

Here, Nc gives the number of Ag atoms in the critical nucleus. Further parameters are the prefactor t0,nuc and the activation energy ΔG≠nuc. Detailed analysis of the nucleation-controlled kinetics has been published by Valov et al.22 To calculate the nucleation time during voltage sweeps we divided the voltage sweep into discrete intervals i with a constant stepwise voltage level Vi and a duration ti. For every voltage, we calculated to which part the nucleation process is completed as pi = ti/tnuc(Vi). By summing up all pi until the sum equals 1, tnuc can be determined. The parameters used for the simulation of the SET and RESET kinetics of Ag/GeSx/Pt cells are provided in Table 1. Table 1. Simulation Model Parameters symbol

value

symbol

value

MAg Z ρm,Ag mr ΔW0 A k0,et ΔG≠et f a ΔG≠hop

1.79 × 10−22 g 1 10.49 g/cm3 0.2 2.7 eV 0.2 5.4 × 103 m/s 0.48 eV 4.1 × 1012 Hz 0.3 nm 0.14 eV

ΔG≠nuc t0,nuc C Nc Aac Afil Ais L ρAg Rel Rs

0.69 eV 1.5 × 10−10 s to 2.5 × 10−7 s 2.5 × 1021 m−3 to 4 × 1028 m−3 1−2 804.25 nm2 12.57 nm2 12.57 nm2 70 nm 1.7 × 10−8 Ωm 76.4 mΩ 0

Figure 2. (a) I−V multilevel switching measurements as a function of the current compliance ICC (1−250 μA, sweep rate ν = 0.3125 V/s). The planar cell design was based upon 70 nm GeSx and a base area of 10 μm × 10 μm. (b) ON resistance RON versus current compliance ICC of 2 μm × 2 μm crossbar ECM cells with 70 nm GeS2.2.

Please note that the concentration of Ag ions c depends strongly on the deposition conditions and aging effects. In addition, the nucleation prefactor t0,nuc and Nc depend on the concentration and the experimental conditions. Consequently, those parameters were adapted for the different experimental studies. The parameters were chosen to fit the experimental data, nevertheless the values are physically justified. The SET and RESET times in the simulation were defined as follows. The SET switching time was defined as the point in time at which the current compliance was reached. As the current jump was very steep, the SET time was almost independent of the exact current compliance value and also on the parameters defining the tunneling current: tunneling barrier height and effective electron mass. In contrast, the RESET time was correlated to a current drop of 3 orders of magnitude.

constant for the different values of ICC. With 2 μm × 2 μm crossbar ECM cells, the ON resistance was calculated as RON = VRESET/IRESET and plotted versus the used current compliance ICC. The results are presented in Figure 2b. The ON resistances can be tuned by the current compliance over 2 orders of magnitude, although ON states that were switched by a current compliance of ICC < 1 μA tended to be unstable in steady state, that is, the measured resistance values remained stable only for a few seconds and finally reverted back to an HRS. The possible reason for this steady state instability was identified in the structural nature of the filament where a resistance below ∼12.9 kΩ can only be explained by taking into account the aforementioned tunneling contact between the filament’s tiny tip and the active electrode. This potentially fragile structure can be easily dissolved by a multitude of processes/reactions. The average values in the log−log plot of Figure 2b (red points) could be fitted in two ranges by the power function RON = aICCb. For low resistances (about 900 Ω and lower) a = 13.984 V/A1−b and b = −0.451 and for high resistances (about 6 kΩ and higher) a = 0.09262 V/A1−b and b = −0.96881. In Figure 3a, five I−V sweeps using the same CC but performed with different sweep rates ν are given. The different slopes around the origin show that beside the current compliance also the sweep rate can be used to control the

4. RESULTS AND DISCUSSION 4.1. SET Kinetics. The SET kinetics of ECM memory cells can be widely controlled during I−V measurements by the sweep rate and the ON resistance by adjusting the current compliance. A typical example of the switching behavior of Ag− GeSx-based memory cell is illustrated in Figure 2a. The memory cell is SET by a positive voltage sweep up to 500 mV and subsequently RESET by a negative voltage sweep down to −1 V. The slopes of the I−V sweeps within the linear Ohmic regime gave an indication that the ON resistance is not 18680

DOI: 10.1021/acs.jpcc.5b03622 J. Phys. Chem. C 2015, 119, 18678−18685

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The growth of the filament itself is solely determined by the electron transfer reactions but the nucleation is much slower and therefore, determining the switching time. Thus, previously published results, which are reported to have similar SET kinetics6,25−27 should be interpreted in the same way and are most likely also limited by nucleation processes. Pulse measurement data of the SET time tSET versus low pulse voltages VSET as depicted in Figure 4a give an insight into the mechanism of loss of data retention of Ag−GeSx-based ECM memory cells with respect to read voltage. In contrast to (for example) Ag-SiO2-based memory cells, we have no indication that a critical SET voltage or threshold voltage exists in GeSx systems. Nevertheless, we additionally noticed a

Figure 3. Planar design with 70 nm GeSx and a base area of 10 μm × 10 μm. (a) Exemplary I−V measurements with sweep rates ν from 0.02 to 10 V/s, constant step-width of 5 mV and maximum voltage of 350 mV. (b) Summary of the SET voltages VSET versus sweep rate ν at different GeSx stoichiometries. Simulation result is given as solid line.

ON resistance.19,23,24 Lower sweep rates gave lower ON resistances as the time for a full positive voltage sweep was longer and more charge to build up the filament was transported through the cell. In pulse measurements, a longer SET time would be the respective factor. Furthermore, the SET voltage VSET increased with increasing sweep rate. This result is presented in Figure 3b for sweep rates ν from 0.02 to 10 V/s and for three different stoichiometries x = 1.6, 1.9, and 2.2 of GeSx. At a sweep rate of 0.02 V/s, the average SET voltage was about 0.15 V and increased exponentially for 10 V/s to about 0.2 V. Meanwhile, the stoichiometry of the solid electrolyte had no pronounced effect on the SET voltage in this case. The reason for the sweep rate dependence of the SET voltage can be found as discussed above in the duration of the voltage sweep and the corresponding charge, as the formation of a filament needs a certain amount of material in the form of Ag+ions. In contrast, if the sweep rate is high a higher voltage of the sweep is required for the SET process. With the introduced simulation model, we were able to accurately replicate this relationship. The simulation results (fits) are shown as black solid line in Figure 3b. From an indepth analysis of the simulated transient overpotentials, we were able to conclude that the SET time and therefore the SET voltage in this voltage regime is predominantly limited by the nucleation process. For example, at 0.01 V/s the nucleation process takes 13.5 s compared to 4 ms for the growth of the filament. Also at 10 V/s, the nucleation process is with 21 ms considerably slower that the growth of the filament with 2 ms.

Figure 4. (a) SET times tSET during pulse measurements with small constant voltages VSET of planar ECM cells (70 nm GeS2.2, base area 10 μm × 10 μm). (b) SET voltage VSET versus electrolyte (GeS1.6) thickness d during I−V measurements (sweep rate ν = 0.3125 V/s) in planar ECM cells. (c) Semilog plot of SET time tSET versus electrolyte (GeS2.2) thickness d during pulse measurements (VSET ≈ 2 V) in 2 μm × 2 μm microcrossbar ECM cells. The stoichiometry has been shown to have no influence on the switching characteristics.18 Simulation results are shown as solid lines. 18681

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The Journal of Physical Chemistry C growing stochastic component of the switching behavior for SET voltages below 200 mV reflecting physical and chemical forces contributing along with the applied voltage, thus masking a possible threshold. Our simulations have shown that the SET kinetics in this type of ECM device can be modeled according to the equivalent circuit model as given in Figure 1. Nucleation and growth of the filament are the key limiting factors during the switching process. At small voltages, mainly the nucleation, that is, stochastic in nature, limits the SET process. The SET kinetics was further investigated by sweep and pulse measurements to decipher the influence of the electrolyte thickness on the switching performance. Figure 4b shows a decreasing SET voltage VSET and Figure 4c shows a decreasing SET time tSET for decreasing electrolyte thicknesses. A reduction of the electrolyte thickness by a factor of 5 gives a reduction of the SET time by 6 orders of magnitude, which underlines the potential of Ag−GeSx-based ReRAM applications, when the memory cells are shrunk to industry standard dimensions of a few nanometers. Our results extend earlier work by Jameson et al. where a change of the GeS2 thickness from 40 to 12 nm decreased the SET time by 3 orders of magnitude.6 As a crucial factor, we consider the amount of Agions (per electrolyte volume) that is dissolved within the GeSx. The dependence of the SET behavior on the electrolyte’s thickness was satisfactorily modeled by assuming an exponential change of the Ag ion concentration versus the electrolyte’s thickness. This change in concentration is also influenced by the fabrication procedure used for these experiments. While the electrolyte’s thickness was changed as described above, the Ag thickness was kept constant at 50 nm and consequently the Ag ion concentration (per volume GeSx) was lower for thicker electrolytes (at the same period of time). The exponential change of concentration (considered from the Ag/GeSx surface) was explained by our earlier work on the dissolution of Ag in GeSx-based ECM cells, where additional details on the mechanism of this process is given.11,28 We found that the switching by sweep measurements at low voltages (Figure 4b) is again limited by the nucleation processes. Interestingly, the samples with 100 nm GeS1.6 showed in the simulation a nucleation time of 0.6 s and a growth time of the filament of 1 s most probably due to the significantly lower Ag ion concentration in the electrolyte. In the case of pulse measurements at higher voltages (Figure 4c), nucleation did not play a decisive role anymore. In fact, we discovered from the analyses of the simulation results that the ion hopping process was a significant limiting factor in the formation of the filament. 4.2. RESET Kinetics. We investigated the RESET kinetics in I−V sweeps and pulsed operation. The RESET voltages were extracted from the I−V measurements, in accordance with our previous work, that is, the voltage position of the RESET current peak. The RESET voltage is plotted versus the current compliance ICC in Figure 5a. Compared to previously published results,10 the RESET voltage seems to be more or less independent of the current compliance ICC (and equivalently the ON resistance RON) whereas at the utmost only a slight increase of VRESET at higher current compliances was measured. In contrast to this finding, there was a strong dependence of the RESET current IRESET versus the current compliance ICC as shown in Figure 5b. An increase of the current compliance ICC (and equivalently a lower ON resistance RON) leads to a higher RESET current IRESET. This is not surprising and was measured before taking into account the results presented in Figure 2b

Figure 5. I−V measurements of 2 μm × 2 μm crossbar ECM cells with 70 nm GeS2.2. (a) Log−log plot of RESET voltage VRESET versus current compliance ICC. (b) Log−log plot of RESET current IRESET versus current compliance ICC. (c) Log−log plot of RESET voltage VRESET versus RESET current IRESET.

where increasing the current compliance leads to lower ON resistances. A lower ON resistance allows for higher currents during the RESET operation until the filament’s contact is ruptured and finally the filament is dissolved. A temperature effect during the initial breakup of the filament was proposed before as a possible explanation, but later in this work we are able to show that the full retraction of the filament must happen through other processes.29 While we did not find a pronounced dependence of the RESET voltage VRESET on the current compliance ICC, we investigated the dependence of VRESET on the RESET current IRESET (Figure 5c). The reset voltage is plotted over the RESET 18682

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The Journal of Physical Chemistry C current for different current compliances. To maintain clarity, only a selection of current compliances was plotted. We observed that the RESET current scales linearly with the RESET voltage for all current compliances. The RESET kinetics was also investigated in the pulsed operation regime. The correlations between applied RESET voltage, RESET time, and ON resistance were worked out by this type of experiment. As expected, RESET times in the seconds range were observed for applied RESET voltages below 100 mV. We used the measurement setup for I−V measurements for this low voltage regime.30 Prior to each experiment, the cells were switched to an ON state by using an I−V sweep and a current compliance of 50 μA to create equal preconditions. For higher voltages, the pulse measurement setup was used, where the switching to an ON state was achieved by applying a voltage pulse of 2 V for one second. However, the measured ON resistances spread from about 500 Ω to 50 kΩ, which is discussed later on. For each particular measurement, the respective RESET voltage was applied and the RESET time, defined as the duration from the start of the voltage pulse until the ECM cell switched from the ON to an OFF state, was recorded. This RESET was defined as a change of the cell’s resistance by several orders of magnitude. Compared to previous experiments10 the RESET voltage range was significantly extended to −10 mV as the upper limit and to −5 V as the lower voltage limit. Figure 6a shows the relationship between ON resistance RON and RESET time tRESET for different RESET voltages. For complete RESET voltages below −200 mV, the RESET time was in the range of seconds, for example, up to 500 s for a RESET voltage of −10 mV. RESET voltages of −1 to −5 V resulted in RESET times in the millisecond to nanosecond regime, respectively. Generally by increasing the RESET voltage, the RESET time decreases rapidly. A doubling of the RESET voltage leads to a reduction of the RESET time by 3 orders of magnitude. However, the ON resistance RON has no prominent influence on the RESET time tRESET. This result matches the analytical model for ECM memory cells by Menzel et al. where the RESET voltage in I−V measurements depends solely on the material parameters and the sweep rate.19 The model picture is in general also valid for pulsed measurements as the sweep rate in quasi-static measurements translates to pulse duration. A temperature effect during the full dissolution of the filament cannot be concluded from these measurement results. Taking into account the discussion above, we further evaluated the RESET kinetics by analyzing the RESET time tRESET versus RESET voltage VRESET dependence independent of the ON resistance as shown in Figure 6b. The results of the pulse measurements show a very distinct nonlinearity with 2 orders of magnitude in RESET voltage and about 7 orders of magnitude in RESET time. Furthermore, it was possible to identify two regimes, one low voltage regime up to roughly −200 mV and one high voltage regime from −1 V and higher. For the low voltage regime, it has to be taken into account that due to the low applied voltage external influences, for example, thermal effects or the inevitable electromotive force Vemf in ECM, memory cells can switch the memory cell spontaneously.24,31 Thus, the low voltage RESET times of the Ag− GeSx system itself are most probably slightly higher than measured in our experiment. We succeeded to reconstruct the experimentally observed nonlinear behavior with our simulation model. In the low

Figure 6. Pulse measurements of 2 μm × 2 μm microcrossbar memory cells with 70 nm GeSx (a) Log−log plot of RESET time tRESET versus ON resistance RON for different RESET voltages VRESET. (b) Semilog plot of RESET time tRESET versus RESET voltage VRESET. Error bars for VRESET > −100 mV have been removed for clarity. Simulation result is given as solid line.

voltage regime described above, the RESET process is limited mainly by the electron transfer reactions. With increasing voltage, ion migration becomes a substantial factor of the RESET kinetics and finally limits the RESET process. It is noteworthy that we used the same parameter values for the RESET kinetics from Table 1 that were used for the SET kinetics. Our model is based on the assumption that the filament is completely dissolved during the RESET process. This has been verified by switching experiments where we see kinetics limitation by nucleation during a subsequent SET after a RESET step. This would not happen if the filament is incompletely dissolved during RESET. The remaining residual filament is possible in the case of very short RESET pulses as used for volatile switching in ReRAM, where we would expect a pure migration limitation.14 However, such a residual filament is unstable within the solid electrolyte and dissolves quickly.28,31

5. CONCLUSIONS In this work, we studied in detail the SET and RESET switching kinetics in Ag−GeSx-based ECM memory cells and applied our simulation model. We were able to confirm the adjustability of the ON resistance during SET operations by a current compliance and by a sweep rate, which is the basis for a 18683

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Ag/GeS2/W Conductive-Bridge Memory Cells. IEEE Electron Device Lett. 2012, 33, 257−259. (9) Jameson, J.; Blanchard, P.; Cheng, C.; Dinh, J.; Gallo, A.; Gopalakrishnan, V.; Gopalan, C.; Guichet, B.; Hsu, S.; Kamalanathan, D.; et al. Conductive-bridge memory (CBRAM) with Excellent HighTemperature Retention. In Electron Devices Meeting (IEDM), 2013 IEEE International; Electron Devices Meeting (IEDM); IEEE International: Bellingham, WA, 2013; pp 738−741. (10) Kamalanathan, D.; Russo, U.; Ielmini, D.; Kozicki, M. N. Voltage-Driven On-Off Transition and Tradeoff With Program and Erase Current in Programmable Metallization Cell (PMC) Memory. IEEE Electron Device Lett. 2009, 30, 553−555. (11) Cho, D.-Y.; Valov, I.; van den Hurk, J.; Tappertzhofen, S.; Waser, R. Direct Observation of Charge Transfer in Solid Electrolyte for Electrochemical Metallization Memory. Adv. Mater. 2012, 24, 4552−4556. (12) Vianello, E.; Molas, G.; Longnos, F.; Blaise, P.; Souchier, E.; Cagli, C.; Palma, G.; Guy, J.; Bernard, M.; Reyboz, M.; et al. Sb-doped GeS2 as performance and reliability booster in Conductive Bridge RAM. In Electron Devices Meeting (IEDM), 2012 IEEE International; Electron Devices Meeting (IEDM); IEEE International: Bellingham, WA, 2012; pp 31.5.1−31.5.4. (13) van den Hurk, J.; Havel, V.; Linn, E.; Waser, R.; Valov, I. Ag/ GeSx/Pt-based Complementary Resistive Switches for Hybrid CMOS/ Nanoelectronic Logic and Memory Architectures. Sci. Rep. 2013, 3, 2856. (14) van den Hurk, J.; Linn, E.; Zhang, H.; Waser, R.; Valov, I. Volatile Resistance States in Electrochemical Metallization Cells Enabling Non-Destructive Readout of Complementary Resistive Switches. Nanotechnology 2014, 25, 425202. (15) Balakrishnan, M.; Kozicki, M. N.; Gopalan, C.; Mitkova, M. Germanium Sulfide-based Solid Electrolytes for Non-volatile Memory. In Device Research Conference, Santa Barbara, CA, June 20−22, 2005; IEEE: Piscataway, NJ, 2005; pp 1−2. (16) Tsuruoka, T.; Hasegawa, T.; Valov, I.; Waser, R.; Aono, M. Rate-limiting Processes in the Fast SET Operation of a Gapless-type Cu-Ta2O5 Atomic Switch. AIP Adv. 2013, 3, 032114. (17) Menzel, S.; Tappertzhofen, S.; Waser, R.; Valov, I. Switching Kinetics of Electrochemical Metallization Memory Cells. Phys. Chem. Chem. Phys. 2013, 15, 6945−6952. (18) van den Hurk, J.; Valov, I.; Waser, R. Preparation and Characterization of GeSx Thin-films for Resistive Switching Memories. Thin Solid Films 2013, 527, 299−302. (19) Menzel, S.; Waser, R. Analytical Analysis of the Generic SET and RESET Characterisitics of Electrochemical Metallization Memory Cells. Nanoscale 2013, 5, 11003−11010. (20) Menzel, S.; Böttger, U.; Waser, R. Simulation of Multilevel Switching in Electrochemical Metallization Memory Cells. J. Appl. Phys. 2012, 111, 014501. (21) Menzel, S.; Waser, R. On the SET/RESET Current Asymmetry in Electrochemical Metallization Memory Cells. Phys. Status Solidi RRL 2014, 8, 540−544. (22) Valov, I.; Staikov, G. Nucleation and Growth Phenomena in Nanosized Electrochemical Systems for Resistive Switching Memories. J. Solid State Electrochem. 2013, 17, 365−371. (23) Tappertzhofen, S.; Mündelein, H.; Valov, I.; Waser, R. Nanoionic Transport and Electrochemical Reactions in Resistively Switching Silicon Dioxide. Nanoscale 2012, 4, 3040−3043. (24) Tappertzhofen, S.; Linn, E.; Böttger, U.; Waser, R.; Valov, I. Nanobattery Effect in RRAMs - Implications on Device Stability and Endurance. IEEE Electron Device Lett. 2014, 35, 208−210. (25) Palma, G.; Vianello, E.; Molas, G.; Cagli, C.; Longnos, F.; Guy, J.; Reyboz, M.; Carabasse, C.; Bernard, M.; Dahmani, F. Effect of the Active Layer Thickness and Temperature on the Switching Kinetics of GeS2-Based Conductive Bridge Memories. Jpn. J. Appl. Phys. 2013, 52, 04CD02. (26) Russo, U.; Kamalanathan, D.; Ielmini, D.; Lacaita, A. L.; Kozicki, M. N. Study of Multilevel Programming in Programmable

potential multilevel operation of this type of memory cells. Furthermore, we observed a distinct nonlinear dependence of the SET time for small SET voltages that dates from a nucleation-limited process. From the evaluation of the thickness dependence of SET time and SET voltage, we concluded in comparison with our simulation results that both parameters strongly depend on the Ag-ion normalized concentration in the electrolyte, which is a function of the electrolyte thickness. We report a detailed study on the RESET behavior and we found no or just a weak dependence of the RESET voltage on the current compliance and/or the ON resistance, respectively. Higher RESET currents are mandatory to switch ECM cells at lower ON resistances. At the same time, the RESET time was independent of the ON resistance for nearly 2 orders of magnitude. No temperature effect for the dissolution of the filament can be derived from the experimental data. By pulsed measurements of the RESET kinetics, we were able to identify for the first time two voltage ranges in the RESET time versus RESET voltage behavior. Limiting factors in these two ranges were proposed to be the electron transfer and ion migration for low and high voltages, respectively.

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AUTHOR INFORMATION

Corresponding Author

*E-mail: [email protected]. Phone: +49 2461 61-2994. Present Address

(J.v.d.H.) AIXTRON SE, Dornkaulstr. 2, 52134 Herzogenrath, Germany. Notes

The authors declare no competing financial interest.

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ACKNOWLEDGMENTS The authors would like to express their gratitude to Christoph Engelen, Robin Reckmann, and Anna-Isabel Ramones for sample preparation and electrical measurements as well as to Sebastian Ferch for numerical simulations and data fitting. The work was financially supported in parts by DFG special priority SFB 917 and by BMBF project no. 03X0140.

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REFERENCES

(1) Moore, G. E. Cramming More Components onto Integrated Circuits. Electronics 1965, 38, 114−117. (2) ITRS-The International Technology Roadmap for Semiconductors, 2012 ed.; http://www.itrs.net/ 2012. (3) Valov, I. Redox-Based Resistive Switching Memories (ReRAMs): Electrochemical Systems at the Atomic Scale. ChemElectroChem 2014, 1, 26−36. (4) Yang, J. J.; Strukov, D. B.; Stewart, D. R. Memristive Devices for Computing. Nat. Nanotechnol. 2013, 8, 13−24. (5) Kozicki, M. N.; Balakrishnan, M.; Gopalan, C.; Ratnakumar, C.; Mitkova, M. Programmable Metallization Cell Memory Based on AgGe-S and Cu-Ge-S Solid Electrolytes. Proc. NVMTS 2005, 83−89. (6) Jameson, J. R.; Gilbert, N.; Koushan, F.; Saenz, J.; Wang, J.; Hollmer, S.; Kozicki, M. N. One-dimensional Model of the Programming Kinetics of Conductive-bridge Memory Cells. Appl. Phys. Lett. 2011, 99, 063506. (7) Jameson, J. R.; Gilbert, N.; Koushan, F.; Saenz, J.; Wang, J.; Hollmer, S.; Kozicki, M. Effects of Cooperative Ionic Motion on Programming Kinetics of Conductive-bridge Memory Cells. Appl. Phys. Lett. 2012, 100, 23505. (8) Jameson, J. R.; Gilbert, N.; Koushan, F.; Saenz, J.; Wang, J.; Hollmer, S.; Kozicki, M.; Derhacobian, N. Quantized Conductance in 18684

DOI: 10.1021/acs.jpcc.5b03622 J. Phys. Chem. C 2015, 119, 18678−18685

Article

The Journal of Physical Chemistry C Metallization Cell (PMC) Memory. IEEE Trans. Electron Devices 2009, 56, 1040−1047. (27) Menzel, S.; Salinga, M.; Böttger, U.; Wimmer, M. Physics of the Switching Kinetics in Resistive Memories. Adv. Funct. Mater. 2015, DOI: 10.1002/adfm.201500825. (28) van den Hurk, J.; Dippel, A.; Cho, D.; Straquadine, J.; Breuer, U.; Walter, P.; Waser, R.; Valov, I. Physical Origins and Suppression of Ag Dissolution in GeSx-based ECM Cells. Phys. Chem. Chem. Phys. 2014, 16, 18217−18225. (29) Menzel, S.; Adler, N.; van den Hurk, J.; Tappertzhofen, S.; Valov, I.; Waser, R. Simulation of Polarity Independent RESET in Electrochemical Metallization Memory Cells. 2013 5th IEEE International Memory Workshop (IMW) 2013, 92−95. (30) Ielmini, D.; Nardi, F.; Balatti, S. Evidence for Voltage-Driven Set/Reset Processes. IEEE Trans. Electron Devices 2012, 59, 2049− 2056. (31) Valov, I.; Linn, E.; Tappertzhofen, S.; Schmelzer, S.; van den Hurk, J.; Lentz, F.; Waser, R. Nanobatteries in Redox-based Resistive Switches Require Extension of Memristor heory. Nat. Commun. 2013, 4, 1771.

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DOI: 10.1021/acs.jpcc.5b03622 J. Phys. Chem. C 2015, 119, 18678−18685