We then developed the PVA based transient memristor with a vertical structure, as shown in Figure 2a. The PVA medium with the Mw of 10000 gmol-1 was used, and indium tin oxide and silver were utilized as the inert and active electrodes, respectively. The thickness of the polymer medium (PVA) was about 300 nm. Figure 2b exhibits the I–V properties of the device. The measurement was performed at a CC of 3×10−5 A to obtain the nonvolatile memory characteristics, and the electroforming process was conducted to trigger the CF formation (see Figure S7) \cite{Park_2020b,Park_2021a}. The device showed the stable nonvolatile memory performances in the bipolar mode, in accordance with the results in Figure S3. The writing and erasing voltages for the device were about 1.4 and −1.0 V, respectively, and the current ratio between the HRS and the LRS was about 103. These operating performances are comparable with those of ECM memristors with inorganic materials \cite{Lee_2020a,Wang_2021}. In the previous studies, the hydroxyl groups in the thin films (about 40 nm) of PVA were aligned by an electric field, which led to the memory effect \cite{Lei_2014,Tsai_2013}. However, in the cases where the PVA film was relatively thick (about 300 nm), such memory effect was not observed (see Figure S8). This means that the resistive switching in the device is attributed to only the metallic CF growth.
For achieving practical hardware based neural networks, the artificial synapses of the systems should possess the stable nonvolatile and reversible memory characteristics \cite{van_de_Burgt_2018,Kim_2021}. We performed a retention test for evaluating the memory stability of the developed organic memristor, as shown in Figure 2c. Each resistance state (HRS and LRS) of the device was sustained stably for 104 s, at a reading voltage of 0.2 V. Additionally, cycle tests for the device were performed using the repeated voltage sweeps consisting of the writing and erasing processes (see Figures 2d and 2e) to estimate the reproducibility of the operating voltages and the reversibility of the resistive switching. During the 50 cycles, we measured the fluctuations of the writing and erasing voltages, as shown in Figure 2d. The ratio values of the standard deviation to the average for estimating the temporal changes of the writing and erasing voltages were approximately 0.18 and 0.24, respectively. These are comparable with those of the ECM memristors with the conventional structure \cite{Park_2020,Ding_2018,Chandane_2019}. Note that, in the typical ECM memristors, the CF is formed in a random fashion, and it can deteriorate the reproducibility of the switching voltages \cite{Choi_2018}. Figure 2e shows the reversibility of the resistive switching in the device. The resistance of the device was stably changed by the switching processes for writing and erasing. From these stable and reversible memory performances, it can be considered that the developed organic memristor is applicable for practical neuromorphic electronics. Figure S9 presents the dispersions of the writing and erasing voltages for ten different cells on a single substrate. Only the small changes were observed in the switching voltages between the cells. Although the device showed the slight fluctuations at the cycle and cell-to-cell uniformity tests, the reproducibility of the switching voltages and the cell uniformity can be facilely enhanced by confining the interfacial ion injection \cite{Liu_2010,Lee_2019a}.
Another essential feature of memristors for artificial synapses is the multilevel state of the conductance \cite{van_de_Burgt_2018,Kim_2021}. We controlled the CF thickness by adjusting the CC values at the writing process, as shown in Figure 2f. The multilevel conductance was effectively demonstrated in the device (see Figure 2g), and each conductance state was maintained steadily (see Figure S10). This implies that the developed device can be used for high-density storage systems and complex artificial neural networks. Figure S11 shows the effect of temperature on the conductance of the device at the LRS. The postive resistivity coefficient of the device was estimated to be about 0.0037 K-1, similar to that of silver (about 0.0038 K-1). This implies that the resistive switching of the vertical-type device was governed by the ECM phenomenon for the CF growth \cite{Jang_2016}. Note that the ECM memristor is a promising candidate as the highly scalable artificial synapse, because its operation is mainly governed by the localized nanoscale CF \cite{Park_2020b,Choi_2018}. As shown in Figure S12, our PVA based memristor showed the stable resistive switching characteristics, irrespective of the cell area.
For the practical applications of neuromorphic systems, the synaptic device should be operated under the pulse condition \cite{Park_2020b,Park_2021a}. We additionally investigated the resistive switching of the device in the pulse modes (see Figure S13). The resistance state of the device was effectively controlled by the voltage pulses, and the writing and erasing times were about 5.3 and 5.0 μs, respectively. Typically, in the ECM memristors, the CF growth and the resultant resistive switching are governed by the voltage conditions \cite{Waser_2009,Valov_2011}. The switching times of the device can be simply reduced by tuning the voltage amplitude.