Synaptic learning behaviors achieved by metal ion migration in a Cu/PEDOT:PSS/Ta memristor

Abstract

In this paper, a memristor with structure of Cu/ PEDOT:PSS/ Ta was fabricated at room temperature. The conductance could be modulated incrementally by pulse sequences. The amplitude, width, frequency and quantity of the pulse sequence play important roles in conductance variation, which is similar to the weight of synapses. Several important synaptic learning behaviors such as short-term potentiation (STP), long-term potentiation (LTP) and spike-timing dependent plasticity (STDP) were emulated by this memristor, respectively. It is found that the movement of Cu ions is critical for this device.

Neuromorphic Computing between Reality and Future Needs

“…One of the justifications provided for doing so is the chalcogenide-based memristor's ultra-fast switching speeds, which allow for processes like STDP to take place at nanosecond scale [97]. Polymer-based memristors have been used because of their inexpensive cost and adjustable performance [68,[103][104][105][106][107][108][109][110][111]. There have also been suggestions for organic memristors, which include organic polymers [69, [112-123].…”

A phenomenological memristor model for synaptic memory and learning behaviors

“…The memristor has been treated as a promising candidate for building bio-inspired neuromorphic systems since its properties are similar to the memory and learning functions in biological systems which have been observed and reported in the experimental studies of memristors fabricated by different materials. [1][2][3][4][5][6][7][8][9][10][11][12][13] Table 1 gives some commonly reported properties with their experimental details in those experimental studies. The forgetting behavior and the transition from short-term memory (STM) to long-term memory (LTM) are two typical properties of this kind of memristor.…”

“…[6] I = bt −m ∼ 13 mV Yes (II) 0.5 s/80 mV 12 4 s Yes No -No -Ag/PEDOT:PSS/Ta [7] EF 1.2 V Yes (I) -5-50 60 s No Yes 50/6 Yes Yes PVA [8] EF -Yes (I) 0.3 s/0.5 V 50-300 60 s -No -Yes No OTP [9] b) EF -0.75 V Yes (I) 0.2 s/−2 V 5-30 30 s No Yes c) -No -Ta/EV(ClO 4 ) 2 /BTP-F/Pt [10] EF 0.2 V Yes (I) 10 ms/1 V 10-60 60 s No Yes 40/9 Yes No Ta/EV(ClO 4 ) 2 /TPA-PI/Pt [11] -0.2 V Yes (II) 10 ms/0.5 V 6 800 ms -Yes 80/11 Yes No Cu/Cu 2 S/Pt [12] EF ∼ 10 mV Yes (II) 0. 5 s/0.1 V 4 10 s No No -No -Cu/PEDOT:PSS/Ta [13] EF -Yes (I) -10-70 60 s No No -Yes Yes…”

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

“…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).…”

“…Some of the issues with previous experimental implementations of memristors in the synaptic role in the STDP application (Chang et al, 2011; Rose et al, 2011a,b; Li et al, 2013a; Subramaniam et al, 2013; Luo et al, 2015; Mahalanabis et al, 2016) include the lack of analog programmability of the memristor, high power requirements, and requirement of very specific programing spike shapes in order to effectively program the synaptic weights. Recent work, using a TaO x memristor as a synapse has demonstrated incremental switching in memristors, through the use of repetitive pulses and a pulse train with increasingly higher amplitudes.…”