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# An Electrochemical-Electret Coupled Organic Synapse with Single-Polarity Driven Reversible Facilitation-to-Depression Switching

Hanlin Wang, Yusheng Chen, Zhenjie Ni, Paolo Samorì

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Hanlin Wang, Yusheng Chen, Zhenjie Ni, Paolo Samorì. An Electrochemical-Electret Coupled Organic Synapse with Single-Polarity Driven Reversible Facilitation-to-Depression Switching. Advanced Materials, 2022, 34 (50), pp.2205945. 10.1002/adma.202205945. hal-03918033

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# An Electrochemical-Electret Coupled Organic Synapse with Single-Polarity Driven Reversible Facilitation-to-Depression Switching

Hanlin Wang, Yusheng Chen, Zhenjie Ni, and Paolo Samori*

Neuromorphic engineering and artificial intelligence demands hardware elements that emulates synapse algorithms. During the last decade electrolyte-gated organic conjugated materials have been explored as a platform for artificial synapses for neuromorphic computing. Unlike biological synapses, in current devices the synaptic facilitation and depression are triggered by voltages with opposite polarity. To enhance the reliability and simplify the operation of the synapse without lowering its sophisticated functionality, here, an electrochemical-electret coupled organic synapse (EECS) sessing a reversible facilitation-to-depression switch, is devised. Electret charging counterbalances channel conductance changes due to electro-chemical doping, inducing depression without inverting the gate polarity. Overall, EECS functions as a threshold-controlled synaptic switch ruled by its amplitude-dependent, dual-modal operation, which can well emulate information storage and erase as in real synapses. By varying the energy level offset between the channel material and the electret, the EECS's transition threshold can be adjusted for specific applications, e.g., imparting additional light responsiveness to the device operation. The novel device architecture represents a major step forward in the development of artificial organic synapses with increased functional complexity and it opens new perspectives toward the fabrication of abiotic neural networks with higher reliability, efficiency, and endurance.

H. Wang, Y. Chen, P. Samori

Université de Strasbourg

CNRS

ISIS

8 allée Gaspard Monge, Strasbourg 67000, France

E-mail: samori@unistra.fr

Z. Ni

School of Chemical Sciences

University of Chinese Academy of Sciences

Beijing 101408, P. R. China

The ORCID identification number(s) for the author(s) of this article can be found under https://doi.org/10.1002/adma.202205945.

© 2022 The Authors. Advanced Materials published by Wiley-VCH GmbH. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and re-production in any medium, provided the original work is properly cited.

DOI: 10.1002/adma.202205945

## 1. Introduction

Synaptic plasticity is of elemental significance for mimicking sensory perception, learning, remembering, and forgetting.[1–3] It operates by strengthening or weakening the inter-neuron connectivity via the controlled occurrence of presynaptic events, with postsynaptic currents (PSCs) being the output enabling quantitative monitoring of the process.[4,5] For example, facilitation can be achieved by repetitive presynaptic stimuli which allow to enhance ultrafast synaptic transmission and memory consolidation.[6] Conversely, the opposite process is depression, which represents an inhibitory operation, avoiding overexcitation and maintaining the stability of neural networks.[7] Due to the critical role played by synaptic plasticity in artificial intelligence to promote interaction between humans and machines, much endeavor has been devoted to mimic biological synapses using organic conjugated materials, aimed at encoding and amplifying information.[8–16] In particular, electrolyte-gated organic materials combine charge transport and electrochemical doping in the channel,[17–19] hence they represent versatile platforms to impart unique electrical properties to synaptic devices.[20–23] Efforts toward their integration in optoelectronic devices led to the development of organic electrochemical transistors (OECTs).[19] As an electronic synapse, the kinetics of ion-doping and de-doping in OECTs have been developed to emulate the facilitation and depression behavior.[10,20] As a model system, electrolyte-gated PEDOT:PSS has been studied due to the reversible electrochemical interaction between mobile ions and polymer backbone.[9,11] Under electrostatic gating, mobile anions are driven to dope the channel, increasing the channel conductivity thereby yielding facilitation. By reversing the polarity of electrostatic gating, anions percolated in the channel are extracted, making it possible to recover the original state in compliance with a depression process. By mastering such polarity-induced switch a variety of organic synapses displaying sophisticated functions have been realized.[15] Upon using aqueous electrolyte,[9,10,16] ion-gel[14,17,23] and polyelectrolyte gating,[12] they simultaneously featured the formation of electron-double-layer (EDL)
and electrochemical doping. As a result, organic synapses with remarkable device performances have been fabricated which exhibited novel functions including non-volatile signal retention,[11] ultralow power consumption[24,25] integrated in a nanoscale device footprint.[26]

While short-term facilitation has been the subject of much research effort, depression received less attention in organic synapses.[9,27] Nonetheless, in view of its complementarity to facilitation, it is key to maintain the balance between excitation and inhibition in neural networks.[7] Moreover, depression reduces synaptic transmission, releasing storage space for new events or memory refreshing, ultimately lowering energy consumption. Depression and facilitation are typically achieved upon using presynaptic gating with opposite polarity. However, such remote control is not applied in biological synapses. In the latter, depression can spontaneously be triggered under prolonged presynaptic stimuli with increased frequency or amplitude, thereby avoiding inversion of the gate polarity. Significantly, from the perspective of neuromorphic computing, this “incomplete” synaptic plasticity hinders the development of the artificial neural network. Moreover, biomimetic electronics require organic synapses capable of readily switching between facilitation and depression to construct highly efficient synaptic readout circuits. Noteworthy, there is growing interest in integrating sensory elements with synaptic readout into biomimetic eyes[12] and artificial afferent nerves.[28,29] Physical stimuli are usually transformed into “single polar” analog signals as presynaptic inputs. In this context, it is imperative to develop organic synapses enabling “single-polarity”, amplitude-dependent facilitation, and depression response, as a key step toward advanced artificial sensory-perception systems.

Here, we demonstrate an electrochemical-electret coupled organic synapse (EECS) displaying reversible gate-amplitude-dependent facilitation-to-depression transition, without the need of switching the polarity of presynaptic gating. The increase and decrease of the synaptic strength are remote controlled by the transition voltage for plasticity transition ($V_{PT}$), which we demonstrate to be tunable by varying the highest occupied molecular orbitals offset ($\Delta$HOMO) between the channel materials and electrets. In this manner, both excitatory and inhibitory type synapses are achieved. Polymer electrets are dielectrics that exhibit electric-field-induced charge trapping and this property has been employed to establish organic flash memory and synapses.[30,31] EECS integrates the functions of electrolyte-gated transistors and electret memory, as demonstrated by realizing a polymer channel gated simultaneously by polyelectrolyte and electret. These two dielectrics are capable to modulate the channel conductance via amplitude-dependent yet opposite, i.e., competitive, synaptic plasticity. Below the transition threshold, short-term facilitation is achieved by electrochemical doping. When the presynaptic gating exceeds the threshold, electret charging, as well as electrochemical doping, are triggered. Short-term depression is activated since depletion of hole density in the channel due to electret charging cannot be fully compensated by the increase in channel conductance from electrochemical doping. In this manner, depression is induced in excitatory organic synapses. Furthermore, we optimize the energy level offset in channel polymers/electrets and endow EECS with desired neuromorphic characteristics.

Polyelectrolyte-gated organic synapses provide opportunities for next-generation neuromorphic devices since they can display synaptic facilitation triggered by electrochemical doping. Moreover, when a semiconductor is interfaced with a polyelectrolyte, the formation of high capacitance EDL determines a negligible potential drop across the bulk polyelectrolyte and a high surface charge density in the semiconductor.[32,33] These characteristics are advantageous for low-voltage operations. The assembly of another dielectric layer on the top of the polyelectrolyte/semiconductor stack allows an increase in the complexity of the device functionality.[34] By EDL-aided capacitive coupling, surface charge density in the dielectric is expected to permeate the polyelectrolyte thereby affecting the charge accumulation in the semiconductor. This feature enables functional dielectric/polyelectrolyte gated synapses with further synaptic functionality in addition to short-term facilitation. For example, ferroelectricity in P(VDF-TrFE) can penetrate the polyelectrolyte to impart “contactless” switching of the non-volatile conductance in the channel.[12] Such advantage bears potential for multi-mechanism-incorporated neuromorphic devices. A critical property in charge-trapping-based transistors is represented by its fatigue which is observed as a gradual decrease in the channel conductance each time they are switched on, in analogy to synaptic depression.[35]

## 2. Results and Discussion

### 2.1. Working Principles and Electrical Characterization of Dual-mode EECS

The unprecedented coupling strategy is demonstrated through the realization of a stacked organic synapse (Figure 1a) based on a trilayer dielectric assembly comprising poly(vinylidene fluoride-trifluoroethylene-chlorofluoroethylene) terpolymer [P(VDF-TrFE-CFE)], poly(2-vinylnaphthalene) (PVN) and poly[(1-vinylpyrrolidone)-co-(2-ethyldimethylammonioethyl methacrylate ethyl sulfate)] [P(VP-EDMAEMAES)]. High-$\kappa$ (40-60) P(VDF-TrFE-CFE) served as a key dielectric component to reduce operation voltages whereas poly(isoindigo-co-bithiophene) (PIID-BT)[36] was used as channel material. The chemical structures of the employed polymers in this standard device are displayed in Figure 1b, while conjugated materials to construct EECS derivatives are shown in Figure S1, Supporting Information. The precise multilayer architecture was obtained by polymer processing with orthogonal solvents (see details in the Materials section, Supporting Information). The morphology of each functional layer was mapped by atomic force microscopy (AFM) (Figure S2, Supporting Information). The crystalline nature of PIID-BT and P(VP-EDMAEMAES) determined a root-mean-square roughness ($R_{RMS}$) of 3.14 nm and 4.14 nm as estimated over areas of $5 \times 5$ um$^2$, respectively. Fortunately, the overlying amorphous PVN and P(VDF-TrFE-CFE) layers have smoothened the film leading to a final $R_{RMS}$ of 2.38 nm, which is suitable for device fabrication.

Under presynaptic potential ($V_{pre}$) with low magnitude, for $V_{pre} < V_{PT}$, electrochemical doping dominated the channel conductance modulation (Figure 2a). The permeation of mobile ions (ethyl sulfate) into the PIID-BT matrix determined its
<figure><img src="image_4.png" /><figcaption>**Figure 1.** Device structure of EECS and functional polymers in its active layers. a) EECS comprises four stacked polymer layers functioning as a neuromorphic device. The topmost P(VDF-TrFE-CFE) serves as a high-κ major dielectric. PVN acts as an electret to trap the holes transited from the semiconductor channel. P(VP-EDMAEMAES) is a polyelectrolyte interlayer, promoting hole transfer from channel to electret due to the formation of an electron double layer (EDL). The bottom layer is the semiconducting p-type PIID-BT. b) Molecular structures of the employed functional polymers.</figcaption></figure>

oxidation which was compensated by ionic charges. This step induced synaptic facilitation, which took place via channel conductance amplification. Yet, when $V_{pre} \ge V_{PT}$, two opposite synaptic operations occurred simultaneously (Figure 2b): i) Increased hole density in the channel due to strengthened electrochemical doping; ii) Depletion of holes in the channel resulting from hole injection from the channel to the electret layer. The upward shift of the electret's HOMO, together with interfacial ionic coupling in the polyelectrolyte, allowed hole injection from the channel to PVN. We postulate that with high $V_{pre}$ and deep-HOMO channel polymers, electret charging (step ii) could offset electrochemical doping (step i), resulting in the EECS switching from facilitation to depression mode. Hence by mastering this principle, transitions from facilitation and depression modes could readily be driven by one polarity just by adjusting the amplitude gating. The functional essence of this architecture lies in the interfacing of PVN and P(VP-EDMAEMAES), supplementing electrolyte-gated excitatory synapses with inhibition capability. This strategy enabled a reversible, dynamic modulation of postsynaptic strength in organic neuromorphic devices. Finally, owing to a high capacitance of EDL, polyelectrolyte interlayer consumes negligible voltage during operation, thereby endowing low energy dissipation characteristics to multilayered organic synapses.

To verify the postsynaptic response in an EECS, a series of $V_{pre}$ at variable amplitude were applied (Figure 2c,d). The following measurement parameters were employed: 700 points were sampled for each individual curve. Each set of excitatory or inhibitory $V_{pre}$ pulses contained 50 pulses. Pulse width and interval of $V_{pre}$ spikes were 15 and 25 ms, respectively. This corresponded to a $V_{pre}$ frequency amounting to 40 Hz. Short-term facilitation was achieved when repeating $V_{pre}$ pulses of -6 V. Subsequently, negative feedback, i.e., depression, was induced upon applying a higher $V_{pre}$ of -12 V. After a 5 s resting time, facilitation was successfully reproduced by applying $V_{pre}$ pulses of -6 V, although its maximum excitatory postsynaptic current (EPSC) decayed to 56.6% compared to the previous facilitation event (351 versus 620 nA). This phenomenon represents an

attenuated synaptic transmission occurring after having completed the depression process, confirming EECS as a highly emulating and self-regulating synapse. Interestingly, EECS is reconfigurable, like its electret memory analog. Reset of the attenuated device was attained under positive gate pulses to discharge the holes stored in PVN back into the channel. In Figure 2d, EECS could hardly produce synaptic signals with $V_{pre}$ pulses of 12 V, accompanied by the full recovery of its excitation efficiency compared to its initial state. These bidirectional tunable postsynaptic responses validate the design and working principle of our neuromorphic device.

## 2.2. Mimicking Facilitation and Depression in an EECS

To distinguish the operation regions between facilitation and depression in EECS, its transfer characteristics were reversibly measured within variable $V_G$ regimes (Figure 3a). Upon applying $V_G$ of ±6 V, being an established regime for facilitation, EECS displayed a clockwise hysteresis loop. $I_{DS, VG=0}$ V in backward sweeping could reach 8.57 nA, thereby exceeding the 3.06 nA detected in the forward direction (Figure S3, Supporting Information). This difference is due to the remnant electrochemical doping, being a common characteristic in electrolyte-gated organic transistors.[37] This finding is in accordance with the increased synaptic strength under $V_{pre}$ of -6 V observed in Figure 2c, indicating electrochemical dynamics as the governing mechanism in a low $V_G$ regime. Upon increasing $V_G$ up to ±12 V, the anti-clockwise loop was obtained in transfer curves, being identical to a p-type organic electret memory. In this scenario, the remnant electrochemical doping cannot compensate for the reduced hole concentration in the channel due to electret charging, thus leading to a microampere to nanoampere attenuation in $I_{DS,VG=0}$ V. As revealed in Figure 3b, the memory window, defined by the shift of $V_{Onset}$ measured in hysteresis loops, almost scaled linearly with $V_G$, reaching its maximum of 12.5 V at $V_G$ of ±25 V. Subsequently, memory window as a function of scan rate was studied (all bidirectional
<figure><img src="image_5.png" /><figcaption>**Figure 2.** Working principle of EECS and its electrical characteristics of switchable synaptic plasticity. a) Step i. Synaptic facilitation in EECS is obtained via electrochemical doping. Under low-amplitude $V_{pre}$, mobile anions, i.e., ethyl sulfate, in P(VP-EDMAEMAES) are repulsed by negative $V_{pre}$ facilitating their permeation into PIID-BT. During intervals of $V_{pre}$ pulses, ethyl sulfate can be extracted from the channel by de-doping dynamics. These processes yield facilitated channel conductance. b) Step ii. Under high-amplitude $V_{pre}$, excess holes electrostatically induced in PIID-BT are injected into PVN, leading to reduced hole concentration. When such a decrease in channel conductance is not fully compensated by facilitated channel conductance from electrochemical doping, synaptic depression is obtained. Therefore, EECS presents an amplitude-dependent dual-mode of synaptic plasticity. c) Postsynaptic currents (PSCs) in EECS under a series of presynaptic stimuli, demonstrating a transition between facilitation and depression. Note that the magnitude of PSC under the 2nd set of facilitating pulses is lower than the previous one. d) Due to the use of positive resetting voltages, the magnitude of PSC under the 2nd set of facilitating pulses can be fully recovered to the scale in the previous one. 700 points sampled with a $V_{pre}$ frequency of 40 Hz. Each train of $V_{pre}$ series (with the same $V_{pre}$ magnitude) contains 50 pulses.</figcaption></figure>

transfer curves in the manuscript were scanned at a rate of 19.77 V s⁻¹). We observed that at 24.28, 19.77, and 16.50 V s⁻¹, the obtained memory window ranges from 8.5 to 9.5 V. In contrast, the memory window was enlarged to 10.7 V at 12.49 V s⁻¹ (Figure S4, Supporting Information). Hence, a wider memory window can be obtained by operating at slower scanning rates.

The modulation of the synaptic transmission in EECS was tested by applying 50 Hz $V_{pre}$ pulses with –6 V for facilitation and –25 V for depression (Figure 3c). Synaptic gain is defined by the change in synaptic weight and it is quantified by the ratio of postsynaptic current amplitude between $A_n$ and $A_1$, where n stands for spike number and $A_1$ is the PSC of the 1st spike. The value of the synaptic weight doubled in the initial 10 spikes. Upon repeating the $V_{pre}$ pulses 100 times, we observed saturation of the synaptic weight reaching an $A_{100}/A_1$ ratio of 604% with respect to the 1st spike. In another case, 100 $V_{pre}$ pulses of –25 V yielded an inhibitory postsynaptic current (IPSC) 50.7% of its initial value. Alongside the effect determined by the number of repeated $V_{pre}$ stimuli which are applied, we found that more significant changes in synaptic gains can be

obtained upon applying $V_{pre}$ with higher frequency (Figure S5, Supporting Information). Paired-pulse facilitation (PPF) and depression (PPD) were quantitatively assessed by measuring the weight change in two successively induced postsynaptic signals. In Figure 3d, under a spike interval of 30 ms, PPF and PPD indices reached 176.9% and 92.5%, respectively. Decay curves were fitted by a biexponential function, resulting in $\tau_1 = 5.47 \times 10^{-4}$ s and $\tau_2 = 0.011$ s for PPF, and $\tau_1 = 3.13 \times 10^{-4}$ s and $\tau_2 = 0.0053$ s for PPD. Power consumption was calculated as $W = I_{postsynaptic} \times V_D \times t$, which is the product of postsynaptic current, drain voltage, and pulse width. For the simplicity of calculation, peak postsynaptic current was used as $I_{postsynaptic}$. For example, the energy consumption of the first spike from the upper panel of Figure 3d was calculated to be 13.1 nJ. Further reduction of power consumption can be expected by using channel materials with higher conductivity such as PEDOT:PSS,[11] hence lower $V_D$ and shorter pulses shall be demonstrated in subsequent works. Lowered PPF index was produced with prolonged spike intervals, implying decreased efficiency for synaptic transmission. As the interval was extended
<figure><img src="image_6.png" /><figcaption>b</figcaption></figure>

<figure><img src="image_7.png" /><figcaption>c</figcaption></figure>

<figure><img src="image_8.png" /><figcaption>d</figcaption></figure>

<figure><img src="image_9.png" /><figcaption>e</figcaption></figure>

<figure><img src="image_10.png" /><figcaption>f</figcaption></figure>

<figure><img src="image_11.png" /><figcaption>**Figure 3.** Electrical characterization of EECS as synapse. a) Hysteresis was observed upon transfer curves sweeping. Clockwise loop in transfer curves was obtained within $V_G$ of ± 6 V, due to remnant electrochemical doping. Under $V_G$ of ±12, ±20, and ±25 V, an-clockwise loops were monitored in analogy to organic electret-based memory. b) Memory window in EECS as a function of $V_G$ range. Averaged values and standard deviation (s.d.) are calculated from at least 5 devices for each entry. c) Synaptic gain as a function of spike number. For facilitation, 50 Hz $V_{pre}$ pulses of –6 V. Pulse width = 5 ms. For depression, 50 Hz $V_{pre}$ pulses of –25 V. Pulse width = 5 ms. Number of pulses = 100. d) Pulse-pair facilitation (PPF) and depression (PPD) recorded with a pulse width of 15 ms and a pulse interval of 30 ms. $V_{pre}$ –6 V for PPF and $V_{pre}$ –25 V for PPD, respectively. Decay curves were fitted by a biexponential function, resulting in $τ₁ = 5.47 × 10⁻⁴$ s and $τ₂ = 0.011$ s for PPF, and $τ₁ = 3.13 × 10⁻⁴$ s and $τ₂ = 0.0053$ s for PPD. e) PPF and f) PPD index measured as a function of presynaptic pulse interval. Shorter intervals lead to more efficient modulation of synaptic transmission.</figcaption></figure>

to 1500 ms, facilitation disappeared with the index approaching 100% (Figure 3e). PPD index reached 90.2% at an interval of 20 ms ($V_{pre}$ = –25 V) and 97.1% at 1500 ms (Figure 3f). This observation indicates faster “forgetting” rate can be attained by applying more frequent inputs.

Operational stability of EECS was assessed by real-time postsynaptic response under repetitive 500 $V_{pre}$ pulses (10 sets × 50 pulses per set, Figure S6, Supporting Information). Driven by $V_{pre}$ = –6 V, monotonously enhanced PSC was reproducibly obtained with a high gain ($A_{500}/A₁$) of 8.371. Upon applying $V_{pre}$ = –12 V, the EECS shifted into depression mode with its channel current being switched-on to its full capacity in the µA regime, then followed by a decreasing trend of PSC. In such a case, a gain of 0.733 was obtained. Importantly, the device could be reset by applying a positive gate input (with the same absolute value in amplitude), prior to a new set of measurement. Upon increasing the amplitude of $V_{pre}$, the synaptic transmission was gradually inhibited with remarkably lower gains, amounting to 0.379 at –18 V and 0.262 at –25 V. For comparison, a control EECS without PVN layer was fabricated. When applying $V_{pre}$ = –12 V, it operated as an excitatory device. Driven by higher voltages, saturation in synaptic weights was obtained rather than inhibition, which ambiguously demonstrated the emergence of depression behavior resulting from the PVN layer (Figure S7, Supporting Information).

## 2.3. Tuning the Plasticity Transition Voltage in an EECS

Controlled switching in synaptic plasticity is key to developing sophisticated algorithms for advanced computing functions in machine learning and pattern recognition. Therefore, we extended our study by investigating the factors that quantitatively determine $V_{PT}$ in EECS. Significantly, in a gated PIID-BT/P(VP-EDMAEMAES)/PVN stack, two EDLs can be induced with one lying in PIID-BT/polyelectrolyte interface and the other in PVN/polyelectrolyte interface. Such a coupling enables negligible potential distributed across P(VP-EDMAEMAES) and it allows reversible charge injection between PIID-BT and PVN, which is facilitated by ion displacement and differs from a tunneling process in traditional dielectrics. In principle, once HOMO levels in PIID-BT and PVN are enhanced under negative gating with sufficient amplitude, holes can be injected and stored in PVN, hence decreasing the facilitated channel conductance induced by electrochemical doping. Therefore, it is expected that ΔHOMO between channel polymer and electret governs the plasticity transition. The energy levels of conjugated polymers and electrets were obtained from literature and are listed in Table S1, Supporting Information. To verify this hypothesis, a control EECS with poly(vinyl-carbazole) as electret (PVK, LUMO, –1.9 eV and HOMO, –5.4 eV) and the other functional layers unchanged were fabricated and tested. In this device, ΔHOMO in PIID-BT/PVK is calculated as 0.21 eV,
<figure><img src="image_12.png" /></figure>

<figure><img src="image_13.png" /></figure>

<figure><img src="image_14.png" /><figcaption>**Figure 4.** Tuning the synaptic behavior of EECS with other electret and channel polymers. a) Bidirectional sweeping in transfer curves produced anti-clockwise hysteresis in a PIID-BT/P(VP-EDMAEMAES)/PVK/P(VDF-TrFE-CFE) EECS. b) Synaptic depression achieved in this device triggered by $V_{pre}$ = -8 V. c) Hysteresis produced in back and forth sweeping in standard PIID-TT EECS (standard here means a trilayer dielectric stack made of P(VP-EDMAEMAES)/PVN/P(VDF-TrFE-CFE), as displayed in Figure 1a). Clockwise loop in transfer curves was obtained within $V_G$ of ±6 V, while anti-clockwise loops were achieved under $V_G$ of ±12, ±20, and ±25 V. This result is similar to standard PIID-BT EECS (PIID-BT/P(VP-EDMAEMAES)/PVN/P(VDF-TrFE-CFE)). d) Synaptic depression in this device was induced by $V_{pre}$ = -10 V, being lower than standard PIID-BT EECS. e) Hysteresis produced in back- and-forth sweeping in standard PCDTPT EECS. Intersections were formed in its transfer curves, implying a persistent electrochemical doping in PCDTPT. f) Threshold for plasticity transition in the investigated devices is plotted against ΔHOMO between electrets and channel polymers. Averaged values and standard deviation (s. d.) are calculated from at least 5 devices for each entry.</figcaption></figure>

being notably lower than 1.16 eV in PIID-BT/PVN. **Figure 4a** plots its hysteretic transfer curves. The memory window is in positive correlation to ΔHOMO and it reached 6.7 V upon applying $V_G$ = ±25 V, being notably lower than 12.0 V in PIID-BT/PVN EECS. Determination of its plasticity transition threshold was studied by a real-time postsynaptic response by using $V_{pre}$ pulses from -6 to -25 V (Figure S8, Supporting Information). However, differently from standard EECS (PIID-BT/PVN), depression rather than facilitation was produced in PIID-BT/PVK device, even under a low $V_{pre}$ = -6 and -8 V, as shown in Figure 4b and Figure S8 (Supporting Information). Note, this transition voltage is profoundly smaller than that in standard EECS ($V_{PT}$, -12 V). This finding can be ascribed to a facile pathway for hole transport from PIID-BT to PVK. The low static ΔHOMO from PIID-BT/PVK is accounted for by this phenomenon, which does not require high gating voltages to enhance their HOMO levels for hole injection. Thus, holes in the channel can easily reach PVK under a preferably lower $V_{pre}$ in standard EECS ($V_{pre}$ = -12 V). By and large, we indifferently realized inhibitory synapses by minimizing ΔHOMO between channel polymer and electret.

Moreover, excitatory synapses in an individual set of $V_{pre}$ pulses as well as inhibitory synapses in the long run were simultaneously recorded in PIID-BT/PVK EECS (Figure S8a, Supporting

Information). We attribute such an observation to a dynamic competition between electrochemical doping and electret-charging at the low $V_{pre}$ region. In particular, a volatile electret-charging effect exists at low $V_{pre}$, while high $V_{pre}$ is characterized by non-volatile electret-charging. Therefore, at low $V_{pre}$ biasing, the depression in the whole data set results from the reduced hole concentration in the channel due to the electret-charging. However, this volatile electret-charging effect can easily be surpassed by the electrochemical doping. This leads to the co-existence of facilitation in individual steps in conjunction with depression in the whole data set. Such competition can be adjusted by slightly increasing the magnitude of $V_{pre}$, thus inducing a non-volatile electret-charging. For example, in Figure S8b (Supporting Information), driven by $V_{pre}$ of -8 V instead of -6 V, PIID-BT/PVK EECS exhibits a more "natural" depression mode.

In addition to electrets, conjugated polymers with variable HOMO were surveyed when combined with PVN to accurately tune the $V_{PT}$ in EECS. HOMO levels of poly(isoindigo-co-thienothiophene) (PIID-TT) and poly[4-(4,4-dihexadecyl-4H-cyclopenta[1,2-b:5,4-b']-dithiophen-2-yl)-alt-[1,2,5]thiadiazolo-[3,4-c]pyridine] (PCDTPT) lie at -5.28 and -4.92 eV, respectively. Combined with PIID-BT, these polymers comprise a gradient in HOMO level. Figure 4c plots the typical hysteresis transfer curves. PIID-TT presented a similar feature to PIID-BT,
with electrochemical doping-induced clockwise loops with $V_G = \pm 6$ V and electret-charging-induced anti-clockwise loops from $V_G$ of $\pm 12$ to $\pm 25$ V. The maximum memory window reached an average value of 11.87 V upon applying $V_G = \pm 25$ V (Figure S9, Supporting Information). Facilitation was induced in the PIID-TT EECS at $V_{pre} = -6$ V. However, a minimum $V_{pre} = -10$ V can trigger depression (Figure 4d), being slightly lower than standard EECS. This is due to the reduced ΔHOMO of PIID-TT/PVN when compared to PIID-BT/PVN (1.07 versus 1.16 eV). Higher $V_{pre}$ of -18 and -25 V led to suppressed gains of 0.817 and 0.460, respectively (Figure S10, Supporting Information). Previous work revealed stronger electrochemical doping available via high-lying HOMO polymers, which we believe is also a factor affecting $V_{PT}$ in EECS. For example, PCDTPT[38,39] is known as a narrow bandgap polymer (1.20 eV) with HOMO of -4.9 eV. Clockwise hysteresis loops were obtained in its bidirectional transfer curves with $V_G$ of $\pm 6$ V and $\pm 12$ V, showing strong electrochemical doping than PIID-BT and PIID-TT (Figure S11, Supporting Information). When applying a $V_G$ with a magnitude within $\pm 30$ V we found an intersection instead of anti-clockwise loops in transfer curves and higher drain current at $V_G = 0$ V in the backward direction (Figure 4e and Figure S11, Supporting Information). We ascribe this behavior to predominant electrochemical doping in PCDTPT based EECS. Furthermore, ΔHOMO in PCDTPT/PVN is as high as 1.45 eV, implying a high gating voltage necessary for electret charging. Therefore, the efficiency of electrochemical doping can be expected to surpass PVN charging in terms of conductance modulation, allowing facilitation within a wide range from $V_{pre}$ of -6 to -25 V. Only at $V_{PT}$ as high as -30 V, PCDTPT based devices shifted into depression mode (Figure S12, Supporting Information). Furthermore, due to the high-lying HOMO of PCDTPT, a persistent long-term plasticity from strong electrochemical doping is produced to give non-volatility, as displayed in Figure S12, Supporting Information.

By substituting channel materials and electrets, we have demonstrated that ΔHOMO represents a critical parameter to switch the synaptic features of EECS. Upon using channel polymers with variable HOMO, efficiency in the electrochemical doping, as well as electret charging, can be optimized. The transition point is plotted as a function of ΔHOMO in Figure 4f. With this knowledge, we can regulate the balance between the excitation and inhibition in organic dual-mode synapses.

Finally, regarding operation voltages, our devices comprise tri-layer dielectrics which render them not very competitive (e.g., $V_{pre} = V_D = -6$ V for PIID-BT/PVK EECS) in low-voltage operations when compared to other organic synapses, such as organic electrochemical transistors (OECTs).[20] Efforts should be paid to reduce operation voltages and increase channel current in this system. To achieve these goals, our future efforts will be dedicated to the development of new EECS architectures based on vertical channel geometries and on the integration of conjugated polymers with higher carrier mobilities.

## 2.4. Photomodulation of Synaptic Plasticity in BHJ-EECS

As the next step, we enhanced the functional complexity of EECS by implementing optical signals as a stimulus to mod-

ulate its synaptic behavior.[40] This function was realized by employing a photoactive bulk heterojunction (BHJ) made of PDPP-T (donor) and ITTC (acceptor) blend as channel layers for EECS. HOMO values in PDPP-T:ITTC amount to -4.99 /-5.62 eV, while the LUMO levels are -3.69 /-3.96 eV, respectively. Blends with similar materials have displayed good photovoltaics performances with high power conversion efficiency.[41] Moreover, PDPP-T is a well-established p-type material with higher FET mobility compared to ITTC. Thus, we considered holes as major carriers in the operation of BHJ-EECS. Under light irradiation, excitons were generated at the PDPP-T:ITTC interface and they dissociated into two pathways: hole transport in PDPP-T and electron transport in ITTC (Figure 5a). This process can be further enhanced by the application of negative gate voltages. As a result, photogenerated holes were accumulated at the PDPP-T/P(VP-EDMAEMAES) interface, contributing to facilitated drain current. As a matter of fact, irradiation of BHJ-EECS yielded a positive $V_{Onset}$ shift of 7 V in transfer curve, and its drain current at $V_G = 0$ V boosted from nA level to 0.58 µA (Figure 5b), indicating the successful development of photosensitive EECS. Moreover, the EECS synaptic behavior under light irradiation was investigated. It was found that the synaptic gain in the device increased from 130.3% in the dark to 162.9% under light at $V_{pre}$ of -15 V (Figure 5c), indicating enhanced synaptic transmission under optical stimuli. In Figure 5d, a clear facilitation-to-depression transition with a gain of 83.9% was recorded in the dark state. In contrast, light irradiation augmented the tendency for decreasing IPSC by an enhanced gain of 97.7%. Hence, the optical stimulus was proven to be capable of modulating the synaptic behavior in BHJ-EECS. It should also be noted that the direction of photogenerated surface potential in BHJ is the opposite to $V_G$, thereby offsetting gate-induced electret charging. All in all, we have demonstrated EECS endowed with an efficient photoactive BHJ as the channel, affording devices with modulated synaptic transmission under optical stimuli.

Furthermore, light-pulse-triggered synaptic plasticity was investigated. Green light with wavelength of 530 nm and intensity of 4.96 mW cm⁻² was used to switch the BHJ-EECS. The employed width of the light pulses was 5 s, while the interval between pulses amounted to 15 s. BHJ-EECS was biased with $V_G$ of 0, -10, and -15 V, respectively. A notable short-term plasticity was produced under light pulses at zero $V_G$ with increased synaptic strength to 102.9%. By operating at $V_G$ of -10 and -15 V, the BHJ-EECS reached a photoresponse with long-term potentiation. Current levels after 10 light-pulse-exposure amounted to 106.7% and 124.8% with respect to initial resting states for $V_G$ of -10/-15 V, respectively (Figure S13, Supporting Information).

## 3. Conclusions

We have reported a coupled electrochemical-electret platform for organic synapses. These devices exhibited facilitation from electrochemical doping and depression from electret charging. Significantly, our EECS showed an amplitude-dependent facilitation-to-depression transition, without the need of inversing
<figure><img src="image_15.png" /><figcaption>**Figure 5.** Photomodulation of synaptic plasticity in BHJ-EECS. a) Energy level alignment in a light-irradiated BHJ-EECS. Aided by negative $V_{pre}$, excitons are efficiently dissociated into photogenerated holes and electrons, contributing to enhanced drain current. b) Photoresponse in BHJ-EECS caused a 56-fold increase in off-state drain current (measured at $V_G = 0$ V). c) Synaptic facilitation in BHJ-EECS was boosted with higher gain under light irradiation. $V_G = -15$ V. d) Synaptic depression in dark-state BHJ-EECS was enhanced by white light irradiation using LEDs with a power density of 20.0 mW cm$^{-2}$.</figcaption></figure>

the gate polarity. Therefore, the developed EECS are capable of mimicking complex processes of biological synapses. Interestingly, we discovered the plasticity transition threshold depends on the HOMO offset between channel semiconductors and electrets. Efficiency in electrochemical doping also affects the synaptic characteristics in our EECS. As a result, we have devised a novel concept for the synapse design and demonstrated threshold tunable depression-enabled excitatory synapses and inhibitory synapses. The presented EECS device exhibited good stability and reproducibility in dynamic synapse measurements. Finally, to prove the versatility of the device and the possibility to enhance its functional complexity, we imparted light responsiveness by introducing a photoactive EECS with a BHJ channel and showed that its synaptic plasticity can be switched or modulated by a combination of optical stimuli and pulsed gating. This proof-of-concept device represents a major step forward toward the next-generation organic neuromorphic devices and artificial visual-perception systems.

**Supporting Information**

Supporting Information is available from the Wiley Online Library or from the author.

**Acknowledgements**

The authors acknowledge funding by European Commission through the Marie Skłodowska Curie ETN project BORGES (GA-813863), the Interdisciplinary Thematic Institute SysChem via the IdEx Unistra (ANR-10-IDEX-0002) within the program Investissement d'Avenir program, the International Center for Frontier Research in Chemistry (icFRC), the Institut Universitaire de France (IUF) and the Chinese Scholarship Council.

**Conflict of Interest**

The authors declare no conflict of interest.

**Data Availability Statement**

The data that support the findings of this study are available from the corresponding author upon reasonable request.

**Keywords**

electrochemical doping, facilitation-to-depression transition, neuromorphic devices, organic electret memory, organic synapses, polyelectrolyte-gated organic transistors
Received: June 30, 2022
Revised: September 25, 2022
Published online: November 2, 2022

[1] A. Citri, R. C. Malenka, Neuropsychopharmacology **2008**, 33, 18.

[2] T. Ohno, T. Hasegawa, T. Tsuruoka, K. Terabe, J. K. Gimzewski, M. Aono, *Nat. Mater.* **2011**, *10*, 591.

[3] L. Q. Zhu, C. J. Wan, L. Q. Guo, Y. Shi, Q. Wan, *Nat. Commun.* **2014**, *5*, 3158.

[4] V. M. Ho, J.-A. Lee, K. C. Martin, *Science* **2011**, *334*, 623.

[5] M. London, A. Schreibman, M. Häusser, M. E. Larkum, I. Segev, *Nat. Neurosci.* **2002**, *5*, 332.

[6] C. F. Stevens, Y. Wang, *Neuron* **1995**, *14*, 795.

[7] M. Galarreta, S. Hestrin, *Nat. Neurosci.* **1998**, *1*, 587.

[8] F. Alibart, S. Pleutin, D. Guérin, C. Novembre, S. Lenfant, K. Lmimouni, C. Gamrat, D. Vuillaume, *Adv. Funct. Mater.* **2010**, *20*, 330.

[9] P. Gkoupidenis, N. Schaefer, B. Garlan, G. G. Malliaras, *Adv. Mater.* **2015**, *27*, 7176.

[10] P. Gkoupidenis, N. Schaefer, X. Strakosas, J. A. Fairfield, G. G. Malliaras, *Appl. Phys. Lett.* **2015**, *107*, 263302.

[11] Y. van de Burgt, E. Lubberman, E. J. Fuller, S. T. Keene, G. C. Faria, S. Agarwal, M. J. Marinella, A. A. Talin, A. Salleo, *Nat. Mater.* **2017**, *16*, 414.

[12] H. Wang, Q. Zhao, Z. Ni, Q. Li, H. Liu, Y. Yang, L. Wang, Y. Ran, Y. Guo, W. Hu, Y. Liu, *Adv. Mater.* **2018**, *30*, 1803961.

[13] Z. He, H. Shen, D. Ye, L. Xiang, W. Zhao, J. Ding, F. Zhang, C.-A. Di, D. Zhu, *Nat. Electron.* **2021**, *4*, 522.

[14] A. Melianas, T. J. Quill, G. LeCroy, Y. Tuchman, H. v. Loo, S. T. Keene, A. Giovannitti, H. R. Lee, I. P. Maria, I. McCulloch, A. Salleo, *Sci. Adv.* **2020**, *6*, eabb2958.

[15] Y. van de Burgt, A. Melianas, S. T. Keene, G. Malliaras, A. Salleo, *Nat. Electron.* **2018**, *1*, 386.

[16] P. C. Harkesh, C.-Y. Yang, D. Tu, J. Y. Gerasimov, A. M. Dar, A. Armada-Moreira, M. Massetti, R. Kroon, D. Bliman, R. Olsson, E. Stavrinidou, M. Berggren, S. Fabiano, *Nat. Commun.* **2022**, *13*, 901.

[17] J. D. Yuen, A. S. Dhoot, E. B. Namdas, N. E. Coates, M. Heeney, I. McCulloch, D. Moses, A. J. Heeger, *J. Am. Chem. Soc.* **2007**, *129*, 14367.

[18] D. Zhao, S. Fabiano, M. Berggren, X. Crispin, *Nat. Commun.* **2017**, *8*, 14214.

[19] J. Rivnay, S. Inal, A. Salleo, R. M. Owens, M. Berggren, G. G. Malliaras, *Nat. Rev. Mater.* **2018**, *3*, 17086.

[20] H. Ling, N. Wang, A. Yang, Y. Liu, J. Song, F. Yan, *Adv. Mater.* **Technol. 2019**, *4*, 1900471.

[21] J. Y. Gerasimov, R. Gabrielsson, R. Forchheimer, E. Stavrinidou, D. T. Simon, M. Berggren, S. Fabiano, *Adv. Sci.* **2019**, *6*, 1801339.

[22] X. Ji, B. D. Paulsen, G. K. K. Chik, R. Wu, Y. Yin, P. K. L. Chan, J. Rivnay, *Nat. Commun.* **2021**, *12*, 2480.

[23] Z. Xie, C. Zhuge, Y. Zhao, W. Xiao, Y. Fu, D. Yang, S. Zhang, Y. Li, Q. Wang, Y. Wang, W. Yue, I. McCulloch, D. He, *Adv. Funct. Mater.* **2022**, *32*, 2107314.

[24] W. Xu, S.-Y. Min, H. Hwang, T.-W. Lee, *Sci. Adv.* **2016**, *2*, e1501326.

[25] C. Zhang, S. Wang, X. Zhao, Y. Yang, Y. Tong, M. Zhang, Q. Tang, Y. Liu, *Adv. Funct. Mater.* **2021**, *31*, 2007894.

[26] J. Lenz, F. del Giudice, F. R. Geisenhof, F. Winterer, R. T. Weitz, *Nat. Nanotechnol.* **2019**, *14*, 579.

[27] J. S. Najem, M. S. Hasan, R. S. Williams, R. J. Weiss, G. S. Rose, G. J. Taylor, S. A. Sarles, C. P. Collier, *Nat. Commun.* **2019**, *10*, 3239.

[28] Y. Kim, A. Chortos, W. Xu, Y. Liu, J. Y. Oh, D. Son, J. Kang, A. M. Foudeh, C. Zhu, Y. Lee, S. Niu, J. Liu, R. Pfattner, Z. Bao, T.-W. Lee, *Science* **2018**, *360*, 998.

[29] H. Tan, Q. Tao, I. Pande, S. Majumdar, F. Liu, Y. Zhou, P. O. Å. Persson, J. Rosen, S. van Dijken, *Nat. Commun.* **2020**, *11*, 1369.

[30] Y.-H. Chou, H.-C. Chang, C.-L. Liu, W.-C. Chen, *Polym. Chem.* **2015**, *6*, 341.

[31] R. Yu, E. Li, X. Wu, Y. Yan, W. He, L. He, J. Chen, H. Chen, T. Guo, *ACS Appl Mater Interfaces* **2020**, *12*, 15446.

[32] M. J. Panzer, C. D. Frisbie, *Adv. Mater.* **2008**, *20*, 3177.

[33] L. Herlogsson, X. Crispin, S. Tierney, M. Berggren, *Adv. Mater.* **2011**, *23*, 4684.

[34] S. Fabiano, N. Sani, J. Kawahara, L. Kergoat, J. Nissa, I. Engquist, X. Crispin, M. Berggren, *Sci. Adv.* **2017**, *3*, e1700345.

[35] J. Wang, Y. Li, C. Yin, Y. Yang, T.-L. Ren, *IEEE Electron Device Lett.* **2017**, *38*, 191.

[36] T. Lei, Y. Cao, X. Zhou, Y. Peng, J. Jian, J. Pei, *Chem. Mater.* **2012**, *24*, 1762.

[37] L. Huang, Z. Wang, J. Chen, B. Wang, Y. Chen, W. Huang, L. Chi, T. J. Marks, A. Facchetti, *Adv. Mater.* **2021**, *33*, 2007041.

[38] C. Zhai, X. Yang, S. Han, G. Lu, P. Wei, A. Chumakov, E. Erbes, Q. Chen, S. Techert, S. V. Roth, P. Zhang, L. Bu, *Chem. Mater.* **2021**, *33*, 2673.

[39] H. Phan, M. Wang, G. C. Bazan, T.-Q. Nguyen, *Adv. Mater.* **2015**, *27*, 7004.

[40] Y. Chen, H. Wang, Y. Yao, Y. Wang, C. Ma, P. Samorì, *Adv. Mater.* **2021**, *33*, 2103369.

[41] X. Jiang, Y. Xu, X. Wang, Y. Wu, G. Feng, C. Li, W. Ma, W. Li, *Phys. Chem. Chem. Phys.* **2017**, *19*, 8069.