Ultrathin Conformable Organic Artificial Synapse for Wearable

Subscriber access provided by University of South Dakota

Organic Electronic Devices

Ultrathin conformable organic artificial synapse for wearable intelligent device applications Sukjae Jang, Seonghoon Jang, Eun-Hye Lee, Minji Kang, Gunuk Wang, and Tae-Wook Kim ACS Appl. Mater. Interfaces, Just Accepted Manuscript • DOI: 10.1021/acsami.8b12092 • Publication Date (Web): 10 Dec 2018 Downloaded from http://pubs.acs.org on December 15, 2018

Just Accepted “Just Accepted” manuscripts have been peer-reviewed and accepted for publication. They are posted online prior to technical editing, formatting for publication and author proofing. The American Chemical Society provides “Just Accepted” as a service to the research community to expedite the dissemination of scientific material as soon as possible after acceptance. “Just Accepted” manuscripts appear in full in PDF format accompanied by an HTML abstract. “Just Accepted” manuscripts have been fully peer reviewed, but should not be considered the official version of record. They are citable by the Digital Object Identifier (DOI®). “Just Accepted” is an optional service offered to authors. Therefore, the “Just Accepted” Web site may not include all articles that will be published in the journal. After a manuscript is technically edited and formatted, it will be removed from the “Just Accepted” Web site and published as an ASAP article. Note that technical editing may introduce minor changes to the manuscript text and/or graphics which could affect content, and all legal disclaimers and ethical guidelines that apply to the journal pertain. ACS cannot be held responsible for errors or consequences arising from the use of information contained in these “Just Accepted” manuscripts.

is published by the American Chemical Society. 1155 Sixteenth Street N.W., Washington, DC 20036 Published by American Chemical Society. Copyright © American Chemical Society. However, no copyright claim is made to original U.S. Government works, or works produced by employees of any Commonwealth realm Crown government in the course of their duties.

Page 1 of 34 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

ACS Applied Materials & Interfaces

Ultrathin conformable organic artificial synapse for wearable intelligent device applications Sukjae Jang1‡ , Seonghoon Jang2‡ , Eun-Hye Lee1, Minji Kang1, Gunuk Wang2* and TaeWook Kim1*

1Functional

Composite Materials Research Center, Institute of Advanced Composite

Materials, Korea Institute of Science and Technology, Jeollabuk-do 55324, Republic of Korea.

2KU-KIST

Graduate School of Converging Science and Technology, Korea University,

Seoul 02841, Republic of Korea.

Keywords: free-standing transistor, conformable transistor, organic artificial synapse, ferroelectric synapse, ultrathin artificial synapse

1 ACS Paragon Plus Environment

ACS Applied Materials & Interfaces 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


Page 2 of 34

Page 3 of 34 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


Abstract

Ultrathin Conformable artificial synapse platforms that can be used as on-body or wearable chips suggest a path to build next-generation, wearable, intelligent electronic systems that can mimic the synaptic operations of the human brain. So far, an artificial synapse architecture with ultimate mechanical flexibility in a free-standing form while maintaining its functionalities with high stability and accuracy on any conformable substrate has not been demonstrated yet. Here, we demonstrate the first ultrathin artificial synapse (~ 500 nm total thickness) that features free-standing ferroelectric organic neuromorphic transistors (FONTs), which can stand alone without a substrate or an encapsulation layer. Our simple dry peel-off process allows integration of the freestanding FONTs with an extremely thin film that is transferable to various conformable substrates. The FONTs exhibit excellent and reliable synaptic functions, which can be modulated by diverse electrical stimuli and relative timing (or temporal order) between the pre- and post-synaptic spikes. Furthermore, the FONTs show sustainable synaptic plasticity even under folded condition (R = 50 μm,  = 0.48%) for more than 6,000 input spikes. Our study suggests that the ultrathin conformable organic artificial synapse 3 ACS Paragon Plus Environment


platforms is considered as one of key technology for realization of wearable intelligent electronics in the future.


Page 4 of 34

Page 5 of 34 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


Introduction

For sustainable advancements in electronics technology, the field of neuromorphic electronics; i.e., electronics that imitate the principle behind biological synapses with a high degree of parallelism has recently emerged as a promising candidate for novel computing technologies as well as a way to directly couple electronic devices to biological (living) neurons without the use of emulators or intermediate stages1-6. In biological nerve systems, a synapse is a basic channel that can transmit an electrical or chemical signal between pre-synaptic and post-synaptic neurons. The degree of its connectivity (synaptic strength) can be gradually strengthened or weakened based on the relative timing of the pre-synaptic and post-synaptic spikes7-9, i.e., the neuron’s membrane potential10 or how many or what types of neurotransmitter11 have been activated. The ability for gradual change in synaptic strength is termed synaptic plasticity10, 12. The intricate signal processing in the massive networks of neurons that is generated or integrated by changes in synaptic plasticity via trillions of synapses is the fundamental foundation of learning, memory, and complex computation tasks in a brain7, 912.

The basic features of synaptic plasticity, such as short- and long-term synaptic plasticity, adaptation, and spike timing dependent plasticity (STDP), have been implemented in the recent past in wide varieties of materials and device concepts using the sequence of spatiotemporal electric programming1-2,

13-20.

These functions are expected to facilitate replication of the intelligence

feature of biological neuron networks, such as pattern and image classification21, and sensory information processing22 with excellent energy efficiency, which would lead to revolutionary technological developments in the design of artificial sensory and intelligent robots23.



Page 6 of 34

For wearable electronics technologies, an ultra-flexible neuromorphic device platform could be envisioned as an on-body intelligent chip to instantly and proactively interact with a wearer for general or specific information and sensing technology purposes24-28. Mimicking the synaptic functions of organic materials may offer great potential for applications in flexible and wearable intelligent devices due to their inherent advantages, such as softness, low-temperature processability, diverse functionalities, and even biocompatibility24,

26, 29.

These devices could

extend from a biometric sensor to a cortical neural prosthesis for enhancing memory that is implanted on the brain interface that has a highly folded and wrinkled surface30-31. Recently, there are several reports on artificial synapses based on organic field-effect transistors and memristors where various synaptic abilities have been realized16, 18-19, 32-39. Because these systems are going to be used for human being by placing on skin or clothes potentially, artificial synapses with softness or applicability to conformable and desirable surfaces is very important. Although some organic artificial synapses even in a free-standing architecture has been published recently39, it has not been proven the stability and accuracy of neuromorphic functionalities on any conformable substrates yet. Demonstrating excellent flexibility and reliable synaptic functions under the folded condition can provide a potential in the applicability of wearable intelligent electronic systems. To achieve organic artificial synapses with softness or applicability to conformable and desirable surfaces, one realistic approach is to fabricate thin devices, which significantly alleviates the bending stress in the devices and allows extraordinary mechanical flexibility40-41. Monitoring the durable synaptic ability against an extreme bending radius under repeated crumpling25,

27, 42-45,

folding46-47 and

wrinkling conditions48 is a trusted method to evaluate the degree of mechanical flexibility of intelligent devices. Therefore, to realize next generation wearable organic artificial synapses, a combination of both the fabrication process for ultra-thin organic devices and their reliable synaptic abilities is a prerequisite. 6 ACS Paragon Plus Environment

Page 7 of 34 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


To accomplish this aim, we fabricate ferroelectric organic neuromorphic transistors (FONTs) in a free-standing form with a PVDF–TrFE (polyvinylidenedifluoride–trifluoroethylene) copolymer, which is a well-known solution processable polymer with ferroelectricity and biocompatibility, as an artificial synapse. Our simple dry peel-off process (POP) and stick-on process (SOP) allowed integration of the free-standing FONTs with an extremely thin film, ~ 500 nm thick, that can stand-alone without a supporting substrate or an encapsulation layer and is transferable to various conformable substrates. The FONTs exhibited reliable switching characteristics under the influence of electrical programming regardless of the substrates and in the free-standing state. The representative synaptic functions, including the excitatory or inhibitory post-synaptic potential, short- or long-term synaptic plasticity, and symmetric and asymmetric forms of STDP were successfully demonstrated using diverse electrical stimuli or the relative timing (or temporal order) between the pre- and post-synaptic input spikes. In addition, the FONTs showed sustainable synaptic plasticity under folded condition (bending radius R = 50 μm, strain  = 0.48%) for more than 6,000 spikes.

Experimental Section

Materials and device fabrication: PVDF-TrFE (70 : 30 % mol copolymer) was purchased from Solvay. Pentacene (99.9% purity) and N,N-dimethylformamide (99.8% purity) were purchased from Sigma-Aldrich, Korea. Polydimethylsiloxane (PDMS) (Sylgard 184 Silicone Elastomer) was purchased from Dow Corning. SU-8 photoresist (SU-8 2005) was purchased from MicroChem. A thermal-shrink plastic film (PVC, 150 μm thick, SZH-SB003) was purchased from SMG. All materials were used without further purification. Heavily doped Si substrates with 100 nm SiO2 were cleaned by ultra-sonication in acetone and isopropanol for 10 min, respectively, and followed 7 ACS Paragon Plus Environment


by drying with nitrogen gas. The cleaned substrates were annealed in a convection oven for 1 hour. Au (20 nm thick) electrodes were formed on the substrates using an electron beam evaporator with a deposition rate of 0.9 Å/s at a pressure of 4  10-6 torr. A PVDF-TrFE solution was prepared by dissolving 100 mg of PVDF-TrFE in 1 ml of dimethylformamide (DMF). A PVDF-TrFE ferroelectric film (415 nm thick) was prepared by spin-coating the prepared PVDF-TrFE solution after filtration with a 0.45 µm PTFE membrane on the Au electrode at a spin rate of 1,500 rpm for 300 s and annealing the electrode at 140 °C for 2 hours in a nitrogen-filled glovebox. Pentacene (30 nm thick) and Au (35 nm thick) were evaporated as the organic semiconductor and source/drain electrode with a deposition rate of 0.2-0.3 Å/s and 1 Å/s, respectively, using a shadow mask under a pressure of 2  10-7 torr. The channel length, which were defined as the distance between the source and drain electrodes, was ~ 20 μm. The channel widths were maintained at 200 μm with source and drain electrodes of 250 μm  200 μm. A PDMS stamp was prepared by blending the silicon elastomer base (Sylgard 184) and the curing agent in a ratio of 10:1 and removing the air bubbles. The homogenous mixture was casted onto a Si wafer and cured at 70 °C for 2 hours. Finally, the free-standing ferroelectric organic neuromorphic transistors (FONTs) were obtained by mechanically peeling off the bottom gate, top-contact (BG-TC) transistors from the fabricated SiO2 substrate with a PDMS stamp and sequential supporting them on a PET film with the center region removed by a punch. Figure S1 in the Supporting Information shows the schematic procedure of our free-standing FONTs. The pentacene transistors with an SU-8 gate dielectric as control samples were fabricated by replacing PVDF-TrFE ferroelectric layers with SU-8 dielectric layers. SU-8 2005 solution (diluted with SU-8 thinner in a ratio of 1:3) was spin-casted on the Au electrode at a spin rate of 3,000 rpm for 30 s and subsequently baked at 150 °C for 30 minutes. The resulting thickness of SU-8 was measured to be around 420 nm.


Page 8 of 34

Page 9 of 34 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


Device characterization: The electrical characteristics of our FONTs were measured using a probe station and a semiconductor parameter analyzer (4145B, HP) in a nitrogen-filled glove box system or a semiconductor parameter analyzer (4155C, HP) air atmosphere, respectively. Cyclic endurance tests, retention tests and STDP measurements were performed using a semiconductor characterization system (4200-SCS, Keithley). The top and cross-sectional scanning microscope images were obtained using a field-emission scanning electron microscope (FESEM, FEI Helios) with an acceleration voltage of 2 kV after coating a thin layer of platinum. For the cross-section image, our free-standing FONT was etched by FIB. An optical microscope (Nikon Eclipse LV150) was used to examine the FONTs on various substrates. The film thickness of SU-8 was measured using a surface profilometer (Surfcorder ET 200, Kosaka, Japan).

Results and Discussion

Figure 1a shows the ultrathin and conformable FONTs consisting of pentacene/PVDFTrFE/Au bottom gate with Au electrodes as the top source and drain contact. A thin Au film (~ 20 nm) covered the whole area on the SiO2/Si wafer and acted as the back gate electrode. A solution processed organic ferroelectric film (PVDF-TrFE) was employed as both the gate dielectric and main supporting layer in the FONTs. The pentacene (p-type organic semiconductor) and Au source/drain electrodes were evaporated through different shadow masks under a vacuum in a consecutive order. The pentacene was selected as an organic semiconductor owing to its reliable p-type properties, simple thermal evaporation process, pattern facility through the shadow mask, and Ohmic contact with Au electrodes. Then, the dry peel-off process (POP) was performed, which means the fabricated FONTs were instantly mechanically exfoliated from the mother substrate 9 ACS Paragon Plus Environment


Page 10 of 34

using a polydimethylsiloxane (PDMS) stamp. The device on the PDMS stamp was completely transferred again onto the polyethylene terephthalate (PET) window frame (stick-on process, SOP), which has a sticky edge and empty hole in the center region, to complete the fabrication of the FONTs in a free-standing form (see Figure S1, Supporting Information). From the cross-sectional SEM image after focused ion beam (FIB) etching, we identified that each layer was well stacked with complete separation, and the total thickness of the device was only 500 nm including all the essential components (Figure 1b, c and S2, Supporting Information). The free-standing FONTs were successfully scaled up to ~ 3 cm × 3 cm and were semitransparent (see Figure S1, Supporting Information), which implied that the device consisted of combinations of very thin layers, as shown in Figure 1d. Although our FONTs are in a free-standing state, the charge carrier concentration of the pentacene channel is modulated by the remnant polarization states of PVDF-TrFE that are electrically programmed by the gate voltage (VGS)49. Detailed switching mechanism of the FONTs is explained in the Figure S3 (Supporting Information). Because modulating the polarization of the PVDF-TrFE layer allows the FONTs to mimic synaptic plasticity36, 47, we did further electrical analysis on FONTs for the first artificial synapse application. The gate electrode and drain electrode of the FONT correspond to the input neuron (so-called pre-synaptic neuron) and output neuron (socalled post-synaptic neuron), respectively. Whenever a spike arrives at the synapse from an input neuron and reaches the output neuron, the synapse generates a temporal dynamic response at the output neuron, which is known as a post-synaptic current (PSC)9-10,

12.

Similarly, a potential

arriving at the gate electrode in the FONT changes the degree of polarization of the organic ferroelectrics, resulting in modulation of the synaptic strength (i.e. conductance of the pentacene channel).


Page 11 of 34 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


We examined the transfer characteristics (IDS-VGS) of the ultrathin and conformable FONT in a free-standing form (Figure 2a). The length (L) and width (W) of the channel were measured to be 20 μm and 200 μm, respectively. Note that the level of gate leakage current remains in sub-1 nA level when the gate voltage was swept between ±30 V with VDS = –10 V (Figure S4, Supporting Information). Note here, although the ON-OFF ratio and the relatively high operating voltages of the FONT require further optimization and improvement for desirable synaptic functionalities, the evaluations of free-standing FONTs under diverse bending conditions as an artificial synapse could provide a framework of applicability for wearable intelligent electronic applications. The neuromorphic devices mimic the synaptic functions with synaptic input spikes, which have widths from tens to hundreds of milliseconds7-9, 12. For the sake of faster operation with instantaneous spike, other semiconductor with higher performance can replace the pentacene. The applied negative input potential enhances the hole accumulation at the interface between the pentacene and PVDF-TrFE, and potentiates the synaptic strength, which allows more drain current flow and is indicative of the excitatory post-synaptic current9,

12.

By contrast, the positive input potential

depresses the synaptic strength, inducing the inhibitory post-synaptic current9. A complete transition between the potentiation and depression in the synaptic strength can be implemented via a basic switching operation in the non-volatile ferroelectric memory transistors. In addition, the FONTs kept their stable switching operation for 300 times repeated transfer I-V characteristics measurement in air atmosphere. (see Figure S5, Supporting Information). Figure 2b shows the cycling between the two completed states for the potentiation (writing) and depression (erasing) of the free-standing FONTs. Based on the retention characteristics, the free-standing FONTs retained their completely potentiated or depressed states for more than 104 s, which is indicative of longterm memory characteristics (Figure 2c). These experimental results indicated reliable and complete synaptic transitions in the FONTs in a free-standing state. Similar results were observed 11 ACS Paragon Plus Environment


Page 12 of 34

for the as-fabricated FONTs on wafers (see Figure S6, Supporting Information). The specific measurement procedure, method, device optimization and movie clips are provided in the Supporting Information (Figure S1-10 and Movie S1-6). To examine durability of the device under artificially controlled stress conditions, we transferred the FONTs to a special substrate, a thermal-shrink plastic film. The transferred FONTs were heated to 55 and 60 °C for 10 s using a hot plate. Under those circumstances, the FONTs experienced extremely stressed conditions, which led to the complex 3-dimensional distortions in their physical dimensions that occur in clothing when it is worn. The FONTs maintained their switching characteristics in anomalous substrate morphologies (Figure 2d, e). To further verify the availability of the FONTs on unconventional substrates, the FONTs were placed on various conformable substrates, such as a textile, jelly, candy, and toothbrush (Figure 2f and Figure S10, Supporting Information). All the transferred FONTs exhibited outstanding flexibility and conformability and the same hysteresis behavior, as shown in Figure 2a. We summarized the hysteresis windows and ON-OFF ratios during the input potential sweeping for the transferred substrates in Figure 2g. In these reasons, we believe that our dry transfer process (POP and SOP) is applicable as a universal technique for fabrication of ultrathin and conformable electronic devices with free-standing form. The synaptic plasticity in the neuron network in the brain is widely considered the primary basis for learning, memory, and recognition9-10, 12. There are two basic classifications of synaptic plasticity based on a temporal or persistent change in the synaptic strength: (i) short-term plasticity and (ii) long-term plasticity. Generally, the time scale of short-term plasticity is approximately hundreds to thousands of milliseconds, and the synaptic strength in that relevant time scale will quickly decay to its original state. This is believed to serve as a major neural substrate for dynamic synapse behaviors that endow a brain with computational roles9-10, 12 ACS Paragon Plus Environment

12.

By contrast, long-term

Page 13 of 34 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


plasticity is defined by a long-lasting change in the synaptic strength (from few minutes to days, even a lifetime), which has two forms in terms of excitatory and inhibitory synaptic transmissions — long-term potentiation (LTP) and long-term depression (LTD)9-10, 12. Synaptic strength is determined by the amplitude of the PSC in the output (post-synaptic) neuron while generating a single input spike in the input (pre-synaptic) neuron, as shown in the schematics in Figure 3a. By delivering a sufficient input spike (with –30 V for 500 ms) to the presynaptic neuron, the post-synaptic neuron was excited. The PSC increased from 1.12 × 10-11 to 6.24 × 10-11 A and remained its changed state, which is analogous to the LTP feature of the synapse. In contrast, the PSC returned to its original state when a shorter input spike, –30 V for 100 ms, was applied, which is analogous to the short-term potentiation (STP) feature of the synapse. These phenomena originate from the remnant polarization degree of the PVDF-TrFE layer based on the different gate voltage pulses36, 47, 49. If the polarizations are downward by a sufficient negative gate voltage pulse, the majority carriers (holes) of the pentacene are accumulated, and the carrier concentration is saturated to a certain point, which is indicative of a reduction in the channel resistance and results in an improvement in the PSC. However, if a single gate voltage pulse is not sufficient for the remnant polarization, leading to insufficient accumulation of charge carriers at the interface between pentacene and PVDF-TrFE, the PSC returns to its initial level (Figure S3, Supporting Information). Figure 3b shows the change in the PSC when two different pulse trains (interval tint = 10 s), input spikes of –30 V for 100 ms and 500 ms, were accumulated on the presynaptic neuron. In the case of the pulse train of –30 V for 500 ms, the PSC had two distinct behaviors according to the total number of applied input pulses. At the beginning of the pulse train (from 1 to 10 pulses), the PSC level linearly increased as a function of time (the upper left panel of Figure 3b). Note that the gradually increased intermediate PSC levels depending on the numbers of cumulative pulses are maintained for a sufficient retention time (500 s) even when no following 13 ACS Paragon Plus Environment


input pulse is applied (Figure S11, Supporting Information). However, at the end of the pulse train (from 90 to 100 pulses), the PSC level was almost saturated (the upper right panel of Figure 3b). Thus, the PSC responses mimicked a synaptic saturation, which prevents uncontrolled growth of synaptic strengths and excessive neural firing50. By contrast, in the case of the shorter pulse train (pulse width = 100 ms and tint = 10 s), the final PSC level did not change, regardless of the number of applied pulses. Interestingly, however, the PSC levels can increase and be rapidly saturated if the tint is smaller (tint = 0.5 and 1 s, Figure S12, Supporting Information). In that case, the following input pulses stimulate the pre-synaptic neuron before their former responses are completely attenuated (i.e., PSC). Namely, they can promote the accumulation of hole carriers in the pentacene by enhancing the polarization of PVDF-TrFE, leading to a rapid increase in the cumulative carrier concentration. The interval dependence on the change in the PSC is phenomenologically analogous to pared-pulse facilitation (PPF) of synapses (Figure S12, Supporting Information)9. By contrast, when a sufficient input pulse train (pulse width = 500 ms) was applied, the rate of increase in the PSC as a function of the number of applied spikes was constant regardless of the interval (tint = 1 and 10 s, Figure S13, Supporting Information). Because the remnant polarization was maintained during the interval time by the sufficient stimulation, resulting in similar PSC response for both interval times (1 and 10 s). In a chemical synapse, high-frequency repeated input spikes on a presynaptic neuron can lead to a greater release of neurotransmitters in synaptic vesicles by increasing the Ca2+ concentration in the nerve terminal10. From an operational principle point of view, the neurotransmitters can be considered hole carriers in the pentacene and the Ca2+ concentration is the polarization degree of the PVDF-TrFE layer. It is important to lower the magnitude and width of the programming pulse in order to realize energy-efficient synaptic device, because the magnitude of applied programming pulse can


Page 14 of 34

Page 15 of 34 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


determine the consumed energy for the learning and recognition process. The energy consumption (Espike) of the FONT can be estimated based on the following equation: Espike = Vin    PSCpeak

(1)

where Vin and  are the amplitude and the width of applied input pulse and PSCpeak is the average PSC point during applying the input pulse. Considering Vin = –30 V,  = 500 ms, and PSCpeak = 2.53 nA in Figure 3a, the Espike can be estimated to be 37.95 nJ that is a bit higher than other reported synaptic devices35, 37-39. We should note here that the energy consumption could be further reduced by the scaling down the FONTs. In addition, the replacement of an organic semiconductor with higher mobility and a dielectric film with a higher capacitance as the FONTs constitutes can lower the required programming voltage and enables to respond quickly even at the pre-synaptic input spike. To mimic excitatory and inhibitory synapses that exhibit LTP and LTD, we controlled the PSC level by adjusting the amplitude, polarity, and width of the input spike pulse. The PSC was monitored while applying a total of 120 potentiating/depressing input pulses with different amplitudes and polarities, from ±10 V to ±30 V with ΔV = ±5 V, on the pre-synaptic neuron (Figure 3c). A larger change in the PSC was observed for both the LTP and LTD when stronger input pulses, i.e., higher amplitudes, were applied. For example, because +30 V input pulse is strong enough to align the ferroelectric domains of the PVDF-TrFE, only 20 potentiating input pulses can polarize the PVDF-TrFE completely, resulting in the saturating PSC values after that. On the other hand, because +10 V input pulse is not enough to polarize its domains, the PSC can be consistently increased even when the number of applied input pulses is 60 times (Figure 3c). Similarly, when the pulse duration increased, the change in the PSC was also larger as shown in Figure 3d (Figure S14, Supporting Information), which is consistent with Figure 3a and 3b. Note that longer pulse



duration can align the ferroelectric domains of the PVDF-TrFE more than short pulse duration and accumulate more charges at the interface, resulting in the larger PSC (Figure 3d). In biological neuron networks, the synaptic strength can also be modulated via concerted preand post-synaptic spikes with a tight temporal correlation7-8. This feature is known as STDP behavior and is an essential feature of the Hebbian learning rule8. This behavior is induced by a causal interaction between the remaining neurotransmitters at the axon of a pre-synaptic neuron after the input spike and the back-propagating spike at the dendrite of a post-synaptic neuron. Diverse types of STDP functions have been experimentally investigated in biological synapses and mimicked in diverse device forms15, 17, 20, 32, 35. There are two main features of the STDP forms (e.g., (i) symmetric and (ii) asymmetric STDP functions)8. For example, in some cases, (i) the synaptic strength change is only determined by the relative timing of the pre- and post-synaptic spikes. In other cases, (ii) the synaptic strength change is determined by both the relative timing and temporal order between the pre- and post-synaptic spikes. To examine the two STDP features, pre-synaptic and post-synaptic spikes were applied with different relative timing, Δt = tpost – tpre, and the synaptic strength changes were measured (Figure 3e, f). By applying a single spike for pre- and post-neuron, the symmetric form of STDP was successfully extracted. When Δt = 0, both the pre- and post-synaptic neurons were simultaneously active, and the change in the synaptic strength (%) showed the largest increase over the whole Δt because of the synchronous activation of both spikes (Figure 3e). This change, however, gradually decreased as the relative timing of both spikes increased, regardless of their temporal order, which mimicked the symmetric feature of the Hebbian learning rule8. To mimic the asymmetric STDP function, we designed and applied specific pulse trains to their corresponding neurons for the preand post-synaptic spikes (Inset illustration in Figure 3f and Figure S15, Supporting Information). Each pulse train applied to the corresponding neuron cannot individually change the synaptic 16 ACS Paragon Plus Environment

Page 16 of 34

Page 17 of 34 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


strength. Details of the applied pulse train and overlapping pulse form based on Δt are provided in the Supporting Information (Figure S15). When Δt > 0 (denoted Pre-Post pair); i.e., the pre-synaptic spike arrives before the post-synaptic spike, the combination of these pulses can result in negative input pulses, enabling the LTP of the synapse. However, when Δt < 0 (denoted Post-Pre pair); i.e., the post-synaptic spike arrives before the pre-synaptic spike, the combination of these pulses can result in positive input pulses, enabling the LTD of the synapse (Figure 3f). When the absolute Δt value increased, the synaptic weight remained constant due to the insufficient and asynchronous stimulation of the input pulses. Using that pulse programming, the asymmetric form of STDP was mimicked. Next-generation flexible and wearable artificial synapse devices or neural prostheses must be able to sustain stable synaptic functions under extremely small bending radii and conform to diverse, distorted surfaces. We already confirmed stable synaptic plasticity of the free-standing FONTs in the flat state in Figure 3. In order to verify that the FONTs maintain their stable synaptic characteristics even under extreme bending conditions, we designed and prepared two extreme, distorted surface conditions a brain-like surface and folded conditions) and investigated the synaptic features of the free-standing FONTs under these conditions. First, we transferred the freestanding FONTs onto the brain-shaped PDMS mold to demonstrate the conformability of the FONTs on a brain-like interface with a highly folded and wrinkled surface (roughness ~ a few mm) (Upper panel of Figure 4a and Figure S16, Supporting Information). Second, we completely folded the free-standing FONTs into a small bending radius of 50 µm (Lower panel of Figure 4a and Figure S17, Supporting Information). The PSCs were measured while applying total of 60 potentiating/depressing input pulses with different polarities, ±30 V, for 500 ms. Under both conditions, the FONTs well maintained their abilities and showed LTP and LTD features (Figure 4b). Figure 4c shows the stable LTP and LTD features for different pulse widths from 100 to 500 17 ACS Paragon Plus Environment


ms under the folded conditions. Furthermore, we demonstrated that the folded FONTs exhibited an ultra-stable transition between the LTP and LTD and a uniform change in the PSC level over 6,000 spikes of pre-synaptic pulses (Figure 4d). Negligible differences in repetitive LTP and LTD operations between the initial 10 cycles (left upper panel) and the last 10 cycles (right upper panel) reveals the robustness of performances of FONTs at extremely deformed conditions. Here, we focused on mimicking the basic features of synaptic plasticity, such as STP, LTP, LTD and STDP, of an individual synapse using the ultrathin and conformable FONTs with high stability and accuracy. For more complex neural processing in a wearable platform, further investigations on conformable neural network circuits are required for the implement of truly wearable intelligent electronics.


Page 18 of 34

Page 19 of 34 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


Conclusions

In summary, an ultrathin conformable artificial synapse based on a free-standing FONT (~ 500 nm total thickness) was successfully fabricated using a simple dry POP and SOP method and was stably transferred to various uneven substrates, such as thermal-shrink plastic film, jelly, textile, candy, toothbrush, and brain mold. Using diverse spatiotemporal electrical pulse programming, the basic synaptic functions (STP, LTP, LTD, and STDP) of the FONTs were demonstrated to be stable in a free-standing form and under extremely harsh conditions, such as on a brain mold and folded into a bending radius as small as 50 μm. We believe that the extraordinary stability and reliability of the synaptic functions of the free-standing FONTs will promote their feasibility as a basic component for mimicking artificial synapses and the possibility of nextgeneration wearable intelligent device applications.



Figures

Figure 1. Images of organic artificial synapses using free-standing FONTs. (a) Schematic device structure of the FONTs and molecular structures of PVDF-TrFE and pentacene. The length (L) and width (W) of the channel were measured to be 20 μm and 200 μm, respectively. (b) Cross-sectional SEM image of a FONT in a free-standing form. (c) Magnified cross-sectional SEM image. The total thickness of the FONT is approximately 500 nm. (d) Photograph of a large-scale array of semi-transparent free-standing FONTs (total size = 3  3 cm2). 20 ACS Paragon Plus Environment

Page 20 of 34

Page 21 of 34 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


Figure 2. Stable electrical characteristics of FONTs. (a) Transfer characteristics of the freestanding FONTs. (b) Cyclic endurance test of the FONT between completely potentiated and depressed states for 500 times. (c) Retention characteristics of the FONT. (d), (e) 3-dimensional distorted FONTs on thermally shrunken plastic films that were heated at 55 and 60 °C. Left images and right graph show the photograph and transfer characteristics, respectively. (f) Transferred freestanding FONTs on diverse substrates (SiO2, free-standing state, textile, toothbrush, jelly, and candy). (g) Summary of the hysteresis windows (upper red graph) and read-out ON-OFF ratios at 0 V (lower blue graph) for the conformed FONTs on substrates. 21 ACS Paragon Plus Environment


Figure 3. Synaptic characteristics of the FONTs. (a) The PSC responses for different, single presynaptic pulses of –30 V for 100 ms (red line) and 500 ms (blue line). The upper panels represent a schematic biological synapse (left) and the corresponding equivalent circuit of the FONT synapse (right). (b) The PSC responses that were triggered by the pre-synaptic pulse trains (100 pulses, 22 ACS Paragon Plus Environment

Page 22 of 34

Page 23 of 34 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


interval tint = 10 s) with widths of 100 ms (red line) and 500 ms (blue line). The upper graph shows the PSC change for the initial (left) and final (right) ten pulses. (c) The PSC as a function of the number of pulses with different amplitudes (from ±10 V to ±30 V) and a fixed width of 500 ms. (d) 3-dimensional contour plot of the PSC as a function of the pulse width (from 100 ms to 1,500 ms with 100 ms step) and number of pulses (30 potentiating pulses with –30 V and 30 depressing pulses with +30 V). (e), (f) Implementation of the symmetric and asymmetric STDP of the FONT synapse, respectively. Synaptic strength changes were plotted as a function of the relative timing (Δt) and temporal order between the pre-synaptic and post-synaptic spikes. Pre-synaptic and postsynaptic spikes of –20 V and 20 V were applied, respectively, with a width of 100 ms to determine the symmetric STDP. The detailed forms of the pulse trains for asymmetric STDP were shown in Figure S15.



Figure 4. Synaptic characteristics of the FONTs under two extreme bending conditions. (a) Images of the conformable FONTs on the brain-shaped PDMS mold (upper panel) and completely folded FONTs (lower panel, bending radius ~ 50 μm). (b) Implementation of LTP (500 ms, –30 V) and LTD (500 ms, +30 V) for the FONT on the brain mold (black line) and the folded FONT (red line). (c) The PSC response of the folded FONT depending on the pulse width and the number of pulses (30 potentiating pulses with –30 V and 30 depressing pulses with +30 V). (d) Repetitive LTP and LTD operations in the folded FONT during 6,000 spikes of pre-synaptic pulses (±30 V for 500 ms). One cycle was 30 potentiating pulses and the subsequent 30 depressing pulses. The upper graph shows the LTP and LTD during the initial (left, red line) and final (right, blue line) 10 cycles, respectively. All the PSCs were measured with an applied bias of –10 V on the post-synaptic neuron.


Page 24 of 34

Page 25 of 34 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


ASSOCIATED CONTENT

Supporting Information.

The following files are available free of charge. Strain calculation of the folded FONT, schematics for the transfer procedure of the FONTs by dry POP and SOP, schematic of the cross-section of FONT, schematics for operating mechanism of FONT, the average transfer characteristics of the FONTs, electrical characteristics of the fabricated FONTs on SiO2 substrate, transfer characteristics of the FONTs with different thicknesses, electrical characteristics of the transistors with SU-8, AFM image of PVDF-TrFE, transfer characteristics of the conformable FONTs on various substrates, retention characteristics of the intermediate PSC states, the PSC response stimulated by potentiating pulses, the detailed pulse train scheme for mimicking the asymmetric STDP, electrical characteristics of the transferred FONT on the brain mold and electrical characteristics of the folded FONTs (PDF) Movie s1, the FONT in a free-standing state during the transfer characteristics measurement (AVI)



Movie s2, the organic transistor with an SU-8 gate dielectric in a free-standing form during measurements of the transfer characteristics (AVI) Movie s3, the FONT conformed to a jelly during measurements of the transfer characteristics (AVI) Movie s4, the FONT attached to a toothbrush during measurements of the transfer characteristics (AVI) Movie s5, the FONT conformed to a candy during measurements of the transfer characteristics (AVI) Movie s6, the folded FONT into a small banding radius of 50 µm during measurements of the transfer characteristics (AVI)

AUTHOR INFORMATION

Corresponding Author *Email: [email protected] and [email protected]

Author Contributions


Page 26 of 34

Page 27 of 34 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


‡These authors contributed equally.

Notes The authors declare no competing financial interest.

ACKNOWLEDGMENTS

This work was supported by the Korea Institute of Science and Technology (KIST) Young Fellow

Program,

the

National

Research

Foundation

of

Korea

(NRF-

2016R1C1B2007330), the KU-KIST research fund, Samsung Electronics, and the KU Future Research Grant.

References

(1) Kuzum, D.; Yu, S.; Wong, H.-S. P. Synaptic Electronics: Materials, Devices and Applications. Nanotechnology 2013, 24 (38), 382001. (2) Jeong, D. S.; Kim, I.; Ziegler, M.; Kohlstedt, H. Towards Artificial Neurons and Synapses: a Materials Point of View. RSC Adv. 2013, 3 (10), 3169-3183. (3) Hasler, J.; Marr, B. Finding a Roadmap to Achieve Large Neuromorphic Hardware Systems. Front. Neurosci. 2013, 7 (118).



(4) Merolla, P. A.; Arthur, J. V.; Alvarez-Icaza, R.; Cassidy, A. S.; Sawada, J.; Akopyan, F.; Jackson, B. L.; Imam, N.; Guo, C.; Nakamura, Y.; Brezzo, B.; Vo, I.; Esser, S. K.; Appuswamy, R.; Taba, B.; Amir, A.; Flickner, M. D.; Risk, W. P.; Manohar, R.; Modha, D. S. A Million Spiking-neuron Integrated Circuit with a Scalable Communication Network and Interface. Science 2014, 345 (6197), 668-673. (5) Sheridan, P. M.; Cai, F.; Du, C.; Ma, W.; Zhang, Z.; Lu, W. D. Sparse Coding with Memristor Networks. Nat. Nanotechnol. 2017, 12 (8), 784-789. (6) Chiolerio, A.; Chiappalone, M.; Ariano, P.; Bocchini, S. Coupling Resistive Switching Devices with Neurons: State of the Art and Perspectives. Front. Neurosci. 2017, 11 (70). (7) Bi, G.; Poo, M. Synaptic Modification by Correlated Activity: Hebb's Postulate Revisited. Annu. Rev. Neurosci. 2001, 24 (1), 139-166. (8) Caporale, N.; Dan, Y. Spike timing–dependent plasticity: A Hebbian Learning Rule. Annu. Rev. Neurosci. 2008, 31 (1), 25-46. (9) Kandel, E. R.; Schwartz, J. H.; Jessell, T. M.; Siegelbaum, S. A.; Hudspeth, A. J. Principles of Neural Science, 5 ed.; McGraw-Hill, New York: 2012. (10) Ho, V. M.; Lee, J.-A.; Martin, K. C. The Cell Biology of Synaptic Plasticity. Science 2011, 334 (6056), 623-628. (11) Lodish, H.; Berk, A.; Zipursky, S. L.; Matsudaira, P.; Baltimore, D.; Darnell, J. Molecular cell biology, 4 ed.; W. H. Freeman, New York: 2000. (12) Abbott, L. F.; Regehr, W. G. Synaptic Computation. Nature 2004, 431 (7010), 796-803. (13) Ohno, T.; Hasegawa, T.; Tsuruoka, T.; Terabe, K.; Gimzewski, J. K.; Aono, M. Shortterm Plasticity and Long-term Potentiation Mimicked in Single Inorganic Synapses. Nat. Mater. 2011, 10 (8), 591-595.


Page 28 of 34

Page 29 of 34 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


(14) Chanthbouala, A.; Garcia, V.; Cherifi, R. O.; Bouzehouane, K.; Fusil, S.; Moya, X.; Xavier, S.; Yamada, H.; Deranlot, C.; Mathur, N. D.; Bibes, M.; Barthelemy, A.; Grollier, J. A ferroelectric Memristor. Nat. Mater. 2012, 11 (10), 860-864. (15) Nishitani, Y.; Kaneko, Y.; Ueda, M.; Morie, T.; Fujii, E. Three-terminal Ferroelectric Synapse Device with Concurrent Learning Function for Artificial Neural Networks. J. Appl. Phys. 2012, 111 (12), 124108. (16) Liu, Y. H.; Zhu, L. Q.; Feng, P.; Shi, Y.; Wan, Q. Freestanding Artificial Synapses based on Laterally Proton-coupled Transistors on Chitosan Membranes. Adv. Mater. 2015, 27 (37), 5599-5604. (17) Wang, Z.; Joshi, S.; Savel’ev, S. E.; Jiang, H.; Midya, R.; Lin, P.; Hu, M.; Ge, N.; Strachan, J. P.; Li, Z.; Wu, Q.; Barnell, M.; Li, G.-L.; Xin, H. L.; Williams, R. S.; Xia, Q.; Yang, J. J. Memristors with Diffusive Dynamics as Synaptic Emulators for Neuromorphic computing. Nat. Mater. 2016, 16, 101-110. (18) Gkoupidenis, P.; Koutsouras, D. A.; Malliaras, G. G. Neuromorphic Device Architectures with Global Connectivity through Electrolyte Gating. Nat. Commun. 2017, 8, 15448. (19) van de Burgt, Y.; Lubberman, E.; Fuller, E. J.; Keene, S. T.; Faria, G. C.; Agarwal, S.; Marinella, M. J.; Alec Talin, A.; Salleo, A. A Non-volatile Organic Electrochemical Device as a Low-voltage Artificial Synapse for Neuromorphic Computing. Nat. Mater. 2017, 16 (4), 414-418. (20) Boyn, S.; Grollier, J.; Lecerf, G.; Xu, B.; Locatelli, N.; Fusil, S.; Girod, S.; Carrétéro, C.; Garcia, K.; Xavier, S.; Tomas, J.; Bellaiche, L.; Bibes, M.; Barthélémy, A.; Saïghi, S.; Garcia, V. Learning through Ferroelectric Domain Dynamics in Solid-state Synapses. Nat. Commun. 2017, 8, 14736.



(21) Yao, P.; Wu, H.; Gao, B.; Eryilmaz, S. B.; Huang, X.; Zhang, W.; Zhang, Q.; Deng, N.; Shi, L.; Wong, H.-S. P.; Qian, H. Face Classification using Electronic Synapses. Nat. Commun. 2017, 8, 15199. (22) Osswald, M.; Ieng, S.-H.; Benosman, R.; Indiveri, G. A Spiking Neural Network Model of 3D Perception for Event-based Neuromorphic Stereo Vision Systems. Sci. Rep. 2017, 7, 40703. (23) Booklet | Brain-inspired Intelligent Robotics: The Intersection of Robotics and Neuroscience Sciences. Science 2016, 354 (6318), 1445-1445. (24) Chan, M.; Estève, D.; Fourniols, J.-Y.; Escriba, C.; Campo, E. Smart Wearable Systems: Current Status and Future Challenges. Artif. Intell. Med. 2012, 56 (3), 137-156. (25) Webb, R. C.; Bonifas, A. P.; Behnaz, A.; Zhang, Y.; Yu, K. J.; Cheng, H.; Shi, M.; Bian, Z.; Liu, Z.; Kim, Y.-S.; Yeo, W.-H.; Park, J. S.; Song, J.; Li, Y.; Huang, Y.; Gorbach, A. M.; Rogers, J. A. Ultrathin Conformal Devices for Precise and Continuous Thermal Characterization of Human Skin. Nat. Mater. 2013, 12 (10), 938-944. (26) Stoppa, M.; Chiolerio, A. Wearable Electronics and Smart Textiles: A Critical Review. Sensors 2014, 14 (7), 11957-11992. (27) Son, D.; Lee, J.; Qiao, S.; Ghaffari, R.; Kim, J.; Lee, J. E.; Song, C.; Kim, S. J.; Lee, D. J.; Jun, S. W.; Yang, S.; Park, M.; Shin, J.; Do, K.; Lee, M.; Kang, K.; Hwang, C. S.; Lu, N.; Hyeon, T.; Kim, D.-H. Multifunctional Wearable Devices for Diagnosis and Therapy of Movement Disorders. Nat. Nanotechnol. 2014, 9 (5), 397-404. (28) Gao, W.; Emaminejad, S.; Nyein, H. Y. Y.; Challa, S.; Chen, K.; Peck, A.; Fahad, H. M.; Ota, H.; Shiraki, H.; Kiriya, D.; Lien, D.-H.; Brooks, G. A.; Davis, R. W.; Javey, A. Fully Integrated Wearable Sensor Arrays for Multiplexed in situ Perspiration Analysis. Nature 2016, 529 (7587), 509-514. 30 ACS Paragon Plus Environment

Page 30 of 34

Page 31 of 34 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


(29) Yu, Y.; Sun, H.; Orbay, H.; Chen, F.; England, C. G.; Cai, W.; Wang, X. Biocompatibility and in vivo operation of Implantable Mesoporous PVDF-based Nanogenerators. Nano Energy 2016, 27, 275-281. (30) Berger, T. W.; Hampson, R. E.; Song, D.; Goonawardena, A.; Marmarelis, V. Z.; Deadwyler, S. A. A Cortical Neural Prosthesis for Restoring and Enhancing Memory. J. Neural Eng. 2011, 8 (4), 046017. (31) Teo, A. J. T.; Mishra, A.; Park, I.; Kim, Y.-J.; Park, W.-T.; Yoon, Y.-J. Polymeric Biomaterials for Medical Implants and Devices. ACS Biomater. Sci. Eng. 2016, 2 (4), 454-472. (32) Alibart, F.; Pleutin, S.; Bichler, O.; Gamrat, C.; Serrano-Gotarredona, T.; LinaresBarranco, B.; Vuillaume, D. A Memristive Nanoparticle/Organic Hybrid Synapstor for Neuroinspired Computing. Adv. Funct. Mater. 2012, 22 (3), 609-616. (33) Gkoupidenis, P.; Schaefer, N.; Garlan, B.; Malliaras, G. G. Neuromorphic Functions in PEDOT:PSS Organic Electrochemical Transistors. Adv. Mater. 2015, 27 (44), 7176-7180. (34) Qian, C.; Sun, J.; Kong, L.-a.; Gou, G.; Yang, J.; He, J.; Gao, Y.; Wan, Q. Artificial Synapses Based on in-plane Gate Organic Electrochemical Transistors. ACS Appl. Mater. Interfaces 2016, 8 (39), 26169-26175. (35) Xu, W.; Min, S.-Y.; Hwang, H.; Lee, T.-W. Organic Core-sheath Nanowire Artificial Synapses with Femtojoule Energy Consumption. Sci. Adv. 2016, 2 (6), e1501326. (36) Kim, E. J.; Kim, K. A.; Yoon, S. M. Investigation of the Ferroelectric Switching Behavior of P(VDF-TrFE)-PMMA Blended Films for Synaptic Device Applications. J. Phys. DAppl. Phys. 2016, 49 (7), 075105. (37) Xiao, Z.; Huang, J. Energy-Efficient Hybrid Perovskite Memristors and Synaptic Devices. Adv. Electron. Mater. 2016, 2, 1600100. 31 ACS Paragon Plus Environment


(38) Xu, W.; Nguyen, T. L.; Kim, Y.-T.; Wolf, C.; Pfattner, R.; Lopez, J.; Chae, B.-G.; Kim, S.-I.; Lee, M. Y.; Shin, E.-Y.; Noh, Y.-Y.; Oh, J. H.; Hwang, H.; Park, C.-G.; Woo, H. Y.; Lee, T.-W. Ultrasensitive Aritificial Synapse based on Conjugated Polyelectrolyte. Nano Energy. 2018, 48, 575-581. (39) Fu, Y.; Kong, L.; Chen, Y.; Wang, J.; Qian, C.; Yuan, Y.; Sun, J.; Gao, Y.; Wan, Q. Flexible Neuromorphic Architectures Based on Self-Supported Multiterminal Organic Transistors. ACS Appl. Mater. Interfaces. 2018, 10(31), 26443-26450. (40) Sekitani, T.; Zschieschang, U.; Klauk, H.; Someya, T. Flexible Organic Transistors and Circuits with Extreme Bending Stability. Nat. Mater. 2010, 9 (12), 1015-1022. (41) Chortos, A.; Liu, J.; Bao, Z. Pursuing Prosthetic Electronic Skin. Nat. Mater. 2016, 15 (9), 937-950. (42) Kim, D.-H.; Lu, N.; Ma, R.; Kim, Y.-S.; Kim, R.-H.; Wang, S.; Wu, J.; Won, S. M.; Tao, H.; Islam, A.; Yu, K. J.; Kim, T.-i.; Chowdhury, R.; Ying, M.; Xu, L.; Li, M.; Chung, H.J.; Keum, H.; McCormick, M.; Liu, P.; Zhang, Y.-W.; Omenetto, F. G.; Huang, Y.; Coleman, T.; Rogers, J. A. Epidermal Electronics. Science 2011, 333 (6044), 838-843. (43) Kaltenbrunner, M.; Sekitani, T.; Reeder, J.; Yokota, T.; Kuribara, K.; Tokuhara, T.; Drack, M.; Schwodiauer, R.; Graz, I.; Bauer-Gogonea, S.; Bauer, S.; Someya, T. An Ultralightweight Design for Imperceptible plastic electronics. Nature 2013, 499 (7459), 458463. (44) Fukuda, K.; Takeda, Y.; Yoshimura, Y.; Shiwaku, R.; Tran, L. T.; Sekine, T.; Mizukami, M.; Kumaki, D.; Tokito, S. Fully-printed High-performance Organic Thin-film Transistors and Circuitry on one-micron-thick Polymer Films. Nat. Commun. 2014, 5, 4147.


Page 32 of 34

Page 33 of 34 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


(45) Fukuda, K.; Sekine, T.; Shiwaku, R.; Morimoto, T.; Kumaki, D.; Tokito, S. Free-standing Organic Transistors and Circuits with sub-micron Thicknesses. Sci. Rep. 2016, 6, 27450. (46) Zhang, L.; Wang, H.; Zhao, Y.; Guo, Y.; Hu, W.; Yu, G.; Liu, Y. Substrate-free Ultraflexible Organic Field-effect Transistors and Five-stage Ring Oscillators. Adv. Mater. 2013, 25 (38), 5455-5460. (47) Kim, R. H.; Kim, H. J.; Bae, I.; Hwang, S. K.; Velusamy, D. B.; Cho, S. M.; Takaishi, K.; Muto, T.; Hashizume, D.; Uchiyama, M.; André, P.; Mathevet, F.; Heinrich, B.; Aoyama, T.; Kim, D.-E.; Lee, H.; Ribierre, J.-C.; Park, C. Non-Volatile Organic Memory with Submillimetre Bending Radius. Nat. Commun. 2014, 5, 3583. (48) Salvatore, G. A.; Münzenrieder, N.; Kinkeldei, T.; Petti, L.; Zysset, C.; Strebel, I.; Büthe, L.; Tröster, G. Wafer-scale Design of Lightweight and Transparent Electronics that Wraps around Hairs. Nat. Commun. 2014, 5, 2982. (49) Khan, M. A.; Bhansali, U. S.; Alshareef, H. N. High-performance Non-volatile Organic Ferroelectric Memory on Banknotes. Adv. Mater. 2012, 24 (16), 2165-2170. (50) Sun, Y. G.; Beierlein, M. Receptor Saturation Controls Short-term Synaptic Plasticity at Corticothalamic Synapses. J. Neurophysiol. 2011, 105 (5), 2319-2329.



Graphical Table of Contents.


Page 34 of 34

Ultrathin Conformable Organic Artificial Synapse for Wearable

Recommend Documents