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Light-stimulated Synaptic Devices Utilizing Interfacial Effect of Organic Field-effect Transistors Shilei Dai, Xiaohan Wu, Dapeng Liu, Yingli Chu, Kai Wang, Ben Yang, and Jia Huang ACS Appl. Mater. Interfaces, Just Accepted Manuscript • DOI: 10.1021/acsami.8b05036 • Publication Date (Web): 07 Jun 2018 Downloaded from http://pubs.acs.org on June 7, 2018

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ACS Applied Materials & Interfaces

Light-stimulated Synaptic Devices Utilizing Interfacial Effect of Organic Field-effect Transistors Shilei Dai, Xiaohan Wu, Dapeng Liu, Yingli Chu, Kai Wang, Ben Yang, Jia Huang* Interdisciplinary Materials Research Center, School of Materials Science and Engineering, Key Laboratory of Advanced Civil Engineering Materials, Ministry of Education, Tongji University, Shanghai, 201804, P. R. China. KEYWORDS. Organic synaptic device; Photon; Organic field-effect transistor; Interfacial charge trapping effect; Memory and learning behavior ABSTRACT: Synaptic transistors stimulated by light-waves or photons may offer advantages to the devices such as wide bandwidth, ultrafast signal transmission and robustness. However, previously reported light-stimulated synaptic devices generally require special photoelectric properties from the semiconductors and sophisticated devices architectures. In this work, a simple and effective strategy for fabricating light-stimulated synaptic transistors is provided by utilizing interface charge trapping effect of organic field-effect transistors (OFETs). Significantly, our devices exhibited highly synapse-like behaviors, such as excitatory postsynaptic current (EPSC), pair-pulses facilitation (PPF), and presented memory and learning ability. The EPSC decay, PPF curves and forgetting behavior can be well expressed by mathematical equations for synaptic devices, indicating that interfacial charge trapping effect of OFETs can be utilized as a reliable strategy to realize organic light-stimulated synapses. Therefore, this work provides a simple and effective strategy for fabricating lightstimulated synaptic transistors with both memory and learning ability, which enlightens a new direction for developing neuromorphic devices.

INTRODUCTION Traditional digital computers based on von Neumann architecture cannot efficiently handle unstructured information due to the physical separation of memory modules and processor parts, which is called “von Neumann bottleneck”.1, 2 In contrast, the human brain is a high parallel, energy-efficient, fault-tolerance and reconfigurable neural network system, and thus easy to deal with these unstructured and complexed problems.3-5 Neurons, which are connected by synapses, serve as the basic units of human brain cognition. The transmission of action potentials between neurons, which is the basis for human information flow, data processing and memory, are all achieved through synapses.6 Moreover, synaptic plasticity fundamentally supports a variety of complex perceptual and cognitive intelligence. Therefore, implementation of synaptic functions with electronic devices is an essential step for the future development of brain-like computers.1, 5, 7-14 In the past few years, various types of synaptic devices stimulated by electrical signals have been reported, including memristors,15-18 phase-change memory,19 atomicswitch memory5 and synaptic transistors10, 13, 20-29. In addition to the achievement of simple synapse-like behaviors in a single synaptic device, arrays or circuits of the devices can further perform image memory, direction recognition, and neural network algorithms etc.20, 22, 26, 30 However, the operating speed of these electrical stimulated de-

vices can be limited due to the bandwidth-connectiondensity trade-off.31 Compared with conventional electrical stimulus, light or photons can offer some advantages such as high bandwidth, ultrafast signal transmission and robustness.32-35 Previous researches have been devoted to the development of light stimulated synaptic devices.33, 3638 For example, Qin et al. have demonstrated photonic synapse-like devices based on graphene hybrid phototransistor.36 Kim et al. have proposed photonic neuromorphic devices using photodynamic amorphous oxide semiconductors,37 and Agnus et al. have demonstrated an optical gated carbon nanotube transistor in which the channel resistance was modulated by light pulse signals.33 These reported light-stimulated synaptic devices exhibited excellent synapses-like behaviors, but they generally require specific photoelectric properties for the semiconductors and sophisticated devices architectures. Herein this work, an organic light-stimulated synaptic transistor utilizing interfacial charge trapping effect of organic field-effect transistors (OFETs) is demonstrated. Traditionally interfacial charge trapping effect was regarded as pitfall for OFETs, however in this work, interfacial charge trapping effect was utilized to induce synapselike behaviors for OFETs. Polyacrylonitrile (PAN) film is used as the OFET dielectric, which allows the polar groups of PAN to interact with the organic semiconductor (OSC) and hence induce the enhanced charge trapping effect between PAN and OSC interface.39-41 Previously, we

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Figure 1. (a) Schematic diagram of the bottom-gate top-contact C8-BTBT OFETs. (b) A cross-section SEM image of the C8-BTBT OFETs. (c) UV–vis absorption spectra of the PAN film, the pure C8-BTBT film and the C8-BTBT/PAN layered composite film deposited on quartz substrates. The inset shows the enlarged absorption spectrum in the wavelength range of 345-375 nm. Transfer characteristics curves of the C8-BTBT OFETs with different (d) light on and (e) light off time. (f) Normalized mobility and threshold voltage changes (△Vth) as a function of time under different UV light conditions, respectively. The mobilities were normalized to the mobility measured in the initial dark state. The threshold voltage changes were defined as △Vth = Vth- Vth initial dark state. have systematically investigated the polymer dielectric interfacial effect in organic transistors and mathematically explained how the polymer polar groups and the OSCs side chain affect the photosensory performances.39 However, the systematic investigation of synapse-like behaviors based on this effect is missing. In this work, we have systematically investigated the synapse-like behaviors of light-stimulated synaptic transistors based on interfacial charge trapping effect. Typical synaptic functions, such as excitatory postsynaptic current (EPSC) and pair-pulse facilitation (PPF), were successfully mimicked by our devices. Memory and learning behavior were also realized by tuning the light stimulation parameters, including light pulse width, intensity and the numbers of light pulses. The EPSC decay, PPF curves and forgetting behavior can be well expressed with mathematical equations. In addition, dynamic learning and forgetting processes were demonstrated through a T-shape synaptic transistors array. Therefore, our results provide a new, simple, effective and widely applicable strategy to fabricate organic lightstimulated synaptic devices. RESULTS AND DISCUSSION Figure 1a shows the schematic of the bottom-gate topcontact 2,7-dioctyl [1] benzothieno[3,2-b] [1] benzothiophene (C8-BTBT) OFETs. Detailed devices fabrication process was

described in the experimental section. PAN film was used as the charge trapping material which allows the polar groups to interact with the OSC, and hence induce charge trapping effect between or near the PAN/OSC interface. C8-BTBT was selected as the channel material due to its superb semiconductor performances and excellent solubility which provided the possibility of fabricating light-stimulated synaptic devices by large area solution process. Moreover, by blending C8BTBT with suitable polymer materials, such as polylactic acid (PLA), our devices can possibly be fabricated by printing technology, which is a promising technology for low-cost and rapidly fabricating organic devices with sophisticated patterns. In this work, thermal evaporated C8-BTBT was used as channel material as a demonstration. The cross-section image of C8-BTBT OFETs was investigated by scanning electron microscope (SEM) (Figure 1b), and the thicknesses of PAN film and silicon dioxide (SiO2) extracted from SEM image were estimated to be about 100 nm and 300 nm, respectively. The calculated capacitance of the hybrid dielectric film -2 (PAN/ SiO2) is about 8 nF cm . The surface morphology of C8-BTBT on the PAN film was investigated by atomic force microscopy (AFM) (Figure S1). The UV–vis absorption spectra of PAN film, pure C8-BTBT and C8-BTBT/PAN layered composite film are shown in Figure 1c. The PAN film did not exhibit obvious absorption peaks in the wavelength range of 300 to 800 nm. In contrast, intensive absorption peaks were observed for the pure C8-BTBT and C8-BTBT/PAN layered


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Figure 2. (a) Schematic image demonstrating the neural signal transmission of biological synapses in neuron and the simplified devices structure of our light-stimulated organic synaptic transistors. (b) EPSC trigged by a UV light spike (360 nm, 0.90 2 mW/cm , 200 ms) with a constant Vd of -1 V and Vg of 2 V. (c) EPSC decay behavior fitted by the stretched exponential function 2 (SEF). (d) Light-spike-time-dependent EPSC, the amplitude of the light spike is 0.90 mW/cm . composite film, which can be attributed to the л-conjugate molecular structure of C8-BTBT. In compared with pure C8BTBT film, the maximum absorption peak value of C8BTBT/PAN layered composite film showed a slight blue shift, which could be attributed to the interaction between the лconjugate molecules of C8-BTBT and the strong electronwithdrawing groups of PAN. As the maximum absorption peak value of C8-BTBT/PAN layered composite film is around 360 nm, the C8-BTBT channel layer can generate many electron-hole pairs under 360 nm UV light illumination. Typical transistor output characteristics of C8-BTBT OFETs measured in the dark state is shown in Figure S2, and decent OFET performance were observed. After a short time 2 of UV light illumination (360 nm, 0.90 mW/cm ), a positive shift of the transfer curve was observed (Figure 1d). In addition, the positive shift of the transfer curve increased when the illumination time was prolonged. When the illumination exceeded a certain time, the positive offset tended to be saturated. The positive shift of the transfer curve could be attributed to the filling of the charge trap states at the C8BTBT/PAN interface by the light-introduced charges. As the illumination time increases, the trap states were gradually filled by the light-introduced charges. When the illumination is off, the light-introduced holes will be gradually re-trapped, resulting in a negative shift of the transfer curve (Figure 1e). When UV light was turned off for 150 s, the transfer curve still showed a certain positive displacement as compared with the initial dark state. Figure 1f shows the normalized hole mobility and threshold voltage change (△Vth) as the

function of time under UV light illumination, respectively. No obvious hole mobility change was observed, but the △Vth changed drastically. The magnitude of the △Vth from the light off state to the light on state is larger than the △Vth from the light on state to the light off state. As expected, the normalized drain current showed similar trend of change with △Vth as shown in Figure S3. Hence, the positive shift of transfer curves could be attributed to the UV light introduced changes in mobile charge densities and the threshold voltage. Figure 2a illustrates the schematic of light-stimulated C8BTBT synaptic transistors. Analogy to biological synapses, the light spike is regarded as the presynaptic input while the drain current is regarded as the postsynaptic current, and the change in conductivity can be seen as a synaptic weight change. The synaptic weight of the C8-BTBT synaptic transistors can be easily modulated through light-introduced and PAN assisted holes de-trapping and trapping processes at the OSC/PNA interface. This behavior is very similar to that of biological synapses, in which the synaptic weight can be 6, 42 modulated through neurotransmitters. Figure 2b shows the typical EPSC of the C8-BTBT synaptic transistors trigged 2 by a UV light spike (360 nm, 0.90 mW/cm , 200 ms) with a constant drain voltage (Vd) of -1 V and gate voltage (Vg) of 2 V. When a UV light spike was applied, EPSC with a peak value of 2.1 nA was achieved at the end of the spike and it gradually declined toward the initial current. Electron-hole pairs in the C8-BTBT channel layer were generated under UV light illumination, and the charge trap states at the C8-



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2

Figure 3. (a) The schematic image of the PPF measurement. (b) EPSCs trigged by a pair of light pulses (0.90 mW/cm , 200 ms) with a constant Vd of -1 V. A1 and A2 are the EPSC values at the end of the first and the second light pulse, respectively. (c) PPF 2 index as the function of light pulse interval (△T) with a fixed light pulse intensity of 0.90 mW/cm and a light pulse width of 200 ms. Error bars in (c) represent standard errors from 3 times independent tests of a synaptic transistor. BTBT/PAN interface were partly filled by the light introduced holes. When the illumination is off, the lightintroduced holes will be gradually re-trapped which lead to typical EPSC decay behavior. Such holes trapping and detrapping related EPSC behavior could be explained by a stretched exponential model, and the EPSC decay could be 15, 43 fitted with the stretched exponential function (SEF) shown below:

(1)

Where τ, τ0 are the retention time and the light spike finished time, respectively. I∞ is the final postsynaptic current and the β is a stretch index between 0 and 1. Figure 2c shows a fitting curve of the EPSC decay trigged by a UV light spike of 2 0.90 mW/cm (360 nm, 200 ms), and the corresponding value of τ is ~685 ms. In biological synapses, synaptic plasticity can be modulated by the spike rate or the spike duration 44 time between stimuli. To further assess the temporal response of the light-stimulated organic synaptic transistors, light-spike-time-dependent EPSCs were investigated with a series of UV light spike duration ranging from 100 to 2000 ms (Figure 2d). When the UV light spike durations were below 500 ms, the peak values of EPSC increased almost linearly, but when the UV light spike durations were above 500 ms, the peak values tended to be saturated. This temporal response behavior in our synaptic devices can also be well explained by the light-introduced and PAN assisted holes detrapping and trapping processes at the OSC/PAN interface. In the beginning, more and more charge trapping states will be filled by the light-introduced charges due to the increas-

ing of light spike duration time and thus lead to the increasing of the EPSC values. However, the number of the charge trapping states at the OSC/PAN interface is limited. Therefore, the EPSC values will tend to be saturated with a longer light spike duration time. Light-spike-intensity-dependent EPSCs were also investigated as show in Figure S4. When the 2 spike intensities were less than 0.90 mW/cm , the peak values of EPSC increased almost linearly, but when the light 2 spike intensities were larger than 0.90 mW/cm , the peak values tended to be saturated. This result indicates that the light-spike-intensity can be utilized to modulate the synaptic weight and plasticity of our synaptic transistors. PPF, as a form of typical short-term plasticity, is a phenomenon in neurobiology in which synaptic responses were enhanced after two consecutive synaptic stimulations, and PPF is widely considered to play important roles in decoding 6, 45 temporal information in visual and auditory signal. The PPF behavior has been successfully mimicked with our lightstimulated organic synaptic transistors. A schematic of the EPSC trigged by a pair of light spike with an inter-spike interval (△tpre) is demonstrated in Figure 3a. Two consecutive 2 UV light spikes (360 nm, 0.90 mW/cm , 200 ms) were applied with an △tpre ranging from 100 to 3000 ms. As shown in Figure 3b, EPSC was trigged by two successive light spikes with an △tpre of 500 ms. The EPSC value triggered by the second light spike is larger than that triggered by the first one, which is very similar to the PPF behavior in the biological synapses. The PPF index can be described with the fol45, 46 lowing equation :


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Figure 4. (a) Normalized channel conductance changes as a function of time with different number of light pulses. (b) △G0 and τ as a function of number of light pulse, respectively. (c) Normalized channel conductance change as the function of time with different light pulse width. (d) △G0 and τ as a function of light pulse width, respectively. (e) Normalized channel conductance change as the function of time with different light pulse intensity. (f) △G0 and τ as a function of light pulse intensity, respectively. The values of τ yielded from Eq. (3). PPF 100% ∙ (2)

where A1 and A2 are the values of the first and second EPSC, respectively. PPF decreases gradually when the △tpre increases as shown in Figure 3c. The maximum PPF of ~ 76% was obtained at a fixed △tpre of 100 ms. As mentioned above, the charge trap states at the OSC/PAN interface will be partly filled by the light induced charges. If the second light spike is applied very close to the first one, the first light spike induced charges will not have enough time to be re-trapped completely before the arrival of the second light spike.

Therefore, at the end of the second spike, the number of filled charge trapping states will be larger than that at the end of the first spike. As a result, EPSC values of the synaptic transistor were enhanced after two consecutive synaptic stimulations. In biological synapses, PPF decay behavior consist of both rapid phase and slow phase, which can be 21, 45 demonstrated with the following equation : PPF (3)

!

where △t is the inter-spike interval (△tpre), c1 and c2 represent the initial rapid and slow phase facilitation magnitudes, re-



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Figure 5. (a) Schematic diagram of a light-stimulated C8-BTBT synaptic transistors array. (b) Fabrication process of the T-shape transistors array. (c) Dynamic learning and forgetting process of the T-shape synaptic transistors array: (i) In the learning process, different times of UV light pulses represents for different times of learning. (ii) The forgetting process started at the end of 20 times of learning. spectively. τ1 is the characteristic relaxation time of the slow phase, while τ2 is the characteristic relaxation time of the rapid phase. As shown in Figure 3c, the experimental PPF decay behavior of the light-stimulated C8-BTBT synaptic transistors is fitting well with Eq. (3). In our case, c1 = 268.09 %, c2 = 36.8 %, τ1 = 47.12 s, τ2= 481.29 s. Therefore, the typical PPF behaviors were successfully simulated by using our synaptic transistors. In psychology, memory behavior can be categorized into two forms according to the retention time: short-term 5, 15 memory (STM) and long-term memory (LTM). Through a 47 rehearsal process, the memory level can be increased. The light-stimulated C8-BTBT synaptic transistors could also be used to achieve such psychological functions by using the light spikes as the external stimulus and the channel conductance change as the memory level. To investigate the memory behavior, a series of light pulses (360 nm, 0.90 2 mW/cm , 200 ms) were applied on the channel of our synap-

tic transistors. Figure 4a shows the decay behavior of the normalized channel conductance change after 10, 30, 60, 120 light spikes, respectively. It is clear that the change of the normalized channel conductance increased as the number of UV light spikes increased, indicating that the memory level increased through the light-stimulating rehearsal process. As time increases, the change of the normalized channel conductance showed a very fast decay at the beginning and then decayed slowly, which is very similar to the memory behavior 5, 15 To further investigate the memory of the human brain. behavior of our synaptic transistors, a well-known forgetting curve of Ebbinghaus is applied here. The Ebbinghaus forget48 ting curve can be expressed by the following equation :

'

p exp % ( (4)

&

where p stands for the probability of recall, t is the time, τ3 is the feature relaxation time, and γ is an index between 0 and 1.


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In our case, the channel conductance change was regarded as the memory level. Hence, the forgetting equation for our synaptic transistor could be express by:

'

)*/ ) % ( &

(5)

where △G(t) = G(t) − Ginitial and △G0 = G0 − Ginitial. G(t) and G0 is the channel conductance at the time of t and the channel conductance at the end of a series of light spikes, respectively. Ginitial is the initial channel conductance before light stimuli. As shown in Figure S5, the experimental forgetting curve is well fitted with Eq. (5) which indicates that our synaptic devices have very similar memory behavior with the human brain. Figure 4b shows the △G0 and the τ3 as a function of UV light spike numbers, respectively, in which τ3 was obtained from the Eq. (5). The increases of both △G0 and τ3 as increase of the UV light spike numbers are strong evidences for STM to LTM transition. In order to further investigate the LTM behavior of our light-stimulated synaptic transistors, 1500 UV light spikes were applied to simulate the rehearsal learning process in brain, as shown in Figure S6. After 1500 light spikes, the change of the normalized channel conductance showed a very fast decay at the beginning and then decayed very slowly. The change of the normalized channel conductance kept above 0.02 for more than 10000 seconds (2.8 hours). In biological synapses, LTM can last for hours or 6 longer. Compared with these biological synapses, our devices exhibited a decent LTM behavior. Besides the light spike numbers, the light spike width can also be used to modulate the memory and forgetting behaviors of our synaptic transistors. Figure 4c shows the normalized channel conductance change as a function of time with different light pulse width. The normalized channel conductance change increased with the increasing of light pulse width. Figure 4d shows the △G0 and the τ3 as a function light pulse width, respectively. Since the △G0 and the τ3 increased as the increasing of light pulse width, we proposed that the light-spike-intensity can be utilized to modulate the memory and forgetting behavior of our synaptic transistors. In addition to the light spike numbers and the light spike width, the light spike intensity also has effects on the memory and forgetting behavior of the synaptic transistors, as presented in Figure 4e-f. The STM to LTM transition behavior can also be successfully realized through increasing the light spike intensity. Learning and forgetting are among the most important 5, 15, 48 and basic behaviors of human brain. Dynamic learning and forgetting processes of our devices were demonstrated by using a T-shape light-stimulated organic synaptic transistors array. Figure 5a shows the schematic of a 10 × 10 lightstimulated C8-BTBT synaptic transistors array. The 10 × 10 transistors array was fabricated with a simple spin-coating process and could be readily peeled off from the silicon substrate. We further cut the pre-fabricated 10 × 10 transistors array into a T-shape device, as shown in Figure 5b. The dynamic learning and forgetting abilities of our lightstimulated C8-BTBT synaptic transistors were demonstrated in Figure 5c. The letter of “T” is gradually stored in the devices array with the increase of the light spike numbers. Different times of UV light stimulus can represent different times of learning. Therefore, a dynamic learning process was achieved. After 20 times of learning, a dynamic forgetting process was further demonstrated. The forgetting process is faster at the beginning, followed by a slower process. 30 s

later, the letter of “T” was almost completely forgot. The learning and forgetting behavior of our synaptic transistors were similar to that of human brain, demonstrating that our devices have potential application in neuromorphic devices. In order to investigate the cyclic tolerance of the lightstimulated synaptic transistor based on interfacial charge trapping effect, 1500 consecutive UV light spikes with an interval time of 1 s were applied (Figure S7). Repeated light spike stimulations will strengthen the postsynaptic current because the light-stimulated synaptic devices exhibit excellent synapse-like behaviors. Therefore, it is hard to directly study the cyclic tolerance of the light-stimulated synaptic device. As an alternative, we choose to observe the device response while the postsynaptic current tends to be saturated. After 1500 consecutive UV light spikes, the postsynaptic current of light-stimulated synaptic transistors tends to be saturated and then the light-stimulated synaptic devices still exhibit excellent responsiveness and reproducibility under UV light stimulation, indicating that our devices have decent cycling stability. Since the light-stimulated synaptic transistors were operating under 360 UV light illumination, it is vital to study the stability of the light-stimulated transistor for long UV exposure time. Therefore, we tested the transfer curves of our devices before and after 30 min 360 nm UV light illumination in order to achieve comparable data. The transfer curve showed a slight difference after 30 min UV light illumination compared to the transfer curve measured before UV illumination (Figure S8). The slight difference observed in the transfer curves measured before and after UV illumination may be due to the little damage of the polymer or organic semiconductors under long time UV irradiation. Although in this work, PAN films were selected as dielectric layers to induce synapse-like behaviors in OFETs, other types of polar dielectric materials may also be suitable to be used as dielectrics in the fabrication of light-stimulated synaptic transistors. It should be noticed that the interfacial charge trapping effect will be different when using different types of polar dielectrics. Therefore, when using different polar polymers as the dielectric layer, the synaptic characteristics of the light-stimulating synaptic transistors may be different. In order to verify this, we have fabricated two lightstimulated synaptic transistors with PLA and PAN as the dielectric layer, respectively. The memory behaviors of these two light-stimulated synaptic transistors were provided in Figure S9. Both of the experimental memory behaviors of the PLA and the PAN based synaptic devices can be fitted well with equation (5). The feature relaxation times of the PLAbased and the PAN-based synaptic transistors extracted from equation (5) are 1.29 s and 118.99 s, respectively, indicating that the PAN-based synaptic transistors exhibited longer memory time than that of the PLA-based synaptic transistors. The different memory abilities of the two light-stimulated synaptic transistors can be attributed to different interfacial effects. In addition to the dielectric layer, the choice of organic semiconductors may also have influence on the inter39 facial charge trapping effect. Therefore, it is very essential to select different polarity dielectric materials and semiconductors according to the requirements of the application. Solvent residues in the polymer dielectric layer may also have influence on the synapse-like behaviors of lightstimulated synaptic transistors, because solvent residues may



become defects for devices. In order to study the influence of solvent residues, we have fabricated two PAN films with different annealing times (120 for 10 s and 60 min, respectively) and then used them to fabricated light-stimulated transistors. The PAN film annealed for 10 s contained more solvent than that of the PAN film annealed for 60 min. The learning and memory abilities of these two devices are presented in Figure S6 and Figure S10. After 1500 times of learning, the light-stimulated synaptic transistor fabricated with the 10 s annealed PAN dielectric (device 1) exhibited longer memory time than that of the synaptic transistor (devices 2) fabricated with the 60 min annealed PAN dielectric. The feature relaxation times of device 1 and device 2 extracted from equation (5) are 831.94 s and 1176.50 s, respectively. The difference in memory ability between device 1 and device 2 may be caused by the different amounts of solvent remaining in the dielectric layer. CONCLUSION In conclusion, light-stimulated synaptic transistors were realized by utilizing a simple and effective strategy utilizing the interfacial charge trapping effect of OFETs. The strategy is based on the inserting of charge trapping layer at the OSC/dielectric interface for the charge trapping process, and the light stimulated charge detrapping process. Here PAN was used as the dielectric material as a demonstration. The strong polar groups of PAN dielectric film can induce strong charge trapping effect at the OSC/PAN interface. The trapping and detrapping processes of the photogenerated charges at the interface provided the OFETs with synapse-like behaviors, such as EPSC and PPF. More importantly, memory and learning behavior similar to human brain have also been achieved in our devices by tuning the light stimulation parameters, including light pulse width and intensity and the numbers of light pulses. All experimental curves, including EPSC decay, PPF and forgetting behaviors can be well described with mathematical equations, indicating that interfacial charge trapping effect of OFET can be regarded as a reliable tool to induce synapse-like behaviors in OFETs. Therefore, by utilizing the interfacial charge trapping effect, this work provides a simple and widely applicable strategy for fabricating synaptic transistors, and is expected to give a new thought to design future neuromorphic devices.

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solution (140 mg ml , DMF) was spin-coated on the top of the silicon substrate at the speed of 2000 rpm for 20 s, and then annealed at 80 for 60 min. After that, the C8-BTBT was thermally evaporated onto the PAN film at a rate of 0.2~0.3 Å/s. 80 nm Au source-drain electrodes were then thermally deposited onto C8-BTBT film through a shadow mask. The channel length (L) and width (W) were 30 μm and 1 mm, respectively. The fabricated C8-BTBT synaptic transistors arrays can be easily peeled off from the silicon substrate. Devices characterization: The surface morphology of C8-BTBT on PAN film was investigated by atom force microscope (AFM, SEIKO SPA-300HV). The thickness of PAN film was obtained from scanning electron microscope (SEM, Nova NanoSEM 450). The transistors characteristics were measured at room temperature using a Keithley 4200-SCS Semiconductor Parameter Instrument. For the characterization of the light-stimulated C8-BTBT synaptic transistors, a LED (white light, Thorlabs MCWHL5-C4) was used as a light source, and the light intensities were calibrated with an optical power meter (Thorlabs PM100D). The synaptic functions were also tested with the Keithley 4200-SCS Semiconductor Parameter Instrument.

ASSOCIATED CONTENT SUPPORTING INFORMATION The Supporting Information is available free of charge on the ACS Publications website. Experimental details for the fabrication of light-stimulated synaptic transistors with spin-coated PAN and PLA dielectrics. AFM image of the C8-BTBT membrane deposited on the PAN film. Typical output characteristic curves of the C8BTBT OFETs. Normalized drain current and threshold voltage changes in both light on and off states as a function of time, respectively. Light-spike-intensity-dependent EPSCs. Normalized channel conductance changes as a function of time. L0ng-term memory behavior. Cyclic tolerance test. Transfer curves of the light-stimulated synaptic transistor before and after 30 min UV light illumination. EPSC responses and memory behaviors of PLA- and PAN-based lightstimulated synaptic transistors exposed to UV light spikes.

AUTHOR INFORMATION

EXPERIMENTAL SECTION

Corresponding Author

Materials and devices fabrication: Polyacrylonitrile (PAN) with molecular weight of 150000 was purchased from Alfa Aesar Co., Ltd., and 2,7-dioctyl [1] benzothieno[3,2-b] [1] benzothiophene (C8-BTBT) was purchased from Suna Tech Inc. OFETs were fabricated using silicon wafers as substrate. PAN films were prepared on the top of silicon wafers by dip −1 coating PAN solution (10 mg ml , DMF) at a speed of 20 μm -1 s at 60 . The C8-BTBT was then thermally evaporated onto the PAN film at a rate of 0.2~0.3 Å/s. After that, 80 nm Au source-drain electrodes were thermally deposited onto the C8-BTBT film through a shadow mask. The channel length (L) and width (W) were 0.2 mm and 6.0 mm, respectively. In order to speed up the manufacturing process of the lightstimulated synaptic transistors, polymer dielectrics were also prepared by spin-coating (see Supplementary Information). The synaptic transistors arrays were also fabricated on a silicon wafer substrate. 80 nm Au gate electrodes were thermally evaporated on the on the top of a silicon substrate. PAN

* (J. H.). E-mail: [email protected].

Author Contributions All authors have given approval to the final version of the manuscript.

ACKNOWLEDGMENT This work was supported by the Science & Technology Foundation of Shanghai (17JC1404600), the National Key Research and Development Program of China (2017YFA0103904), the National Natural Science Foundation of China (No. 51741302), and the Fundamental Research Funds for the Central Universities.

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