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A bioinspired neuromuscular system enabled by flexible electro-optical N2200 nanowire synaptic transistor

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Published 24 June 2024 © 2024 The Author(s). Published by IOP Publishing Ltd
, , Focus Issue on Flexible and Stretchable Electronics for Neuromorphic Computing Citation Jiahe Hu et al 2024 Neuromorph. Comput. Eng. 4 024016 DOI 10.1088/2634-4386/ad54ea

2634-4386/4/2/024016

Abstract

Mimicking the functional traits of the muscle system evolves the development of the neuromorphic prosthetic limbs. Herein, a bioinspired neuromuscular system was constructed by connecting an information processor that uses a flexible electro-optical synaptic transistor (FNST) to an effector that uses artificial muscle fibers. In this system, the response of artificial muscle fibers, which imitate the movement of biological muscle fibers, is manipulated by neuromorphic synaptic devices. The FNST is regulated by light pulses and electrical spikes to emulate biological synaptic functions, and thereby applied in secure communication. The feasibility of n-type organic nanowires acting as the channels for neuromorphic devices was demonstrated. Attributing to the flexibility of the n-type organic semiconductor N2200 nanowires, the current of the FNST retains >85% of its initial value after the 5000 bending cycles to radius = 1 cm. The tolerance of bending of the FNST implies its potential applications in wearable electronics. This work offers an approach to potentially advancing electronic skin, neuro-controlled robots, and neuromorphic prosthetic limbs.

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1. Introduction

The human nervous system orchestrates a series of reactions through reflex arcs when responding to environmental stimuli such as light, pressure, temperature, and humidity [14]. The fundamental elements of a reflex arc include receptors, afferent nerves, neural centers, efferent nerves, and effectors [57]. Receptors detect sensory information. Afferent nerves convey the signals to the central nervous system, which processes them and issues commands [8]. Efferent nerves transmit these commands to muscles or other effectors to initiate a response [9]. In an artificial reflex arc, sensors mimic receptors to perceive external stimuli and relay the information through artificial afferent nerves to a central processing unit [10, 11]. Artificial synapses are regarded as the central processing units for transferring and integrating information [12]. The information processed by artificial synapses could be relayed through efferent nerves to drive the actuators that execute the response [13]. In biological systems, skeletal muscles play a crucial role in driving the movements of human limbs [14, 15]. Recently, some artificial neuromuscular systems focusing on mimicking the movement of skeletal muscles have been reported [1618]. The development of bioinspired neuromuscular systems has potential implications for neuro-controlled robots and neuromorphic prosthetic limbs [19, 20].

Artificial synapses composed of organic materials are applicable to neuromorphic computing and artificial neural networks for effective information transfer and storage [2123]. The unique advantages of these organic artificial synapses include ultra-low energy consumption, high mechanical flexibility, and compatibility with low-cost mass production by methods like inkjet printing or spin-coating [2, 10, 2426]. Most organic artificial synapses use p-type semiconductors as channel materials [2730], while it is relatively rare to adopt n-type semiconductors as the channel of artificial synapses [3133]. To fabricate bipolar artificial synapses to emulate complex synaptic functions, both p-type and n-type organic semiconductors with flexibility are required. Recently, electro-hydrodynamic nanowire printing (e-NWP) is used to fabricate nanowire synaptic transistors [3436]. The nanowires printed by e-NWP have the advantages of being long, continuous, and well-aligned. However, there are few reports on utilizing the additive manufacturing technology to prepare n-type organic flexible synaptic transistors.

In this work, a bioinspired neuromuscular system emulating the skeletal muscle system was constructed using a flexible electro-optical synaptic transistor (FNST) as an information processor and artificial muscle fibers as the effector. In this system, the movement of artificial muscle fibers is controlled by the FNST. Applying electrical spikes with different frequencies to the FNST, the bending degree of the artificial muscle fibers varies correspondingly. The FNST uses N-type poly{[N,N'-bis(2-octydodecyl)naphthalene-1,4,5,8-bis(dicarboximide)-2,6-diyl]-alt-5,5'-(2,2' bithiophene)} (N2200) nanowires (NWs) as channel and can be regulated both by light pulses and by electrical spikes to emulate synaptic plasticity features, which can be applied in secure communication. The FNST has excellent bend resistance, retaining over 85% of its electrical performance after 5000 bending cycles, which makes it suitable for applications in wearable electronics. The present study holds significance for areas like neuroprosthetics and artificial intelligence.

2. Experiments

The experiment section describes the preparation process of the bioinspired neuromuscular system (figure S1) and the characterization of materials and devices. The bioinspired neuromuscular system mainly consists of an N2200 nanowire synaptic transistor and artificial muscle fibers, which are prepared as follows.

2.1. Fabrication of the flexible electro-optical N2200 nanowire synaptic transistor

N-type poly{[N,N'-bis(2-octydodecyl)naphthalene-1,4,5,8-bis(dicarboximide)-2,6-diyl]-alt-5,5'-(2,2'-bithiophene)} (N2200, Mw > 50 000; Derthon) and poly(ethylene oxide) (PEO, Mw ∼ 400 000; Sigma-Aldrich) were dissolved in chlorobenzene at a 7:3 weight ratio, then stirred for 12 h at 60 °C to create a uniform printing ink. N2200 nanowire synaptic transistors were prepared using e-NWP. The process is controlled by an intelligent digital platform, which enables fast and highly reproducible printing of NW arrays. For the printing process, a polyimide (PI) substrate with deposited gold source and drain electrodes (70 nm) was placed on the printing platform, and a syringe was filled with the prepared ink. The syringe had a metal nozzle that had 80 μm inner diameter and was mounted with its tip 3.5 mm above the substrate. A voltage of ∼2 kV was applied to the nozzle, and the blended ink was extruded at 20 nl min−1 with the nozzle moving at 1 m s−1. The N2200/PEO ink formed a fine stream under the electric field. During the printing process, the solvent fully evaporated, so a continuous solid NW forms on the PI substrate.

The FNST can be stimulated by light pulses. To realize electrical spikes modulation, an ion gel composed of polymer (poly(vinylidene fluoride-co-hexafluoropropylene)) (PVDF-HFP) and ionic liquid (1-ethyl-3-methylimiazolium bis-(trifluoromethyl sulfonyl) imide) ([EMIM-TFSI]) was transferred onto the surface of N2200 NWs. The ion gel was prepared by mixing PVDF-HFP, [EMIM-TFSI], and acetone in a weight ratio of 1:4:7 at room temperature, then drying the mixture in a vacuum oven at 70 °C for 0.5 h. A metal probe was used as a presynaptic input terminal.

2.2. Fabrication of the artificial muscles

To form the electrolyte layer, chitosan (∼0.6 g) was added into 2 wt% acetic acid aqueous solution (20 ml). The mixture was stirred for 30 min at 70 °C, then sonicated for 15 min to remove remnant air bubbles. Finally, the mixture was placed in a vacuum oven for 4 h at 75 °C to remove the solvent.

To form the electrode layer, chitosan (∼0.2 g) was added to the acetic acid solution and stirred for 30 min at 70 °C. Then multiwalled carbon nanotubes (10.0%; Boyu Gaoke) and reduced graphene oxide (0.5 wt%; Boyu Gaoke) were added to the solution and stirred at 70 °C for 10 min. Polyaniline (∼0.08 g) was then added and the mixture was stirred for 40 min, then sonicated for 30 min. Finally, the mixture was poured into a mold then placed in a vacuum oven for 4 h at 75 °C.

To fabricate artificial muscles, the electrolyte layer was sandwiched between two electrode layers, which were then cut to 20 mm × 5 mm and assembled using hot-pressing technology.

2.3. Construction of the bioinspired neuromuscular system

To construct the bioinspired neuromuscular system, the synaptic device was integrated with the amplifier circuit and artificial muscle fibers. To control the efferent muscular actions, an operational amplifier was used to transform the output from the synaptic device. By connecting the drain electrode of the synaptic device to the conversion amplification module, the postsynaptic current is converted to an output voltage, which can drive the artificial muscle fibers.

2.4. Characterization of materials and devices

The surface morphology of N2200 nanowires was investigated using a scanning electron microscope (SEM) (TESCAN MIRA LMS) and an atomic force microscope (AFM) (Bruker). X-ray diffraction (XRD) patterns were obtained using a Rigaku D diffractometer. X-ray photoelectron spectra (XPS) were obtained using a Thermofisher Nexsa. Absorption spectra were measured using a Hitachi U4150 spectrometer. All electrical characterizations were performed using a probe station in a nitrogen-filled glovebox, and the data were gathered using a Keithley 4200A semiconductor parameter analyzer. A continuous-wave semiconductor laser with a wavelength of 405 nm was used as the light source.

3. Results

3.1. General concept and materials characterization

Motor neurons connect with skeletal muscle fibers via chemical synapses within living organisms [37]. Upon receiving excitatory signals, the presynaptic area of a motor neuron releases the neurotransmitter acetylcholine (ACh) [38], which diffuses across the synaptic cleft, then interacts with ACh receptors in the postsynaptic membrane. This interaction causes ion channels to open and thereby generate a postsynaptic potential [39]. This chain of events ultimately leads to the contraction of muscle fibers.

To construct a bioinspired neuromuscular system, the FNST was used to emulate the functions of biological synapses. Polymer-ion-gel fibers were fabricated to serve as artificial muscles, simulating biological muscles. Electrical spikes with different frequencies can modulate the postsynaptic currents generated by the FNST. After amplification through a circuit, the postsynaptic currents drive the artificial muscles to contract, and thus mimic the excitatory behavior of motor neurons (figure 1(a)).

Figure 1. Refer to the following caption and surrounding text.

Figure 1. (a) Schematic of biological and bioinspired neuromuscular systems. SEM images of (b) N2200 nanowire array and (c) a single nanowire. (d) AFM image of an N2200 nanowire. (e) XRD pattern of N2200 nanowires. (f) XPS spectra of S 2p peaks. (g) Absorption spectra of N2200 nanowires.

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The electrodynamically-printed NWs were long and continuous. Parallel NWs were ∼60 μm apart (figure 1(b)), and each NW had a diameter of ∼650 nm (figure 1(c)). An AFM image of a single N2200 NW showed a height of ∼200 nm (figure 1(d)). The XRD pattern of N2200 nanowires showed a peak at 2θ = 3.92°, which represents the (100) orientation of N2200 (figure 1(e)) [40]. XPS spectra showed peaks at binding energies EB = 163.88 eV for S 2p3/2 and EB = 165.08 eV for S 2p1/2; these peaks confirm the existence of sulfur in N2200 NWs (figure 1(f)) [41]. The XPS spectra also confirmed the presence of oxygen and nitrogen (figure S2). Absorption spectra of the N2200 nanowires had a broad absorption peak between 500 and 800 nm (figure 1(g)).

3.2. N2200 nanowire synaptic transistor modulated by light pulses

In a human retina, when photoreceptor cells receive light stimulation of a specific intensity or wavelength, they undergo chemical and electrophysiological changes, which generate electrical signals (figure 2(a)) [42, 43]. They are passed through synapses to connected bipolar cells, which relay the signals through synapses to retinal ganglion cells [44]. N2200 as an n-type organic semiconductor exhibits visible light responsiveness (figure 1(g)). Additionally, its excellent flexibility makes it suitable for use in flexible electro-optical synaptic transistors to emulate the photoreceptor neurons in the human eye.

Figure 2. Refer to the following caption and surrounding text.

Figure 2. (a) Diagram of light-sensing pathway in a biological nervous system. (b) Schematic of the FNST modulated by light pulses. (c) Current characteristics of the FNST measured under illumination and dark conditions. (d) EPSC triggered by a single light pulse. (e) EPSC triggered by a pair of light pulses. (f) PPF index vs. time interval Δt between pairs of light pulses.

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The FNST can act as a light-sensitive synapse modulated by light pulses (figure 2(b)). The FNST shows a higher current under illumination than in darkness; this difference confirms the production of photo-generated carriers (figure 2(c)). Under drain voltage Vd = 1 V, the application of a light pulse (405 nm, 50 ms) induced generation of photo-carriers in the N2200 NWs, and Ids was considered as the excitatory postsynaptic current (EPSC). The photo-carriers gradually dissipate once the pulse stimulus ceases, and the EPSC returns to its initial state (figure 2(d)).

Paired-pulse facilitation (PPF) represents short-term synaptic plasticity [45, 46]. PPF was simulated by applying two consecutive light pulses under Vd = 1 V (figures 2(e) and S3). Experiments about synaptic plasticity were repeated more than three times, and corresponding statistics were shown in mean value and standard deviation. The height of the second EPSC peak (A2) was higher than that of the first EPSC peak (A1) (figure 2(e)), because the photo-induced carriers generated by the first light pulse had not entirely recombined by the time the second pulse arrived, so the carriers accumulated, and thereby increased the photocurrent. The increase was quantified as PPF index = A2/A1 × 100%. When two light pulses separated by intervals 50 ⩽ Δt ⩽ 450 ms were applied to the FNST, the PPF index gradually decreased as Δt increased (figures 2(f) and S4).

Spike-duration dependent plasticity (SDDP) refers to the correlation between EPSC and the duration of synaptic stimuli. To measure the SDDP, the FNST was stimulated using light pulses with durations 50 ⩽ D ⩽ 500 ms in increments of 50 ms, under Vd = 1 V. The EPSC increased as D increased (figure 3(a)). The SDDP index was defined as the ratio of EPSC triggered by the nth light pulse (An) and that triggered by the first light pulse (A1). As D increased, the SDDP Index increased continuously (figure 3(b)). Increase in D causes increase in the number of photo-generated carriers in the semiconductor, so the photocurrent increases.

Figure 3. Refer to the following caption and surrounding text.

Figure 3. (a) EPSC triggered by light pulses with different durations. (b) SDDP index vs. light pulse duration. (c) EPSC triggered by consecutive light pulses with different frequencies. (d) SRDP index vs. light pulses frequency. (e) EPSC triggered by light pulses with different numbers. (f) SNDP index vs. number of light pulses.

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Spike-rate dependent plasticity (SRDP) is a form of synaptic plasticity and is among the most important mechanisms for synaptic learning and memory in neural cognitive processes [47, 48]. In the context of this mechanism, high-frequency neuronal activities generally result in the reinforcement of synaptic weights. The mechanism facilitates self-organization and adaptability within neural networks, and thereby achieves high flexibility in information encoding. The FNST emulated SRDP. When consecutive light pulses with pulse frequencies 3.33 Hz ⩽ ƒ ⩽ 10 Hz were applied to the FNST under Vd = 1 V, its EPSC gradually increased as f increased (figure 3(c)). The SRDP index was defined as the ratio between the EPSC triggered by the 6th or 10th (A6 or A10) light pulse to the EPSC triggered by the first light pulse (A1). The SRDP index increased as f increased (figure 3(d)).

Spike-number dependent plasticity (SNDP) is a form of synaptic plasticity in which the EPSC increases when the number of stimuli increases. At a constant Vd = 1 V, the EPSC increased as the number N of light pulses was increased from 1 to 10 (figure 3(e)). This phenomenon occurs because increase in N causes increase in the number of photo-generated carriers in the semiconductor, with consequent increase in photocurrent. The SNDP index was defined as the ratio between the EPSC triggered by the light pulses with the pulse number of N (An) and the EPSC triggered by a single light pulse (A1). As N increased, the SNDP index increased (figure 3(f)).

3.3. N2200 nanowire synaptic transistor modulated by electrical spikes

The responses of the FNST can also be modulated by electrical spikes (figure 4(a)). Cations are initially distributed randomly in the ion gel. When an electrical spike (2 V, 50 ms) is applied under Vd = 0.4 V, they move to and accumulate at the interface between the ion gel and the N2200 nanowires to form an electric double layer. In this process, electrostatic coupling between cations and electrons leads to an accumulation of electrons in the n-type channel, and thereby increases the drain current or EPSC. Once the pulse stimulus ceases, the ions within the ion gel start to diffuse back to their original distribution. Consequently, the carriers cease accumulating, and the drain current returns to a steady state after a certain relaxation time (figure 4(b)).

Figure 4. Refer to the following caption and surrounding text.

Figure 4. (a) Diagram of the FNST modulated by electrical spikes. (b) EPSC triggered by a single electrical spike. (c) EPSC triggered by a pair of electrical spikes. (d) PPF index vs. time interval Δt between pairs of electrical spikes. (e) EPSC triggered by electrical spikes with different voltage amplitudes. (f) EPSC triggered by electrical spikes with different numbers. (g) EPSC triggered by electrical spikes with different durations. (h) Morse code generated by the FNST modulated by electrical spikes.

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PPF was simulated by applying two consecutive electrical spikes (2 V, 50 ms) under Vd = 0.4 V. Δt between the electrical spikes was less than the relaxation time of the cations, so the cations in the ion gel could not fully return to equilibrium before the second stimulus was applied. The residual cations in the interface summed with additional cations that were driven to the interface by the second spike, so the current increased; as a result, the EPSC triggered by the second electrical spike (B2) was higher than that triggered by the first electrical spike (B1) (figure 4(c)). The PPF index B2/B1 × 100% was gradually decreased as Δt increased from 100 to 1400 ms (figures 4(d) and S5).

Spike-voltage dependent plasticity (SVDP) was quantified under Vd = 0.4 V at gate voltages 1 ⩽ Vg ⩽ 5 (figures 4(e) and S6). EPSC gradually increased as Vg increased. Therefore, the synaptic plasticity of the FNST can be effectively modulated by the amplitude of gate voltage.

SNDP was mimicked by applying electrical spikes. Under Vd = 0.4 V, as the number N of electrical spikes (2 V, 50 ms) increased from 1 to 10, the accumulation of ions in the interface or channel was increased, so EPSC increased (figure 4(f)). SNDP index = Bn/B1 × 100%, where Bn and B1 are the EPSC triggered by electrical spikes with N = n and 1, respectively, increased monotonically due to the increase of EPSC with an increase in the number of spikes (figure S7).

SDDP was mimicked by applying electrical spikes with different D under Vd = 0.4 V. SDDP index was defined as Bn/B1 × 100%, where Bn and B1 are the EPSC triggered by the nth and the first electrical spikes, respectively. As D increased from 50 to 500 ms, both the EPSC and SDDP index increased monotonically (figures 4(g) and S8). This phenomenon occurs because increase in D causes increase in the number of cations that move from their equilibrium positions to the interface between ion gel and N2200, so the conductance of the N2200 channel increases.

The SDDP feature can be exploited to generate international Morse code by using electrical spikes to modulate the FNST. International Morse code consists of 'dot' (·) and 'dash' (-) [49, 50]. Morse code was encoded by adjusting the duration of electrical spikes. The threshold was set as 1.2 μA. EPSC triggered by electrical spikes with D = 50 ms were smaller than this threshold and correspond to '·'; whereas spikes with D = 150 ms were larger than the threshold and correspond to '-'. Signals 'NKU' were successfully generated by the FNST (figure 4(h)).

3.4. Responses of bioinspired neuromuscular system

Neuromorphic devices offer a more efficient emulation of brain-like mechanisms for information processing than von Neumann computational architectures do [51, 52]. Neuromorphic devices can perform fundamental neural tasks like spike propagation and synaptic plasticity, and can support intricate dynamic operations such as multi-layer accumulation processing [53]. A bioinspired neuromuscular system was constructed by integrating the FNST, an amplifier circuit, and artificial muscle fibers (figure 5(a)). As applying currents, the ions inside the artificial muscle fibers rapidly diffuse and accumulate, resulting in irregular bending of their surface. The efferent muscular actions can be controlled by conveying the output signals from the synaptic devices to the artificial muscle fibers. The applications of this bioinspired neuromuscular system are mainly geared towards neuromorphic prosthetic limbs and neuro-controlled robots [7, 54].

Figure 5. Refer to the following caption and surrounding text.

Figure 5. (a) Diagram of the bioinspired neuromuscular system. (b) EPSC triggered by consecutive electrical spikes with different frequencies. (c) SRDP index vs. electrical spike frequencies. (d) Degradation rate of flexible FNST vs. bending cycle. (e)–(h) Bending state of the artificial muscle fibers under different stimuli.

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Controllable efferent muscular actions of the bioinspired neuromuscular system were realized by exploiting the characteristics of SRDP. When ten consecutive electrical spikes (2 V, 50 ms) were applied under Vd = 0.4 V, EPSC increased monotonically as f increased from 1.82 to 10 Hz (figure 5(b)). SRDP index was defined as the ratio of the EPSCs triggered by the 10th spike (B10) and the first spike (B1); this index also increased monotonically as f increased (figure 5(c)). The initial state of the artificial muscle fiber was unflexed (figure 5(e)). When electrical spikes were applied at f = 3.33 Hz to the FNST, the flexion angle of the artificial muscle fiber was ∼10° (figure 5(f)); as f increased to 10 Hz, the flexion angle of the artificial muscle fiber reached ∼60° (figure 5(g)). Figure S9 shows the statistical curve of signal output for each part of the bioinspired neuromuscular system. These results confirm that the efferent muscular actions of the bioinspired neuromuscular system can be effectively controlled by the FNST by exploiting the SRDP coding strategy.

Furthermore, the FNST showed excellent flexibility. EPSC was collected after different cycles to a bending radius of 1 cm. Under Vd = 0.4 V, the EPSC peak triggered by a single electrical spike (2 V, 50 ms) was slightly degraded after 1, 10, 100, 1000, and 5000 bending cycles (figure S10). Here, the retention rate R was defined as the ratio of the EPSC peak with bending to that without bending. R was greater than ∼95% after 1000 bending cycles and greater than ∼85% after 5000 bending cycles (figure 5(d)). These results demonstrate that this FNST has potential application in wearable electronics.

4. Discussion

A bioinspired neuromuscular system was developed, employing a flexible electro-optical synaptic transistor (FNST) as an information processor and an artificial muscle as an end effector. In this system, the response of artificial muscle fibers were regulated by the synaptic device to imitate the behavior of biological muscles. Leveraging the SRDP characteristic of the FNST device, control over the artificial muscle was achieved. As the frequency of electrical spikes applied to the device increased, the bending degree of the artificial muscle increased correspondingly. Notably, the FNST device can be modulated by both optical pulses and electrical spikes to mimic biological synaptic plasticity, thus presenting potential applications in secure communications. Moreover, the device exhibited remarkable stability against mechanical bending up to 5000 bending cycles with a radius of 1 cm, indicating suitability of the device for wearable electronics. Although this bioinspired neuromuscular system demonstrates the potential for integrating of electronic prosthetics with the human nervous system, there are still issues that need to be addressed, such as achieving compatibility with biological systems. Designing electronic prosthetics with a greater biological realism is essential for improving their compatibility with the sensory and motor nervous systems [55]. Thus, a deeper understanding of human neuromuscular reflex replicas is required, including emerging qualities such as human-like compliance, force and position control, as well as adaptive stiffness [56]. These qualities will enhance the compatibility of neuroprosthetics with the human body. In conclusion, this work demonstrates an artificial neuromuscular system based on neuromorphic electronics employing low-dimensional organic materials, and it allows for integration with robotic or sensory systems towards applications in advanced robotics and wearable electronics.

Acknowledgments

This work was supported by the National Science Fund for Distinguished Young Scholars of China (T2125005), the National Key R&D Program of China (2022YFE0198200, 2022YFA1204500, 2022YFA1204504), the Shenzhen Science and Technology Project (JCYJ20210324121002008), the Natural Science Foundation of Tianjin (Nos. 22JCYBJC01290, 23JCQNJC01440), the Key Project of Nature Science Foundation of Tianjin (No. 22JCZDJC00120), the Fundamental Research Funds for the Central Universities, Nankai University (Nos. BEG124901, BEG124401), the National Natural Science Foundation of China (62204131, 62201290), and the China Postdoctoral Science Foundation (2023T160336). We express our gratitude to Jiaxin Chen (Nankai University, China) for the language polishing of our manuscript.

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