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Wentao Xu
Nankai University
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Somatosensory nerves require synapses to respond efficiently and in parallel for receving and transmiting biological signals. The gap between biological systems and conventional electronics needs ionotronics to bridge. However, the exploration of new materials and the systematic construction of ionotronics still pose challenges. Graphdiyne, a highly π-extended two-dimensional (2D) carbon allotrope, has demonstrated potential applications in ionic peripheral systems for its inherent network holes that can be used for rapid and selective transmission of diverse ions. Here, a graphdiyne-based artificial synapse (GAS), exhibiting intrinsic short-term plasticity, has been proposed to mimic the biological signal transmission behaviors. An record-breaking impulse responsiveness (±5 mV) that is an order of magnitude exceeding biological level has been realized for ultra-sensitive and power-efficient brain-inspired applications, with the lowest femtowatt-level consumption (~16.7 fW). Most importantly, GAS is capable of parallelly processing signals transmitted from multiple preneurons and therefore realizing dynamic logics and spatiotemporal rules. In a proof-of-concept demonstration, our artificial efferent nerve, connecting GAS with artificial muscles, completes the information integration of preneurons and the information output of motor neurons, which is advantageous for coalescing multiple sensory feedbacks (e.g., visual and tactile) and reacting to these events. Our synaptic element has potential applications in bioinspired peripheral nervous systems of soft electronics and neurorobotics.
Keywords
Graphdiyne, artificial synapse, short-term plasticity, parallel information processing, artificial efferent nerve
Figure 1
Figure 2
Figure 3
Figure 4
There is NO Competing Interest.
This is a list of supplementary files associated with this preprint. Click to download.
- FigureS1.jpg
a Schematic illustration of the liquid/liquid interfacial protocol and the corresponding digital photo. GDY is obtained from the middle layer of the glass cylinder. The catalyst and the hexaethynylbenzene (HEB) monomer were placed above and below the intermediate layer of pure water. b SEM image of the obtained GDY. The scale bar corresponds to 4 μm. c SEM image (Scale bar: 400 nm), d AFM images, e cross-section SEM image (Scale bar: 1 μm) of the spin-coated GDY film.
- FigureS2.jpg
I–V curves measured in sweep cycles of a, c -5 to 5 V, …, -1 to 1 V, and b, d 5 to -5 V, …, 1 to -1 V in Li-GAS a and b and Na-GAS c and d, respectively. The curve shows the ion dynamics process, electric double layer process and electrochemical doping process of the device under the action of pulse. e I–V curves and f schematic illustration of ions’ dynamic diffusion in a sweep cycle of -5 → 5 V. Eight sweeping cycles were applied in Li-GAS. g Initial and termination of current values for Na-GAS in different voltage linear sweep modes. h Initial and termination current ratio (Ipre/Ipost) versus time interval (Δtpost-pre) between successive pulses in Na-GAS.
- FigureS3.jpg
a Peak value of postsynaptic current with different negative pulse amplitudes in Li-GAS and Na-GAS. Inset: Postsynaptic current triggered by a single spike in Li-GAS. Retention curve under positive and negative pulses and corresponding retention time in b Li-GAS and c Na-GAS. In order to further demonstrate the short-term plasticity of the device, the retention curve was analyzed and the current decayed to near the baseline within a few seconds (< 6 s).
- FigureS4.jpg
Postsynaptic currents triggered by two consecutively negative pulses and corresponding PPF index in a Li-GAS and b Na-GAS. c Postsynaptic current at different pulse number in Na-GAS. d Gain of postsynaptic currents (SNDP index; A10/A1×100%) plotted as a function of presynaptic pulse number in Li-GAS and Na-GAS. e Postsynaptic current at different pulse duration in Na-GAS. f Gain of postsynaptic currents (SDDP index; A10/A1×100%) plotted as a function of presynaptic pulse duration in Li-GAS and Na-GAS.
- FigureS5.jpg
a Postsynaptic current triggered by nonidentical negative pulse sequence and b the corresponding current (peak current and attenuation current) color image in Li-GAS. c Postsynaptic current triggered by negative pulses with amplitude of -3.5 and -5 V in Li-GAS. d Postsynaptic current triggered by 5 negative and 5 positive pulses with amplitude of ± 5 mV in Na-GAS.
- FigureS6.jpg
a The amplitude of postsynaptic current at T = 0 plotted as a function of ΔT. b A spiking logic response by two presynaptic inputs (synapse 1, synapse 2, synapse 1 + synapse 2) with different pulse duration and correspomding truth tables for “AND” logic (duration: 0.82762 s) and “OR” logic (duration: 2.48732 s), respectively.
- FigureS7.jpg
a Postsynaptic current triggered by two presynaptic inputs at 0.48 Hz from the same time period to different time periods. b Postsynaptic current triggered by two presynaptic inputs with different frequency (0.48 and 0.8 Hz) from the different time period to same time periods. c Postsynaptic current triggered by two presynaptic inputs at 0.344 Hz from the different time period to same time periods. d Postsynaptic current triggered by two presynaptic inputs with different frequency (0.344 and 0.60 Hz) from the different time period to same time periods. e The current peak shape of the postsynaptic current, which is used to estimate the frequency and amplitude of the presynaptic pulse. The response triggered by four low-frequency (0.344, 0.4, 0.6, and 0.8 Hz) presynaptic pulses can be well integrated and output. Analysis of the temporal profiles of postsynaptic currents in these four cases demonstrates the possibility of a bioinspired approach to identify the frequency of presynaptic pulse sequences, which can be estimated from the shape of postsynaptic signals and peak-valley time interval. Furthermore, GAS can identify the frequency of presynaptic inputs to a certain extent based on the postsynaptic current to infer and analyze the sensory information transmitted from afferent nerves.
- FigureS8.jpg
Diagram of synaptic device- amplifier circuit-polymer actuator system. As a demonstration, the nano-amp-level postsynaptic current of a single device (Na-GAS) is amplified and the motor neuron synaptic potential is output to drive the artificial muscle (polymer actuator).
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A new preprint design is coming!
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See the published version of this preprint at Nature Communications.
This is a preprint, a preliminary version of a manuscript that has not completed peer review at a journal. Research Square does not conduct peer review prior to posting preprints. The posting of a preprint on this server should not be interpreted as an endorsement of its validity or suitability for dissemination as established information or for guiding clinical practice.
Learn more about In Review
Article
Wentao Xu
Nankai University
Corresponding Author
Badges
Prescreen
This manuscript passed our Prescreen assessment
Complete author information
Appropriate declaration statements
Potential risks to human health
Prescreen
Peer Review Timeline
CURRENT STATUS: Published
View the published article at Nature Communications.
Version 1
Posted 07 Aug, 2020
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
License:
This work is licensed under a CC BY 4.0 License. Read Full License
View the published article at Nature Communications.
Somatosensory nerves require synapses to respond efficiently and in parallel for receving and transmiting biological signals. The gap between biological systems and conventional electronics needs ionotronics to bridge. However, the exploration of new materials and the systematic construction of ionotronics still pose challenges. Graphdiyne, a highly π-extended two-dimensional (2D) carbon allotrope, has demonstrated potential applications in ionic peripheral systems for its inherent network holes that can be used for rapid and selective transmission of diverse ions. Here, a graphdiyne-based artificial synapse (GAS), exhibiting intrinsic short-term plasticity, has been proposed to mimic the biological signal transmission behaviors. An record-breaking impulse responsiveness (±5 mV) that is an order of magnitude exceeding biological level has been realized for ultra-sensitive and power-efficient brain-inspired applications, with the lowest femtowatt-level consumption (~16.7 fW). Most importantly, GAS is capable of parallelly processing signals transmitted from multiple preneurons and therefore realizing dynamic logics and spatiotemporal rules. In a proof-of-concept demonstration, our artificial efferent nerve, connecting GAS with artificial muscles, completes the information integration of preneurons and the information output of motor neurons, which is advantageous for coalescing multiple sensory feedbacks (e.g., visual and tactile) and reacting to these events. Our synaptic element has potential applications in bioinspired peripheral nervous systems of soft electronics and neurorobotics.
Figure 1
Figure 2
Figure 3
Figure 4
There is NO Competing Interest.
This is a list of supplementary files associated with this preprint. Click to download.
- FigureS1.jpg
a Schematic illustration of the liquid/liquid interfacial protocol and the corresponding digital photo. GDY is obtained from the middle layer of the glass cylinder. The catalyst and the hexaethynylbenzene (HEB) monomer were placed above and below the intermediate layer of pure water. b SEM image of the obtained GDY. The scale bar corresponds to 4 μm. c SEM image (Scale bar: 400 nm), d AFM images, e cross-section SEM image (Scale bar: 1 μm) of the spin-coated GDY film.
- FigureS2.jpg
I–V curves measured in sweep cycles of a, c -5 to 5 V, …, -1 to 1 V, and b, d 5 to -5 V, …, 1 to -1 V in Li-GAS a and b and Na-GAS c and d, respectively. The curve shows the ion dynamics process, electric double layer process and electrochemical doping process of the device under the action of pulse. e I–V curves and f schematic illustration of ions’ dynamic diffusion in a sweep cycle of -5 → 5 V. Eight sweeping cycles were applied in Li-GAS. g Initial and termination of current values for Na-GAS in different voltage linear sweep modes. h Initial and termination current ratio (Ipre/Ipost) versus time interval (Δtpost-pre) between successive pulses in Na-GAS.
- FigureS3.jpg
a Peak value of postsynaptic current with different negative pulse amplitudes in Li-GAS and Na-GAS. Inset: Postsynaptic current triggered by a single spike in Li-GAS. Retention curve under positive and negative pulses and corresponding retention time in b Li-GAS and c Na-GAS. In order to further demonstrate the short-term plasticity of the device, the retention curve was analyzed and the current decayed to near the baseline within a few seconds (< 6 s).
- FigureS4.jpg
Postsynaptic currents triggered by two consecutively negative pulses and corresponding PPF index in a Li-GAS and b Na-GAS. c Postsynaptic current at different pulse number in Na-GAS. d Gain of postsynaptic currents (SNDP index; A10/A1×100%) plotted as a function of presynaptic pulse number in Li-GAS and Na-GAS. e Postsynaptic current at different pulse duration in Na-GAS. f Gain of postsynaptic currents (SDDP index; A10/A1×100%) plotted as a function of presynaptic pulse duration in Li-GAS and Na-GAS.
- FigureS5.jpg
a Postsynaptic current triggered by nonidentical negative pulse sequence and b the corresponding current (peak current and attenuation current) color image in Li-GAS. c Postsynaptic current triggered by negative pulses with amplitude of -3.5 and -5 V in Li-GAS. d Postsynaptic current triggered by 5 negative and 5 positive pulses with amplitude of ± 5 mV in Na-GAS.
- FigureS6.jpg
a The amplitude of postsynaptic current at T = 0 plotted as a function of ΔT. b A spiking logic response by two presynaptic inputs (synapse 1, synapse 2, synapse 1 + synapse 2) with different pulse duration and correspomding truth tables for “AND” logic (duration: 0.82762 s) and “OR” logic (duration: 2.48732 s), respectively.
- FigureS7.jpg
a Postsynaptic current triggered by two presynaptic inputs at 0.48 Hz from the same time period to different time periods. b Postsynaptic current triggered by two presynaptic inputs with different frequency (0.48 and 0.8 Hz) from the different time period to same time periods. c Postsynaptic current triggered by two presynaptic inputs at 0.344 Hz from the different time period to same time periods. d Postsynaptic current triggered by two presynaptic inputs with different frequency (0.344 and 0.60 Hz) from the different time period to same time periods. e The current peak shape of the postsynaptic current, which is used to estimate the frequency and amplitude of the presynaptic pulse. The response triggered by four low-frequency (0.344, 0.4, 0.6, and 0.8 Hz) presynaptic pulses can be well integrated and output. Analysis of the temporal profiles of postsynaptic currents in these four cases demonstrates the possibility of a bioinspired approach to identify the frequency of presynaptic pulse sequences, which can be estimated from the shape of postsynaptic signals and peak-valley time interval. Furthermore, GAS can identify the frequency of presynaptic inputs to a certain extent based on the postsynaptic current to infer and analyze the sensory information transmitted from afferent nerves.
- FigureS8.jpg
Diagram of synaptic device- amplifier circuit-polymer actuator system. As a demonstration, the nano-amp-level postsynaptic current of a single device (Na-GAS) is amplified and the motor neuron synaptic potential is output to drive the artificial muscle (polymer actuator).
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