| Literature DB >> 34716679 |
Yao Ni1,2,3,4, Jiulong Feng1,2,3,4, Jiaqi Liu1,2,3,4, Hang Yu5,6, Huanhuan Wei1,2,3,4, Yi Du1,2,3,4, Lu Liu1,2,3,4, Lin Sun1,2,3,4, Jianlin Zhou5, Wentao Xu1,2,3,4.
Abstract
The first flexible organic-heterojunction neuromorphic transistor (OHNT) that senses broadband light, including near-ultraviolet (NUV), visible (vis), and near-infrared (NIR), and processes multiplexed-neurotransmission signals is demonstrated. For UV perception, electrical energy consumption down to 536 aJ per synaptic event is demonstrated, at least one order of magnitude lower than current UV-sensitive synaptic devices. For NIR- and vis-perception, switchable plasticity by alternating light sources is yielded for recognition and memory. The device emulates multiplexed neurochemical transition of different neurotransmitters such as dopamine and noradrenaline to form short-term and long-term responses. These facilitate the first realization of human-integrated motion state monitoring and processing using a synaptic hardware, which is then used for real-time heart monitoring of human movement. Motion state analysis with the 96% accuracy is then achieved by artificial neural network. This work provides important support to future biomedical electronics and neural prostheses.Entities:
Keywords: artificial neural network; broadband light; flexible organic-heterojunction neuromorphic transistors; motion state monitoring; multiplexed-neurotransmission signals
Year: 2021 PMID: 34716679 PMCID: PMC8728819 DOI: 10.1002/advs.202102036
Source DB: PubMed Journal: Adv Sci (Weinh) ISSN: 2198-3844 Impact factor: 16.806
Figure 1Schematic illustration and material characteristics. a) Schematic of an afferent nervous system that integrates optical sensing and dual‐electric signal processing units under electro‐optical pulse. b) Schematic of the transmissions of two kinds of excitatory neurotransmitters in the synaptic cleft under presynaptic spikes. c) Chemical structures of TFSI anion and EMIM cation in the ion gel and band diagrams of the dual channel; PSCs consisting of electrons (e−‐PSC) or holes (h+‐PSC) are generated in the F16CuPc or C8‐BTBT channel in response to two kinds of opposite presynaptic spikes. d) Atomic force microscope (AFM) images of lower PMMA: C8‐BTBT and upper F16CuPc films. e) XRD patterns and f) UV–vis–NIR absorption spectrum of F16CuPc, C8‐BTBT, and C8‐BTBT/F16CuPc heterojunction.
Figure 2Broadband light perception and switchable synaptic plasticity. a) Artificial light‐perception afferent nerve composed of a sensing unit and a processing unit, which emulate the perception of lights at various wave lengths (NUV, vis, and NIR) and the conversion of photoelectric signals with high‐sensitive, LTP, and STP, respectively. b) (left) ∆L‐EPSCs (∆L‐EPSC = L‐EPSC − background current) for OHNT triggered by illumination at wavelengths of 380, 640, and 790 nm (V DS for 380 nm = −1 V; V DS for 640 and 790 nm = 0.2 V); (right) Energy band diagrams under three types of illuminations are on the right. c) PPF index according to the time interval, at different wavelengths of 380, 640, and 790 nm. d) ∆L‐EPSCs triggered by illuminations at different wavelengths of 380, 640, and 790 nm with different frequency. e) ∆L‐EPSCs triggered by different number of illuminations at different wavelengths of 380, 640, and 790 nm.
Figure 3Light‐induced nerve functions: NUV‐receptor, IR‐induced recognition and vis‐induced memory. a) Electrical energy consumption according to the amplitude of V DS, at the wavelength of 380 nm. b) L‐EPSCs triggered by 380 nm UV light of different duty cycles, which simulates the proposed pain perception model caused by ultraviolet keratitis. c) LTP and STP triggered by 640 nm vis light, and 790 nm NIR light, respectively. d) ∆L‐EPSCs triggered by two pairs of spatiotemporally correlated 790 nm NIR light signals versus time. e) Optical wireless communication via OHNT with 790 nm NIR light signals representing the International Morse code of “NKU.” f) Presynaptic pulses programmed OHNT array with 640 nm vis light signals, emulating 5 × 5 pixel image of “NKU.”
Comparison of our work with previously reported opto‐electronic neuromorphic transistors in terms of the light intensity and electrical energy consumption under UV irradiation
| Structure | Light wavelength | Light intensity | Electrical energy consumption | Year | Ref. |
|---|---|---|---|---|---|
| CsPbBr3 QDs | 365 nm | 0.153 mW cm−2 | 1.4 × 103 pJ | 2018 | [ |
| Si nanocrystals | 375 nm | 2.68 mW cm−2 | 0.14 nJ | 2019 | [ |
| CsPbBr3 perovskite quantum dots | 400 nm | 100 µW cm−2 | 4.1 pJ | 2019 | [ |
| Black phosphorus | 365 nm | 3 mW cm−2 | 9.24 × 102 pJ | 2019 | [ |
|
NT‐CN /PMMA /pentacene | 365 nm | 0.38 mW cm−2 | 18.06 fJ | 2020 | [ |
| C8‐BTBT /F16CuPc | 380 nm | 7 µW cm−2 | 536 aJ | This work |
Figure 4h+‐PSC based short‐term plasticity for a real‐time heart monitoring and alarming artificial nervous system. a) EPSC for OHNT triggered by negative spikes of −4.5 V (V DS = −1 V). b) EPSC triggered by 30 consecutive negative spikes; SNDP index (A n/A 1) according to the number of negative spikes from 1 to 30. c) PPF/PPD index according to the time interval. d) SFDP index as a function of the frequency of negative spikes after the OHNT has experienced different durations of spikes. e) 3 cycles of SFDP stimulated at the frequency of negative spike from 0.3 to 10 Hz. f,g) Schematic illustration of artificial nerve conduction system for heart signal processing, including piezoresistive module, pretreatment circuit and OHNT devices. h) Heart‐PSCs under different movements (sitting, stand up, standing, walking, running, sitting for resting).
Figure 5e−‐PSC based long‐term plasticity for exercise state recognition. a) EPSC for OHNT triggered by positive spikes of 3 V (VDS = 0.2 V). b) EPSC triggered by different number of positive spikes. c) EPSCs with different number of positive spikes according to the degradation time. d) Trend of ∆EPSCs (∆EPSC = EPSC − background current) with bending cycles. The radius of curvature was 0.8 cm during the test. e) EPSCs triggered by positive spikes with different single‐spike durations; SDDP index (A n/A 1) according to the duration of single spike from 0.05 to 0.5 s. f) Potentiation‐depression regulations. Synaptic potentiation triggered by a series of 30 positive spikes (4 V), and depression triggered by various series of 30 negative spikes with different amplitude (−1, −1.2, −1.5, −1.8, or −2 V). g) Neural network that uses OHNT array for PPG pattern recognition, in which 1536 input units and 4 output units are fully connected: state #1 = “walk,” state #2 = “Run,” state #3 = “Low‐resistance‐bike (LRB),” and state #4 = “High‐resistance‐bike (HRB)” to represent states of exertion. h) Diagram of a multilayer artificial neural network. i) Changes in the weight values of 1536 input synapses during 200 learning phases, under case #1. j) Convergence curves for the PPG pattern with respect to the number of learning epochs, under different cases. k) Confusion matrix for a classification test involving 125 PPG images after 200 epochs, under case #2.