Energy-efficient organic photoelectric synaptic transistors with environment-friendly CuInSe₂ quantum dots for broadband neuromorphic computing

Abstract

Photoelectric synaptic device is a promising candidate component in brain-inspired high-efficiency neuromorphic computing systems. Implementing neuromorphic computing with broad bandwidth is, however, challenging owing to the difficulty in realizing broadband characteristics with available photoelectric synaptic devices. Herein, taking advantage of the type-II heterostructure formed between environmentally friendly CuInSe₂ quantum dots and organic semiconductor, broadband photoelectric synaptic transistors (BPSTs) that can convert light signals ranging from ultraviolet (UV) to near-infrared (NIR) into post-synaptic currents are demonstrated. Essential synaptic functions, such as pair-pulse facilitation, the modulation of memory level, long-term potentiation/depression transition, dynamic filtering, and learning-experience behavior, are well emulated. More significantly, benefitting from broadband responses, information processing functions, including arithmetic computing and pattern recognition can also be simulated in a broadband spectral range from UV to NIR. Furthermore, the BPSTs exhibit obvious synaptic responses even at an ultralow operating voltage of –0.1 mV with an ultralow energy consumption of 75 aJ per event, and show their potential in flexible electronics. This study presents a pathway toward the future construction of brain-inspired neural networks for high-bandwidth neuromorphic computing utilizing energy-efficient broadband photoelectric devices.

Keywords

broadband / environment friendly / neuromorphic computing / photoelectric synaptic transistors / ultralow energy consumption

References

[1] Yang JQ, Wang R, Ren Y, et al. Neuromorphic engineering: from biological to spike-based hardware nervous systems. Adv Mater. 2020; 32(52): e2003610.

[2] Zhou F, Chai Y. Near-sensor and in-sensor computing. Nature Electronics. 2020; 3(11): 664-671.

[3] Yu J, Wang Y, Qin S, et al. Bioinspired interactive neuromorphic devices. Mater Today. 2022; 60: 158-182.

[4] Sun F, Lu Q, Feng S, Zhang T. Flexible artificial sensory systems based on neuromorphic devices. ACS Nano. 2021; 15(3): 3875-3899.

[5] Choi S, Yang J, Wang G. Emerging memristive artificial synapses and neurons for energy-efficient neuromorphic computing. Adv Mater. 2020; 32(51): e2004659.

[6] Wei H, Shi R, Sun L, et al. Mimicking efferent nerves using a graphdiyne-based artificial synapse with multiple ion diffusion dynamics. Nat Commun. 2021; 12(1): 1068.

[7] Shan L, Zeng H, Liu Y, et al. Artificial tactile sensing system with photoelectric output for high accuracy haptic texture recognition and parallel information processing. Nano Lett. 2022; 22(17): 7275-7283.

[8] Zhang Z, Wang S, Liu C, Xie R, Hu W, Zhou P. All-in-one two-dimensional retinomorphic hardware device for motion detection and recognition. Nat Nanotechnol. 2022; 17(1): 27-32.

[9] Xie Z, Zhuge C, Zhao Y, et al. All-solid-state vertical three-terminal n-type organic synaptic devices for neuromorphic computing. Adv Funct Mater. 2022; 32(21): 2107314.

[10] Sun Y, Ding Y, Xie D. Mixed-dimensional van der Waals heterostructures enabled optoelectronic synaptic devices for neuromorphic applications. Adv Funct Mater. 2021; 31(47): 2105625.

[11] Zhang Q, Jin T, Ye X, Geng D, Chen W, Hu W. Organic field effect transistor-based photonic synapses: materials, devices, and applications. Adv Funct Mater. 2021; 31(49): 2106151.

[12] Zhang C, Xu F, Zhao X, et al. Natural polyelectrolyte-based ultraflexible photoelectric synaptic transistors for hemispherical high-sensitive neuromorphic imaging system. Nano Energy. 2022; 95: 107001.

[13] Hou YX, Li Y, Zhang ZC, et al. Large-scale and flexible optical synapses for neuromorphic computing and integrated visible information sensing memory processing. ACS Nano. 2021; 15(1): 1497-1508.

[14] Hong S, Cho H, Kang BH, et al. Neuromorphic active pixel image sensor array for visual memory. ACS Nano. 2021; 15(9): 15362-15370.

[15] Xu F, Zhang C, Zhao X, et al. Intrinsically stretchable photonic synaptic transistors for retina-like visual image systems. J Mater Chem C. 2022; 10(29): 10586-10594.

[16] He Z, Shen H, Ye D, et al. An organic transistor with light intensity-dependent active photoadaptation. Nat Electron. 2021; 4(7): 522-529.

[17] Kwon SM, Cho SW, Kim M, Heo JS, Kim YH, Park SK. Environment-adaptable artificial visual perception behaviors using a light-adjustable optoelectronic neuromorphic device array. Adv Mater. 2019; 31(52): e1906433.

[18] Chen C, He Y, Mao H, et al. A photoelectric spiking neuron for visual depth perception. Adv Mater. 2022; 34(20): e2201895.

[19] Xie D, Wei L, Xie M, et al. Photoelectric visual adaptation based on 0D-CsPbBr₃-quantum-dots/2D-MoS₂ mixed-dimensional heterojunction transistor. Adv Funct Mater. 2021; 31(14): 2010655.

[20] Zhang J, Liu D, Shi Q, et al. Bioinspired organic optoelectronic synaptic transistors based on cellulose nanopaper and natural chlorophyll-a for neuromorphic systems. NPJ Flexible Electron. 2022; 6(1): 30.

[21] Liao F, Zhou Z, Kim BJ, et al. Bioinspired in-sensor visual adaptation for accurate perception. Nat Electron. 2022; 5(2): 84-91.

[22] Jayachandran D, Oberoi A, Sebastian A, et al. A low-power biomimetic collision detector based on an in-memory molybdenum disulfide photodetector. Nat Electron. 2020; 3(10): 646-655.

[23] Shi J, Jie J, Deng W, et al. A fully solution-printed photosynaptic transistor array with ultralow energy consumption for artificial-vision neural networks. Adv Mater. 2022; 34(18): e2200380.

[24] Shao H, Li Y, Chen J, et al. Mimicking evasive behavior in wavelength-dependent reconfigurable phototransistors with ultralow power consumption. SmartMat. 2023.

[25] Chen J, Zhou Z, Kim BJ, et al. Optoelectronic graded neurons for bioinspired in-sensor motion perception. Nat Nanotechnol. 2023; 18(8): 882-888.

[26] Park HL, Kim H, Lim D, et al. Retina-inspired carbon nitride-based photonic synapses for selective detection of UV light. Adv Mater. 2020; 32(11): e1906899.

[27] Zhai Y, Zhou Y, Yang X, et al. Near infrared neuromorphic computing via upconversion-mediated optogenetics. Nano Energy. 2020; 67: 104262.

[28] Zhu QB, Li B, Yang DD, et al. A flexible ultrasensitive optoelectronic sensor array for neuromorphic vision systems. Nat Commun. 2021; 12(1): 1798.

[29] Pradhan B, Das S, Li J, et al. Ultrasensitive and ultrathin phototransistors and photonic synapses using perovskite quantum dots grown from graphene lattice. Sci Adv. 2020; 6(7): eaay5225.

[30] Wang S, Chen H, Liu T, et al Retina-inspired organic photonic synapses for selective detection of SWIR light. Angew Chem Int Ed. 2023; 62(6): e202213733.

[31] Huang X, Liu Y, Liu G, et al Short-wave infrared synaptic phototransistor with ambient light adaptability for flexible artificial night visual system. Adv Funct Mater. 2023; 33(1): 2208836.

[32] Kuang J, Liu K, Liu M, et al. Interface defects tuning in polymer-perovskite phototransistors for visual synapse and adaptation functions. Adv Funct Mater. 2023; 33(5): 2209502.

[33] Yu JJ, Liang LY, Hu LX, et al. Optoelectronic neuromorphic thin-film transistors capable of selective attention and with ultra-low power dissipation. Nano Energy. 2019; 62: 772-780.

[34] Zhang J, Lu Y, Dai S, et al. Retina-inspired organic heterojunction-based optoelectronic synapses for artificial visual systems. Research. 2021; 2021: 7131895.

[35] Ge S, Huang F, He J, et al. Bidirectional photoresponse in perovskite-ZnO heterostructure for fully optical-controlled artificial synapse. Adv Opt Mater. 2022; 10(11): 2200409.

[36] Ni Y, Yang L, Feng J, Liu J, Sun L, Xu W. Flexible optoelectronic neural transistors with broadband spectrum sensing and instant electrical processing for multimodal neuromorphic computing. SmartMat. 2023; 4(2): e1154.

[37] Shao H, Li Y, Yang W, et al. A reconfigurable optoelectronic synaptic transistor with stable Zr-CsPbI₃ nanocrystals for visuomorphic computing. Adv Mater. 2023; 35(12): 2208497.

[38] Wang Y, Zhu Y, Li Y, Zhang Y, Yang D, Pi X. Dual-modal optoelectronic synaptic devices with versatile synaptic plasticity. Adv Funct Mater. 2022; 32(1): 2107973.

[39] Hao Z, Wang H, Jiang S, et al. Retina-inspired self-powered artificial optoelectronic synapses with selective detection in organic asymmetric heterojunctions. Adv Sci. 2022; 9(7): e2103494.

[40] Huang X, Li Q, Shi W, et al. Dual-mode learning of ambipolar synaptic phototransistor based on 2D perovskite/organic heterojunction for flexible color recognizable visual system. Small. 2021; 17(36): e2102820.

[41] Ni Y, Feng J, Liu J, et al. An artificial nerve capable of UV-perception, NIR-vis switchabl. plasticity modulation, and motion state monitoring. Adv Sci. 2022; 9(1): e2102036.

[42] Zhang J, Guo P, Guo Z, et al. Retina-inspired artificial synapses with ultraviolet to near-infrared broadband responses for energy-efficient neuromorphic visual systems. Adv Funct Mater. 2023; 33(32): 2302885.

[43] Pi L, Wang P, Liang S-J, et al. Broadband convolutional processing using band-alignment-tunable heterostructures. Nat Electron. 2022; 5(4): 248-254.

[44] Cho SW, Kwon SM, Kim Y-H, Park SK. Recent progress in transistor-based optoelectronic synapses: from neuromorphic computing to artificial sensory system. Adv Intelli Syst. 2021; 3(6): 2000162.

[45] Hu C, Dong D, Yang X, et al. Synergistic effect of hybrid PbS quantum dots/2D-WSe₂ toward high performance and broadband phototransistors. Adv Funct Mater. 2017; 27(2): 1603605.

[46] Chen, S, Wang Y, Liu Q, et al. Broadband enhancement of PbS quantum dot solar cells by the synergistic effect of plasmonic gold nanobipyramids and nanospheres. Adv Energy Mater. 2018; 8(8): 1701194.

[47] Zhang H, Zhang Y, Song X, et al. Highly photosensitive vertical phototransistors based on a poly(3-hexylthiophene) and PbS quantum dot layered heterojunction. ACS Photon. 2017; 4(3): 584-592.

[48] Shen T, Li F, Zhang Z, Xu L, Qi J. High-performance broadband photodetector based on monolayer MoS₂ hybridized with environment-friendly CuInSe₂ quantum dots. ACS Appl Mater Interfaces. 2020; 12(49): 54927-54935.

[49] Yin L, Han C, Zhang Q, et al. Synaptic silicon-nanocrystal phototransistors for neuromorphic computing. Nano Energy. 2019; 63: 103859.

[50] Huang W, Hang P, Wang Y, et al. Zero-power optoelectronic synaptic devices. Nano Energy. 2020; 73: 104790.

[51] Zhu Y, Huang W, He Y, et al. Perovskite-enhanced silicon-nanocrystal optoelectronic synaptic devices for the simulation of biased and correlated random-walk learning. Research. 2020; 2020: 7538450.

[52] Wang Y, Lv Z, Chen J, et al. Photonic synapses based on inorganic perovskite quantum dots for neuromorphic computing. Adv Mater. 2018; 30(38): e1802883.

[53] Liu Y, Liu D, Gao C, et al. Self-powered high-sensitivity all-in-one vertical tribo-transistor device for multi-sensing-memory-computing. Nat Commun. 2022; 13(1): 7917.

[54] Abbott LF, Regehr WG. Synaptic computation. Nature. 2004; 431(7010): 796-803.

[55] Guo R, Huang F, Zheng K, Pullerits T, Tian J. CuInSe₂ quantum dots hybrid hole transfer layer for halide perovskite photodetectors. ACS Appl Mater Interfaces. 2018; 10(41): 35656-35663.

[56] Guo R, Shen T, Tian J. Broadband hybrid organic/CuInSe₂ quantum dot photodetectors. J Mater Chem C. 2018; 6(10): 2573-2579.

[57] Li Y, Wang J, Yang Q, Shen G. Flexible artificial optoelectronic synapse based on lead-free metal halide nanocrystals for neuromorphic computing and color recognition. Adv Sci. 2022; 9(22): e2202123.

[58] Salin PA, Scanziani M, Malenka RC, Nicoll RA. Distinct short-term plasticity at two excitatory synapses in the hippocampus. Proc Natl Acad Sci. 1996; 93(23): 13304-13309.

[59] Lv Z, Chen M, Qian F, et al. Mimicking neuroplasticity in a hybrid biopolymer transistor by dual modes modulation. Adv Funct Mater. 2019; 29(31): 1902374.

[60] Gao S, Liu G, Yang H, et al. An oxide Schottky junction artificial optoelectronic synapse. ACS Nano. 2019; 13(2): 2634-2642.

[61] Zhang J, Shi Q, Wang R, et al. Spectrum-dependent photonic synapses based on 2D imine polymers for power-efficient neuromorphic computing. InfoMat. 2021; 3: 904-916.

[62] Wang X, Hao D, Huang J. Dye-sensitized perovskite/organic semiconductor ternary transistors for artificial synapses. Sci China Mater. 2022; 65(9): 2521-2528.

[63] Wang K, Chen J, Yan X. MXene Ti₃C₂ memristor for neuromorphic behavior and decimal arithmetic operation applications. Nano Energy. 2021; 79: 105453.

[64] Sun J, Oh S, Choi Y, et al. Optoelectronic synapse based on IGZO-alkylated graphene oxide hybrid structure. Adv Funct Mater. 2018; 28(47): 1804397.

[65] Ahmed T, Tahir M, Low MX, et al. Fully light-controlled memory and neuromorphic computation in layered black phosphorus. Adv Mater. 2020; 33(10): e2004207.

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