Environment‐Adaptable Artificial Visual Perception Behaviors Using a Light‐Adjustable Optoelectronic Neuromorphic Device Array

Emulating the biological visual perception system typically requires a complex architecture including the integration of an artificial retina and optic nerves with various synaptic behaviors. However, self-adaptive synaptic behaviors, which are frequently translated into visual nerves to adjust environmental light intensities, have been one of the serious challenges for the artificial visual perception system. Here, an artificial optoelectronic neuromorphic device array to emulate the light-adaptable synaptic functions (photopic and scotopic adaptation) of the biological visual perception system is presented. By employing an artificial visual perception circuit including a metal chalcogenide photoreceptor transistor and a metal oxide synaptic transistor, the optoelectronic neuromorphic device successfully demonstrates diverse visual synaptic functions such as phototriggered short-term plasticity, long-term potentiation, and neural facilitation. More importantly, the environment-adaptable perception behaviors at various levels of the light illumination are well reproduced by adjusting load transistor in the circuit, exhibiting the acts of variable dynamic ranges of biological system. This development paves a new way to fabricate an environmental-adaptable artificial visual perception system with profound implications for the field of future neuromorphic electronics.

[1]  Jae Hyun Kim,et al.  High-performance and scalable metal-chalcogenide semiconductors and devices via chalco-gel routes , 2018, Science Advances.

[2]  H-S Philip Wong,et al.  Artificial optic-neural synapse for colored and color-mixed pattern recognition , 2018, Nature Communications.

[3]  Kevin C. See,et al.  Solution-deposited sodium beta-alumina gate dielectrics for low-voltage and transparent field-effect transistors. , 2009, Nature materials.

[4]  W. Hu,et al.  A Ferroelectric/Electrochemical Modulated Organic Synapse for Ultraflexible, Artificial Visual‐Perception System , 2018, Advanced materials.

[5]  Xiaodong Chen,et al.  Artificial Sensory Memory , 2019, Advanced materials.

[6]  H. Barlow Temporal and spatial summation in human vision at different background intensities , 1958, The Journal of physiology.

[7]  Young Sun,et al.  All‐Solid‐State Synaptic Transistor with Ultralow Conductance for Neuromorphic Computing , 2018, Advanced Functional Materials.

[8]  Yang Hui Liu,et al.  Freestanding Artificial Synapses Based on Laterally Proton‐Coupled Transistors on Chitosan Membranes , 2015, Advanced materials.

[9]  David-Wei Zhang,et al.  A MoS2/PTCDA Hybrid Heterojunction Synapse with Efficient Photoelectric Dual Modulation and Versatility , 2018, Advanced materials.

[10]  Young Min Song,et al.  Bioinspired Artificial Eyes: Optic Components, Digital Cameras, and Visual Prostheses , 2018 .

[11]  Zhenan Bao,et al.  Stretchable organic optoelectronic sensorimotor synapse , 2018, Science Advances.

[12]  Yong-Young Noh,et al.  Flexible metal-oxide devices made by room-temperature photochemical activation of sol–gel films , 2012, Nature.

[13]  Youngjune Park,et al.  Reversible uptake and release of sodium ions in layered SnS2-reduced graphene oxide composites for neuromorphic devices. , 2019, Nanoscale.

[14]  John L. Barbur,et al.  Photopic, Mesopic, and Scotopic Vision and Changes in Visual Performance , 2010 .

[15]  S. Park,et al.  Multi-spectral gate-triggered heterogeneous photonic neuro-transistors for power-efficient brain-inspired neuromorphic computing , 2019 .

[16]  Fei Yu,et al.  Ionotronic Neuromorphic Devices for Bionic Neural Network Applications , 2019, physica status solidi (RRL) – Rapid Research Letters.

[17]  Li Qiang Zhu,et al.  Restickable Oxide Neuromorphic Transistors with Spike‐Timing‐Dependent Plasticity and Pavlovian Associative Learning Activities , 2018, Advanced Functional Materials.

[18]  Zhenan Bao,et al.  A bioinspired flexible organic artificial afferent nerve , 2018, Science.

[19]  Ion Dependence of Gate Dielectric Behavior of Alkali Metal Ion-Incorporated Aluminas in Oxide Field-Effect Transistors , 2013 .

[20]  W. Regehr,et al.  Short-term synaptic plasticity. , 2002, Annual review of physiology.

[21]  Yeongjun Lee,et al.  Organic Synapses for Neuromorphic Electronics: From Brain-Inspired Computing to Sensorimotor Nervetronics. , 2019, Accounts of chemical research.

[22]  Young Sun,et al.  A Synaptic Transistor based on Quasi‐2D Molybdenum Oxide , 2017, Advanced materials.

[23]  Ruipeng Li,et al.  Modulation‐Doped In2O3/ZnO Heterojunction Transistors Processed from Solution , 2017, Advanced materials.

[24]  M. Kanatzidis,et al.  Low-temperature fabrication of high-performance metal oxide thin-film electronics via combustion processing. , 2011, Nature materials.

[25]  Qinghua Zhang,et al.  A Ferrite Synaptic Transistor with Topotactic Transformation , 2019, Advances in Materials.

[26]  M. Marinella,et al.  A non-volatile organic electrochemical device as a low-voltage artificial synapse for neuromorphic computing. , 2017, Nature materials.

[27]  Wei Li,et al.  Broadband optoelectronic synaptic devices based on silicon nanocrystals for neuromorphic computing , 2018, Nano Energy.

[28]  Di Chen,et al.  An Artificial Flexible Visual Memory System Based on an UV‐Motivated Memristor , 2018, Advanced materials.

[29]  Yuchao Yang,et al.  Ion Gated Synaptic Transistors Based on 2D van der Waals Crystals with Tunable Diffusive Dynamics , 2018, Advanced materials.

[30]  Hea-Lim Park,et al.  Versatile neuromorphic electronics by modulating synaptic decay of single organic synaptic transistor: From artificial neural networks to neuro-prosthetics , 2019, Nano Energy.

[31]  Xinge Yu,et al.  Metal oxides for optoelectronic applications. , 2016, Nature materials.

[32]  Hong-Joon Yoon,et al.  Transcutaneous ultrasound energy harvesting using capacitive triboelectric technology , 2019, Science.