Towards Artificial Visual Sensory System: Organic Optoelectronic Synaptic Materials and Devices

Organic Synaptic Transistors Based on C8-BTBT/PMMA/PbS QDs for UV to NIR Face Recognition Systems

Developing optoelectronic synaptic devices with low power consumption, broadband response, and biological compatibility is crucial to simulate the functions of optic nerve. Here, an organic synapse transistor based on C8-BTBT/PMMA/PbS quantum dots (PbS QDs) is fabricated, which has good stability, low power consumption (as low as 0.49 fJ per event under 800 nm near-infrared optical pulse), and broadband response from ultraviolet to near-infrared wavelengths. Based on the trap and release of photogenerated carriers by PbS QDs, a series of synaptic behaviors are simulated by the device. Furthermore, we use artificial neural network as the model to realize the recognition of facial feature image in the broad spectral range; the recognition rate reached 96.25% (350 nm ultraviolet), 92.14% (580 nm visible), and 90.03% (800 nm near-infrared). This work is beneficial for advancing the development of future artificial intelligence vision sensing.

An optoelectrochemical synapse based on a single-component n-type mixed conductor

Organic mixed ionic-electronic conductors (OMIECs) are materials that can be used to build bio-inspired electronic devices as they emulate ion-based cellular communication through doping with aqueous ionic charges. The integration of charge photogeneration and electrochemical doping processes in the polymer film enables optoelectronic applications that involve synaptic transistors. However, no OMIEC has yet been implemented to create a miniaturized photoactive platform capable of perceiving and processing multi-spectral visual information. Here, we present a materials and device design concept in which an n-type OMIEC film is incorporated into the micron-scale channel of an electrochemical transistor operating directly in an aqueous electrolyte under ambient conditions. The conjugated polymer channel, consisting of a fluorinated bisistain-lactone-bithiazole acceptor, has a current modulated in response to both electrical and optical stimuli, emulating the multimodal function of the visual nervous system. Our optoelectrochemical synapse achieves multilevel conductance states as well as transduction of visual information covering ultraviolet, visible, and near-infrared regions of the spectrum - a range beyond that of the human visual system's perception. The resulting transistor active-matrix array is capable of adaptive sensing, memory, and pre-processing of visual information, demonstrating an efficient optoelectronic neuromorphic system with multi-task learning capability.

Molecular Cocrystal Strategy for Retinamorphic Vision with UV-Vis-NIR Perception and Fast Recognition

Neuromorphic vision sensors capable of multispectral perception and efficient recognition are highly desirable for bioretina emulation, but their realization is challenging. Here, we present a cocrystal strategy for preparing an organic nanowire retinamorphic vision sensor with UV-vis-NIR perception and fast recognition. By leveraging molecular-scale donor-acceptor interpenetration and charge-transfer interfaces, the cocrystal nanowire device exhibits ultrawide photoperception ranging from 350 to 1050 nm, fast photoresponse of 150 ms, high specific detectivity of 8.2 × 1012 Jones, and responsivity of 15 A W-1, as well as retina-like photosynaptic plasticity behaviors. Utilizing the sensor nerve and convolutional neural network, the architecture achieves 90% accuracy in recognizing colorful images. The cocrystal design offers an effective method for constructing nanowire photosynases with high performance in artificial visual systems.

Optically Modulated Nanofluidic Ionic Transistor for Neuromorphic Functions

Neuromorphic systems that can emulate the behavior of neurons have garnered increasing interest across interdisciplinary fields due to their potential applications in neuromorphic computing, artificial intelligence and brain-machine interfaces. However, the optical modulation of nanofluidic ion transport for neuromorphic functions has been scarcely reported. Herein, inspired by biological systems that rely on ions as signal carriers for information perception and processing, we present a nanofluidic transistor based on a metal-organic framework membrane (MOFM) with optically modulated ion transport properties, which can mimic the functions of biological synapses. Through the dynamic modulation of synaptic weight, we successfully replicate intricate learning-experience behaviors and Pavlovian associate learning processes by employing sequential optical stimuli. Additionally, we demonstrate the application of the International Morse Code with the nanofluidic device using patterned optical pulse signals, showing its encoding and decoding capabilities in information processing process. This study would largely advance the development of nanofluidic neuromorphic devices for biomimetic iontronics integrated with sensing, memory and computing functions.

In Situ Cascade Catalytic Polymerization of Dopamine Based on Pt NPs/CoSAs@NC Nanoenzyme for Constructing Highly Sensitive Photocurrent-Polarity-Switching PEC Biosensing Platform

Nanozymes open up new avenues for amplifying signals in photoelectrochemical (PEC) biosensing, which are yet limited by the generated small-molecule signal reporters. Herein, a multifunctional nanoenzyme of Pt NPs/CoSAs@NC consisting of Co single atoms on N-doped porous carbon decorated with Pt nanoparticles is successfully synthesized for cascade catalytic polymerization of dopamine for constructing a highly sensitive photocurrent-polarity-switching PEC biosensing platform. Taking protein tyrosine phosphatase 1B (PTP1B) as a target model, Pt NPs/CoSAs@NC nanoenzymes are linked to magnetic microspheres via phosphorylated peptides. Upon dephosphorylation of PTP1B, Pt NPs/CoSAs@NC nanoenzymes with multiple enzyme-like activities, including peroxidase (POD)-like, catalase (CAT)-like, and oxidase (OXD)-like activities, are released and collected to induce the in situ cascade catalytic polymerization of dopamine on ZnCdS photoelectrode in the presence of H2O2. The generated polymer-molecule of polydopamine served as efficient signal reporter for simultaneously amplifying signal and switching photocurrent polarity, which not only improved the sensitivity but also enhanced the reliability. This biosensing platform is capable of sensitively quantifying PTP1B with ultralow detection limit (0.04 fM), wide linear range (0.1 fm-0.1 µm), and good applicability in complex biological samples. This work pioneers the utilization of nanozyme-based cascade catalytic polymerization strategy for improving sensitivity and reliability in biosensing technologies.

A triradical-containing trinuclear Pd(II) complex: spin-polarized electronic transmission, analog resistive switching and neuromorphic advancements

Neuromorphic computation has emerged as a potential alternative to subvert the von Neumann bottleneck issue in conventional computing. In this context, the development of resistive switching-based memristor devices mimicking various synaptic functionalities has engendered paramount attention. Here, we report a triradical-containing trinuclear Pd(II) cluster with a cyclohexane-like framework constituted by the Pd-Se coordination motif displaying facile memristor property with neuromorphic functionality as a thin-film device. The metal-ligand complex (complex 1) possessed an St = 1/2 ground state by experiencing a spin-frustrated-type magnetic coupling phenomenon amongst the three ligand-based organic radicals (SR = 1/2), coordinated to the Pd(II) ions. Three reversible one-electron reduction waves countered with a one-electron and one two-electron reversible oxidation waves were noticed in the cyclic voltammogram of the complex, confirming electrons accepting and releasing capacity of the complex at low potentials, i.e., within +0.2 V to -1.1 V. Employing the radical-containing complex 1 as the active thin-film sandwiched between two orthogonal electrodes, resistive switching based memristor property with biological synaptic actions were successfully emulated. Intriguingly, the artificial neural network (ANN) simulated efficient pattern recognition demonstrated using the recorded potentiation and depression curves from the device, which is a step ahead for the hardware realization of neuromorphic computing. The performance of the ANN on MNIST data with reduced image resolution has further been evaluated. Density functional theory (DFT)-based theoretical calculation predicted that the spin-polarized electronic transmission substantiated the memristive property in the neutral complex 1.

A Photoelectrochemical Retinomorphic Synapse

Reproducing human visual functions with artificial devices is a long-standing goal of the neuromorphic domain. However, emulating the chemical language communication of the visual system in fluids remains a grand challenge. Here, a "multi-color" hydrogel-based photoelectrochemical retinomorphic synapse is reported with unique chemical-ionic-electrical signaling in an aqueous electrolyte that enables, e.g., color perception and biomolecule-mediated synaptic plasticity. Based on the specific enzyme-catalyzed chromogenic reactions, three multifunctional colored hydrogels are developed, which can not only synergize with the Bi2S3 photogate to recognize the primary colors but also synergize with a given polymeric channel to promote the long-term memory of the system. A synaptic array is further constructed for sensing color images and biomolecule-coded information communication. Taking advantage of the versatile biochemistry, the biochemical-driven reversible photoelectric response of the cone cell is further mimicked. This work introduces rich chemical designs into retinomorphic devices, providing a perspective for replicating the human visual system in fluids.

Solution-Processed Ultralow Voltage Organic Transistors With Sharp Switching for Adaptive Visual Perception

Neuromorphic visual systems can emulate biological retinal systems to perceive visual information under different levels of illumination, making them have considerable potential for future intelligent vehicles and vision automation. However, the complex circuits and high operating voltages of conventional artificial vision systems present great challenges for device integration and power consumption. Here, bioinspired synaptic transistors based on organic single crystal phototransistors are reported, which exhibit excitation and inhibition synaptic plasticity with time-varying. By manipulating the charge dynamics of the trapping centers of organic crystal-electret vertical stacks, organic transistors can operate below 1 V with record high on/off ratios close to 108 and sharp switching with a subthreshold swing of 59.8 mV dec-1. Moreover, the approach offers visual adaptation with highly localized modulation and over 98.2% recognition accuracy under different illumination levels. These bioinspired visual adaptation transistors offer great potential for simplifying the circuitry of artificial vision systems and will contribute to the development of machine vision applications.

All-Photolithography Fabrication of Ion-Gated Flexible Organic Transistor Array for Multimode Neuromorphic Computing

Organic ion-gated transistors (OIGTs) demonstrate commendable performance for versatile neuromorphic systems. However, due to the fragility of organic materials to organic solvents, efficient and reliable all-photolithography methods for scalable manufacturing of high-density OIGT arrays with multimode neuromorphic functions are still missing, especially when all active layers are patterned in high-density. Here, a flexible high-density (9662 devices per cm2) OIGT array with high yield and minimal device-to-device variation is fabricated by a modified all-photolithography method. The unencapsulated flexible array can withstand 1000 times' bending at a radius of 1 mm, and 3 months' storage test in air, without obvious performance degradation. More interesting, the OIGTs can be configured between volatile and nonvolatile modes, suitable for constructing reservoir computing systems to achieve high accuracy in classifying handwritten digits with low training costs. This work proposes a promising design of organic and flexible electronics for affordable neuromorphic systems, encompassing both array and algorithm aspects.