Developing multifunctional artificial sensory systems is an important task for constructing future artificial neural networks. A system with multisignal output capability is highly required by the rising demand for high-throughput data processing in the Internet of Things (IoT) society. Here, a novel dual-output artificial tactile sensing (DOATS) system with parallel output of photoelectric signals was proposed. Because of the ionic−electronic coupling mechanism in lightemitting synaptic (LES) devices in the DOATS system, modulating electric current and light emission can coexist through ion accumulation and electron−hole recombination. As a result, the DOATS system can realize the simulation of human tactile information, and the recognition of 16 kinds of fabrics was demonstrated with an accuracy rate of 94.1%. A photoelectric hybrid artificial neural network was proposed, which achieved efficient and accurate multitask operation. The DOATS system proposed in this work is promising for implementing photoelectric hybrid neural network and promoting the development of interactive artificial intelligence.
Organic phototransistors with high
sensitivity and responsivity
to light irradiance have great potential applications in national
defense, meteorology, industrial manufacturing, and medical security.
However, undesired dark current and photoresponsivity limit their
practical applications. Here, a novel vertical organic phototransistor
combined with ferroelectric materials is developed. The device structure
has nanometer channel length, which can effectively separate photogenerated
carriers and reduce the probability of carrier recombination and defect
scattering, thus improving the device performance of phototransistors.
Moreover, by inserting the poly(vinylidene fluoride-co-trifluoroethylene) (P(VDF-TrFE)) ferroelectric layer, the Schottky
barrier at the interface between the semiconductor and source can
be adjusted by the polarization of the external electric field, which
can effectively reduce the dark current of the phototransistor to
further improve the device performance. Therefore, our phototransistors
exhibit a high photoresponsivity of more than 5.7 × 105A/W, an outstanding detectivity of 1.15 × 1018 Jones,
and an excellent photosensitivity of 5 × 107 under
760 nm light illumination, which are better than those of conventional
lateral organic phototransistors. This work provides a new approach
for the development of high-performance phototransistors, which opens
a new pathway for organic phototransistors in practical application.
Artificial synaptic devices serve as the cornerstone of artificial neural networks, much research is devoted to the development of artificial synaptic devices with multiple functions for the future construction of large‐scale artificial neural networks. By adding optical signal output to traditional synaptic devices, the strategy of transforming the devices from a single electrical interconnection to an optoelectronic interconnection is considered to be an effective way to solve the problem of wire cross‐talk in large‐scale artificial neural networks. Herein, a quantum‐dot light‐emitting synaptic transistor capable of dual output of optoelectronic signals by integrating the functions of light‐emitting transistor and synaptic transistor into a single device is demonstrated for the first time. Based on the novel working mechanism and the excellent optoelectronic properties of quantum dots, the device can exhibit dual responses of electrical and optical signals under electrical pulse stimulation. More importantly, some key synaptic functions such as excitatory postsynaptic current, paired pulse facilitation, high‐pass filtering properties, and the transition from short‐term memory to long‐term memory are successfully simulated in the device. In addition, classical conditioned reflex experiments as well as the processes of learning and forgetting are optically and electrically simulated. This work provides a feasible way to realize multivariate artificial neural networks with high integration and optoelectronic interconnection to transmit information, showing great potential in the development of neuromorphic computing in the future.
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