Ling-an Kong

Multi-gate organic neuron transistors for spatiotemporal information processing

Due to similar transmission characteristics of biological synaptic activities, neuromorphic behaviors simulated by organic electrochemical transistors (OECTs) is of great interest. In this letter, the fabrication and performance of multi-gate poly(3-hexylthiophene) (P3HT) OECTs with ion-gel gating are reported. The neuromorphic behaviors, such as dendrite correlated excitatory postsynaptic current (EPSC), paired pulse facilitation, and modulation, were simulated in the OECTs. These behaviors were observed to depend on the degree of temporal correlation and distance between the in-plane-gate and the channel. More importantly, by using dendritic integration from two different gates, spatiotemporally correlated outputs were also emulated. The spatial orientations of the input pulse are defined, and changing the orientation will result in a change in the EPSC amplitude. Our results provide a way to construct spatiotemporally neural network based on multi-gate OECTs.

Artificial synapses based on biopolymer electrolyte-coupled SnO2 nanowire transistors

The fabrication of biologically inspired solid-state devices has attracted tremendous attention for decades, and the hardware implementation of artificial synapses using individual ionic/electronic hybrid devices is very important for neuromorphic applications. Herein, electric double-layer (EDL) synaptic transistors coupled by proton neurotransmitters with a multiple in-plane gate structure were successfully fabricated using SnO2 nanowires. Not only the important synaptic functions were mimicked in these devices, but also the synaptic behaviors can be modulated over a dynamic range via the multi-terminal regulation of synaptic inputs. Furthermore, a light source was used to illuminate the SnO2 nanowire synaptic transistors, which were used as the light-modulating terminals. The observed neuromorphic functions were also dynamically modulated via the light density. These excellent nanoscale synaptic transistors may find significant applications in synaptic electronics.

Deep-ultraviolet-triggered neuromorphic functions in In-Zn-O phototransistors

In recent years, photoelectronic synaptic devices have emerged as a platform for use in next-generation neuromorphic systems and artificial neural networks (ANNs). In this paper, we report an artificial photoelectronic synapse based on an ion-gel gated In-Zn-O phototransistor. The phototransistor is stimulated by a deep ultraviolet light spike, and it can process and store information in the form of an electric current. Key biological synaptic behaviors were investigated, including excitatory post-synaptic current and paired pulse facilitation. Furthermore, channel conduction can be changed by photoelectric synergy in order to simulate potentiation and depression behavior in the human brain. Most importantly, four forms of spike-timing dependent plasticity learning principles were realized by a photoelectric hybrid stimulation. Our studies provide a path towards hybrid photoelectronic ANNs capable of performing solar-blind sensitive tasks.In recent years, photoelectronic synaptic devices have emerged as a platform for use in next-generation neuromorphic systems and artificial neural networks (ANNs). In this paper, we report an artificial photoelectronic synapse based on an ion-gel gated In-Zn-O phototransistor. The phototransistor is stimulated by a deep ultraviolet light spike, and it can process and store information in the form of an electric current. Key biological synaptic behaviors were investigated, including excitatory post-synaptic current and paired pulse facilitation. Furthermore, channel conduction can be changed by photoelectric synergy in order to simulate potentiation and depression behavior in the human brain. Most importantly, four forms of spike-timing dependent plasticity learning principles were realized by a photoelectric hybrid stimulation. Our studies provide a path towards hybrid photoelectronic ANNs capable of performing solar-blind sensitive tasks.

Flexible Neuromorphic Architectures Based on Self-Supported Multiterminal Organic Transistors

Because of the fast expansion of artificial intelligence, development and applications of neuromorphic systems attract extensive interest. In this paper, a highly interconnected neuromorphic architecture (HINA) based on flexible self-supported multiterminal organic transistors is proposed. Au electrodes, poly(3-hexylthiophene) active channels, and ion-conducting membranes were combined to fabricate organic neuromorphic devices. Especially, freestanding ion-conducting membranes were used as gate dielectrics as well as support substrates. Basic neuromorphic behavior and four forms of spike-timing-dependent plasticity were emulated. The fabricated neuromorphic device showed excellent electrical stability and mechanical flexibility after 1000 bends. Most importantly, the device structure is interconnected in a way similar to the neural architecture of the human brain and realizes not only the structure of the multigate but also characteristics of the global gate. Dynamic processes of memorizing and forgetting were incorporated into the global gate matrix simulation. Pavlovs learning rule was also simulated by taking advantage of the multigate array. Realization of HINAs would open a new path for flexible and sophisticated neural networks.