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Chitosan, a natural polysaccharide, is nontoxic, lightweight and biodegradable, which exhibits a great potential for the emerging flexible and “green” electronic applications. Here, lightweight flexible aluminum-zinc-oxide (AZO) thin-film transistors (TFTs) are fabricated using chitosan biopolymer as self-supporting layer. This kind of biopolymer electrolyte can provide a strong electric-double-layer effect, which leads to a large capacitance with lower energy consumption. With the low-cost indium-free AZO deposited onto the chitosan film as the coplanar gate and source/channel/drain electrodes, the transistor shows a moderate on/off ratio of ∼104, a relatively ideal field-effect mobility of 0.3 cm2/Vs and a moderate sub-threshold swing of 0.65 V/dec. Moreover, logic “AND” function is realized in the flexible device with two coplanar gates as the input terminals. Such chitosan-gated flexible TFT devices can provide promising candidates for the next generation wearable and “green” electronics.

Brain‐inspired associative memory is meaningful for pattern recognitions and image/speech processing. Here, a ferroelectric synaptic transistor network is proposed that is capable of associative learning and one‐step recalling of a whole set of data from only partial information. The competition between an external field and the internal depolarization field governs the ferroelectric creep of domain walls and offers each single ferroelectric synapse a full and subfemtojoule‐energy‐cost Hebbian synaptic plasticity, including short‐term memory (STM) to long‐term memory (LTM) transition, and remarkably both spike‐timing‐dependent plasticity (STDP) and spike‐rate‐dependent plasticity (SRDP). Assisted by the third terminal to control the ferroelectric domain dynamics, self‐adaptive coupling between neurons is realized by updating synaptic weight concurrently. Pavlov's dog experiment and multiassociative memories are demonstrated in this ferroelectric synaptic transistor network. Such ferroelectric synaptic transistor network is available for building multilayer neural networks and provides new avenues for associative‐memory information processing.

The modification of C60 nano-interlayers on the organic field-effect transistors (OFETs) based on 2,7-diocty[1]benzothieno-[3,2-b]benzothiophene (C8-BTBT)/SiO2 was addressed at both the electronic structure and device level. It is observed that a band bending occurs in C8-BTBT layer with the insertion of C60, which induces a strong hole accumulation at the interface region, facilitating the formation of high concentration conducting channel when the interface is incorporated into OFETs. The strong acceptor C60 may cause charge transfer from the trap states in C8-BTBT, resulting in a field-effect operation with decreased threshold voltage. However, the increasing disorder in C8-BTBT induced by the C60 nano-interlayer may reduce the hole mobility at the C8-BTBT/SiO2 interface region and change the growth model of C8-BTBT. In addition, as confirmed by the transfer characteristic of the OFETs, the thin C60 insertion layer isn’t continuous enough to induce an ambipolar transport behavior despite its high mobility. The competition between the two opposite effects results in compromised performance in such OFETs. The device performance parameters deteriorate generally with increasing the C60 nano-interlayer thickness. So, it is inferred that the C60 interlayer alone cannot improve the performance of the C8-BTBT/SiO2-based OFETs without further optimization. Importantly, the device performance exhibits an abnormal improvement with a 6 nm C60 interlayer, which might be ascribed to a higher energy level shift of C8-BTBT caused by a quasi-continuous C60 film at this thickness.

The hardware implementation of biological synapses is very necessary for a new brain-like neuromorphic computation system. In recent years, optoelectronic synaptic devices have become the application platform for next generation neuromorphic system and artificial neural network. Here, a new kind of photoelectronic synaptic transistors are proposed using the Al-Zn-O (AZO) as coplanar gate and the laterally-coupled poly (vinyl alcohol) (PVA) electrolyte membrane as neurotransmitter. The key synaptic functions such as excitatory postsynaptic current (EPSC) and paired-pulse-facilitation (PPF) were successfully emulated. More importantly, by exposing an ultraviolet (UV) laser, the transformation of short-term memory (STM) to long-term memory (LTM) can be mimicked in our neuromorphic devices. Furthermore, an energy-band diagram is finally proposed for a better understanding of the underlying mechanism of LTM behavior. These results represent an important step toward the next-generation neural networks enabled by photo-electric hybrid nano-electronics, and point to the potential of more sophisticated neuromorphic computations.

Pain-perceptual nociceptors (PPN) are essential sensory neurons that recognize harmful stimuli and can empower the human body to react appropriately and perceive precisely unusual or dangerous conditions in the real world. Furthermore, the sensitization-regulated nociceptors (SRN) can greatly assist pain-sensitive human to reduce pain sensation by normalizing hyperexcitable central neural activity. Therefore, the implementation of PPNs and SRNs in hardware using emerging nanoscale devices can greatly improve the efficiency of bionic medical machines by giving them different sensitivities to external stimuli according to different purposes. However, current most-normal organic/oxide transistors face a great challenge due to channel scaling, especially in the sub-10 nm channel technology. Here, a sub-10 nm indium-tin-oxide transistor with an ultrashort vertical channel as low as ≈3 nm, using sodium alginate bio-polymer electrolyte as gate dielectric, is demonstrated. This device can emulate important characteristics of PPN such as pain threshold, memory of prior injury, and pain sensitization/desensitization. Furthermore, the most intriguing character of SRN can be achieved by tuning the channel thickness. The proposed device can open new avenues for the fascinating applications of next-generation neuromorphic brain-like systems, such as bio-inspired electronic skins and humanoid robots.