Based on the achievement of synthesis of ZnO nanowires in mass production, ZnO nanowires gas sensors were fabricated with microelectromechanical system technology and ethanol-sensing characteristics were investigated. The sensor exhibited high sensitivity and fast response to ethanol gas at a work temperature of 300 °C. Our results demonstrate the potential application of ZnO nanowires for fabricating highly sensitive gas sensors.

Sensory neurons within skin form an interface between the external physical reality and the inner tactile perception. This interface enables sensory information to be organized identified, and interpreted through perceptual learning-the process whereby the sensing abilities improve through experience. Here, an artificial sensory neuron that can integrate and differentiate the spatiotemporal features of touched patterns for recognition is shown. The system comprises sensing, transmitting, and processing components that are parallel to those found in a sensory neuron. A resistive pressure sensor converts pressure stimuli into electric signals, which are transmitted to a synaptic transistor through interfacial ionic/electronic coupling via a soft ionic conductor. Furthermore, the recognition error rate can be dramatically decreased from 44% to 0.4% by integrating with the machine learning method. This work represents a step toward the design and use of neuromorphic electronic skin with artificial intelligence for robotics and prosthetics.

Neuromorphic chip refers to an unconventional computing architecture that is modelled on biological brains 1-3 . It is ideally suited for processing sensory data for intelligence computing, decision-making or context cognition. Despite rapid development, conventional artificial synapses 4-12 exhibit poor connection flexibility and require separate data acquisition circuitry, resulting in limited functionalities and significant hardware redundancy. Here we report a novel light-stimulated artificial synapse based on a graphene-nanotube hybrid phototransistor that can directly convert optical stimuli into a "neural image" for further neuronal analysis. Our optically-driven synapses involve multiple steps of plasticity mechanisms and importantly exhibit flexible tuning of both short-and long-term plasticity. Furthermore, our neuromorphic phototransistor can take multiple pre-synaptic light stimuli via wavelength-division multiplexing and allows advanced optical processing through charge-trap-mediated optical coupling. The capability of complex neuromorphic functionalities in a simple silicon-compatible device paves the way for novel neuromorphic computing architectures involving photonics 13 .Inspired by biological neural systems, neuromorphic chips are rapidly developed as a viable technological avenue in artificial intelligence. In stark contrast to traditional von Neumann computers, neuromorphic devices are dedicated to processing data and interacting with the world in humanlike ways 1, 11 . This manner renders neuromorphic chips extremely effective for solving complex tasks such as image recognition, multi-object detection and visual signal classification, which are beyond the capabilities of conventional semiconductor devices. In biological neural systems, synapses whose connectivity response depends on the history of stimuli previously experienced 14 , act as the most fundamental computing element. The changing of connectivity, also known as synaptic plasticity, is responsible for both short-and long-term memory behaviors, and the assembly of synapses produces functionally significant operations 15 . Stimulated by such biological systems, several artificial synaptic devices that may potentially meet the scalability requirements have been developed based on either transistors 5-11 or memorisistors [16][17][18][19] .Despite dramatic advancement, state-of-the-art synaptic devices with pure electronic components present two major limitations. First, in most conventional artificial synapses, the neuromorphic computing is isolated from the data acquisition sensors (ocular, olfactory or auditory stimuli) 20, 21 . The lack of neuromorphic sensing results in huge hardware redundancy and system latency. Furthermore, real neuronal system always involves multiple steps of plasticity mechanism that enable considerable flexibility in the modulation of the connectivity strength 14, 22,23 . For a given artificial synaptic pair, the coupling coefficient of these devices is always fixed, which is not adequate to emulate the comp...

After more than four billion years of evolution, nature has created a large number of fascinating living organisms, which show numerous peculiar structures and wonderful properties. Nature can provide sources of plentiful inspiration for scientists to create various materials and devices with special functions and uses. Since Messersmith proposed the fabrication of multifunctional coatings through mussel-inspired chemistry, this field has attracted considerable attention for its promising and exiciting applications. Polydopamine (PDA), an emerging soft matter, has been demonstrated to be a crucial component in mussel-inspired chemistry. In this review, the recent developments of PDA for mussel-inspired surface modification are summarized and discussed. The biomedical applications of PDA-based materials are also highlighted. We believe that this review can provide important and timely information regarding mussel-inspired chemistry and will be of great interest for scientists in the chemistry, materials, biology, medicine and interdisciplinary fields.