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...

Graphene has emerged as a promising material for photonic applications fuelled by its superior electronic and optical properties. However, the photoresponsivity is limited by the low absorption cross-section and ultrafast recombination rates of photoexcited carriers. Here we demonstrate a photoconductive gain of ∼105 electrons per photon in a carbon nanotube–graphene hybrid due to efficient photocarriers generation and transport within the nanostructure. A broadband photodetector (covering 400–1,550 nm) based on such hybrid films is fabricated with a high photoresponsivity of >100 A W−1 and a fast response time of ∼100 μs. The combination of ultra-broad bandwidth, high responsivities and fast operating speeds affords new opportunities for facile and scalable fabrication of all-carbon optoelectronic devices.

Epitaxial bcc Fe has been grown on GaAs͑100͒-(4ϫ6) at room temperature and studied with in situ magneto-optical Kerr effect ͑MOKE͒, low-energy electron diffraction, and alternating gradient field magnetometry ͑AGFM͒. The magnetic properties at room temperature were found to proceed via three phases; a nonmagnetic phase for the first three and a half monolayers, a short-range-ordered superparamagnetic phase, and a ferromagnetic phase above about five monolayers. The thickness dependencies of the coercivity and MOKE intensity further suggested that the ferromagnetic phase is subdivided into three distinct regimes with different magnetic properties. A combination of the in situ MOKE and ex situ AGFM measurements shows that the entire Fe film is ferromagnetic with a bulklike moment after the onset of the ferromagnetism, in contrast with previous studies, in which magnetic dead layers or half-magnetization phases due to the intermixing of Fe and As were proposed. The results show that it is the growth morphology of the ultrathin films, rather than the diffusion of As, that plays the dominant role in determining the magnetic properties in this system.

ZrSiS materials show unsaturated magnetoresistance until a magnetic field of 53 T with a butterfly‐shaped angular dependence. Intense Shubnikov‐de Haas oscillations resolve a bulk Dirac cone with a nontrivial Berry phase. Combined with angle‐resolved photoemission spectroscopy and theoretical calculations, ZrSiS is proved to be a Dirac material with both surface and bulk Dirac bands.