4,218 publications from this institution
For the enhancement of triboelectric nanogenerator’s output performance, the method of using self-assembled monolayers to functionalize surfaces is introduced.
Abstract The emulation of synaptic plasticity to achieve sophisticated cognitive functions and adaptive behaviors is critical to the evolution of neuromorphic computation and artificial intelligence. More feasible plastic strategies (e.g., mechanoplasticity) are urgent to achieve comparable, versatile, and active cognitive complexity in neuromorphic systems. Here, a versatile mechanoplastic artificial synapse based on tribotronic floating‐gate MoS 2 synaptic transistors is proposed. Mechanical displacement can induce triboelectric potential coupling to the floating‐gate synaptic transistor, trigger a postsynaptic current signal, and modulate the synaptic weights, which realizes the synaptic mechanoplasticity in an active and interactive way. Typical synaptic plasticity behaviors including potentiation/inhibition and paired pulse facilitation/depression are successfully imitated. Assistant with the charge trapping by floating gate, the artificial synapse can realize mechanical displacement derived short‐term and long‐term plasticity simultaneously. A facile artificial neural network is also constructed to demonstrate an adding synaptic weight and neuromorphic logic switching (AND, OR) by mechanoplasticity without building complex complementary metal oxide semiconductor circuits. The proposed mechanoplastic artificial synapse offers a favorable candidate for the construction of mechanical behavior derived neuromorphic devices to overcome the von Neumann bottleneck and perform advanced synaptic behaviors.
We report the synthesis and characterization of nanowire−nanoribbon junction arrays of ZnO, which were grown by thermal evaporation of the mixture of ZnO and SnO2 powders at 1300 °C through a vapor−liquid−solid process. The Sn particles produced by the reduction of SnO2 act as the catalyst; the structure is formed due to a fast growth of ZnO nanowires along [0001] and the subsequent "epitaxial" radial growth of the ZnO nanoribbons along the six 〈011̄0〉 directions around the nanowire. The "liana" shape nanostructure could be a candidate for fabricating ultrahigh sensitive sensors.
Abstract Nanoparticles and the physical and chemical functional specificity and selectivity they possess, suggest them as ideal building blocks for two- and three-dimensional cluster self-assembled superlattice structures, in which the particles behave as well-defined molecular matter and they are arranged with long-range translation and even orientation order [1]. Self-assembled arrays involve self-organization into monolayers, thin films, and superlattices of size-selected nanoclusters encapsulated in protective compact organic coating. The macroscopic properties of the nanocrystal superlattice (NCS) are determined not only by the properties of each individual particle but by the coupling/interaction between nanocrystals interconnected and isolated by a monolayer of thin organic molecules. Periodic packing of nanocrystals is different from the 3-D packing of atoms. First, to an excellent approximation atoms are spherical, while nanoparticles can be faceted polyhedra, thus, the 3-D packing of particles can be critically affected by their shapes and sizes.
Abstract Dynamical calculations have shown that the surface resonance wave is confined to the surface top few layers in the geometry of reflection high-energy electron diffraction (RHEED); it takes the dominant role in the resonance reflections of electrons from surfaces. The Goose–Hanchen effect is valid for describing the scattering of electrons in RHEED. The interrupting effect on the resonance wave of a surface step is shown to be sensitive to the step height. This effect is demonstrated as a new method of determining step heights as well as their distribution on surfaces.
