446 research outputs found

    In situ investigations of the phase change behaviour of tungsten oxide nanostructures

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    This study appraises the use of in-situ diffraction and spectroscopy techniques, complemented with ex-situ electron microscopy analyses, to investigate the geometry and phase change behaviour of bundled ultrathin W18O49 nanowires and WO3 nanoparticles. Our in-situ X-ray diffraction (XRD) results have shown that the phase transition of WO3 nanoparticles occurs in sequence as the temperature increases, from monoclinic (room temperature) → orthorhombic (350 ºC) → tetragonal (800 °C), akin to bulk WO3; however, W18O49 nanowires remain stable as the monoclinic phase up to 500 °C, after which complete oxidation to WO3 and transformation to the orthorhombic β-phase at 550 °C is observed. The in-situ Raman spectroscopy investigations have shown that as the temperature increases, the Raman peaks downshift toward lower wavenumbers in both structures, which can be attributed to the increased bond lengths in the lattice. We have also demonstrated that the Raman shift at 187.6 cm-1 can be used as a fingerprint band for the phase transition from the γ- to the β-phase of the WO3 nanoparticle. Furthermore, WO3 nanoparticles exhibit the γ- to β-phase conversion at 275 °C, which is about 75 °C lower than the relaxation temperature of 350 °C for the monoclinic γ-W18O49 nanowires. We propose that this fundamental phase transition understanding can offer important guidance for the design and development of WOx-based nanodevices by defining their allowed operating conditions

    A Unified Weight Initialization Paradigm for Tensorial Convolutional Neural Networks

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    Tensorial Convolutional Neural Networks (TCNNs) have attracted much research attention for their power in reducing model parameters or enhancing the generalization ability. However, exploration of TCNNs is hindered even from weight initialization methods. To be specific, general initialization methods, such as Xavier or Kaiming initialization, usually fail to generate appropriate weights for TCNNs. Meanwhile, although there are ad-hoc approaches for specific architectures (e.g., Tensor Ring Nets), they are not applicable to TCNNs with other tensor decomposition methods (e.g., CP or Tucker decomposition). To address this problem, we propose a universal weight initialization paradigm, which generalizes Xavier and Kaiming methods and can be widely applicable to arbitrary TCNNs. Specifically, we first present the Reproducing Transformation to convert the backward process in TCNNs to an equivalent convolution process. Then, based on the convolution operators in the forward and backward processes, we build a unified paradigm to control the variance of features and gradients in TCNNs. Thus, we can derive fan-in and fan-out initialization for various TCNNs. We demonstrate that our paradigm can stabilize the training of TCNNs, leading to faster convergence and better results.Comment: Accepted in ICML 202

    A generic method to synthesise graphitic carbon coated nanoparticles in large scale and their derivative polymer nanocomposites

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    A versatile Rotary Chemical Vapour Deposition (RCVD) technique for the in-situ synthesis of large scale carbon-coated non-magnetic metal oxide nanoparticles (NPs) is presented, and a controllable coating thickness varying between 1–5 nm has been achieved. The technique has significantly up-scaled the traditional chemical vapour deposition (CVD) production for NPs from mg level to 10 s of grams per batch, with the potential for continuous manufacturing. The resulting smooth and uniform C-coatings sheathing the inner core metal oxide NPs are made of well-crystallised graphitic layers, as confirmed by electron microscopy imaging, electron dispersive spectrum elemental line scan, X-ray powder diffractions and Raman spectroscopy. Using nylon 12 as an example matrix, we further demonstrate that the inclusion of C-coated composite NPs into the matrix improves the thermal conductivity, from 0.205 W∙m−1∙K−1 for neat nylon 12 to 0.305 W∙m−1∙K−1 for a 4 wt% C-coated ZnO composite, in addition to a 27% improvement in tensile strength at 2 wt% addition
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