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Electrooxidation of the biomass derivative 5-hydroxymethylfurfural (HMF) is a highly promising approach for attaining versatile value-added chemicals (e.g., 2,5-furandicarboxylic acid, FDCA). Ni-based sulfides are promising electrocatalysts for HMF electrooxidation reaction (HMFOR). However, the HMFOR activity of Ni-based catalysts is far from satisfactory due to the unfavorable adsorption of HMF and OH*. Herein, we propose controlled W doping to effectively modify the electronic configuration of nanostructured Ni3S2 to manipulate adsorption of HMF and OH*, for efficiently converting HMF into FDCA. Experimental and theoretical calculations indicate the incorporation of high-valence W results in the upshift of d-band center of Ni3S2, which facilitates the adsorption and dissociation of water to produce more OH*. Meanwhile, the high-valence W has strong electron-withdrawing ability and attracts electrons from Ni, leading to the elevated Ni valence, which is beneficial to optimizing the adsorption energy of HMF. Both concurrently contribute to the superb HMFOR performance. As a result, W20-Ni3S2@NF with optimal W dopant exhibits a low driving potential (1.34 V vs. RHE at 10 mA cm−2), accompanying with the 100% HMF conversion, 99.2% FDCA selectivity, and 97.3% Faraday efficiency. This work provides a design principle for HMFOR electrocatalysts by modulating the adsorption behaviors of HMF and OH* via rational electronic structure engineering. [ABSTRACT FROM AUTHOR]

As one of the supervised tensor learning methods, the support tensor machine (STM) for tensorial data classification is receiving increasing attention in machine learning and related applications, including remote sensing imaging, video processing, fault diagnosis, etc. Existing STM approaches lack consideration for support tensors in terms of data reduction. To address this deficiency, we built a novel sparse STM model to control the number of support tensors in the binary classification of tensorial data. The sparsity is imposed on the dual variables in the context of the feature space, which facilitates the nonlinear classification with kernel tricks, such as the widely used Gaussian RBF kernel. To alleviate the local risk associated with the constant width in the tensor Gaussian RBF kernel, we propose a two-stage classification approach; in the second stage, we advocate for a scaling strategy on the kernel function in a data-dependent way, using the information of the support tensors obtained from the first stage. The essential optimization models in both stages share the same type, which is non-convex and discontinuous, due to the sparsity constraint. To resolve the computational challenge, a subspace Newton method is tailored for the sparsity-constrained optimization for effective computation with local convergence. Numerical experiments were conducted on real datasets, and the numerical results demonstrate the effectiveness of our proposed two-stage sparse STM approach in terms of classification accuracy, compared with the state-of-the-art binary classification approaches. [ABSTRACT FROM AUTHOR]

The step edges and intrinsic atomic structure of single-crystal substrate play a critical role in determining the growth pathways of transition metal dichalcogenide (TMD) grains, particularly whether the TMDs will grow into wafer-scale single-crystal or anisotropic nanoribbons. Hereby, we investigate the growth behaviours of the MoS2 nanograins on (0001) and (1 1 ¯ 02 ) sapphire substrates. On one hand, the step edges formed on the (0001) surface after thermal treatment are found to promote the macroscopic aggregation of MoS2 nanograins and to form unidirectional large triangular islands along with the < 11 2 ¯ 0 > steps in the annealing process, while on the pristine (0001) surface, the MoS2 nanograins grow into a random network-like pattern. Moreover, oxygen treatment on the substrate can further enhance the growth of MoS2 nanograins. Transmission electron microscopy and fast Fourier transform patterns reveal that the substrate could modulate the orientation of MoS2 nanograins during their growing process. On the other hand, the MoS2 nanograins on the (1 1 ¯ 02 ) surface could self-assemble into one-dimensional nanoribbons due to the strong structural anisotropy of the substrate. In addition, the ratio of Raman intensities for peaks that correspond to the E 2 g 1 and A1g phonon modes shows a linear relationship with the grain size due to the change of the "phonon confinement". Moreover, new peaks located at 226 and 280 cm−1 can be observed in the off-resonant and resonant Raman spectra for the MoS2 nanograin samples, respectively, which can be attributed to the scatterings from the edges of as-fabricated MoS2 nanostructures. [ABSTRACT FROM AUTHOR]

Dual-layer and tri-layer broadband antireflective (AR) films with excellent transmittance were successfully fabricated using base-/acid-catalyzed mixed sols and propylene oxide (PO) modified silica sols. The sols and films were characterized by scanning electron microscope (SEM), Fourier transform infrared spectroscopy (FTIR), nuclear magnetic resonance (NMR), transmission electron microscope (TEM), and scanning transmission electron microscope (STEM). FTIR and TEM results suggest that the PO molecules were covalently bonded to the silica particles and the bridge structure existing in PO modified silica sol is responsible for the low density of the top layer. The density ratio between different layers was measured by cross-sectional STEM, and the results are 1.69:1 and 2.1:1.7:1 from bottom-layer to top-layer for dual-layer and tri-layer films, respectively. The dual-layer film demonstrates good stability with 99.8% at the central wavelength of 351 nm and nearly 99.5% at the central wavelength of 1053 nm in laser system, and for the tri-layer AR film, the maximum transmittance reached nearly 100% at both the central wavelengths of 527 and 1053 nm. [ABSTRACT FROM AUTHOR]

Metallic 1T-phase MoS 2 exhibits superior hydrogen evolution reaction (HER) performance than natural 2H-phase MoS 2 owing to its higher electrical conductivity and abundance of active sites. However, the reported 1T-MoS 2 catalysts usually suffer from extreme instability, which results in quick phase transformation at ambient conditions. Herein, we present a facile approach to engineer the phase of MoS 2 by introducing intercalated hydrazine. Interestingly, the as-synthesized 1T-dominant MoS 2 sample demonstrates excellent ambient stability without noticeable degradation for 3 months. Additionally, the 1T-dominant MoS 2 exhibits superior electrical conductivity (∼700 times higher than that of 2H-MoS 2 ) and improved electrochemical catalytic performance (current density ∼12 times larger than that of 2H-MoS 2 at an overpotential of 300 mV vs the reversible hydrogen electrode, RHE). Through experimental characterizations and density functional theory (DFT) calculation, we conclude that the stabilization of the metallic phase could be attributed to the electron donation from hydrazine molecules to the adjacent Mo atoms. The phase control strategy in this work provides a guideline to develop other highly efficient and stable two-dimensional (2D) electrocatalysts.