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In this article, a novel Mo(VI)-imprinted adsorbent based on brown algae (Mo-PVA-SA-I) was synthesized through an ion-imprinting technique in combination with surface imprinting and polymer crossli...

A novel preparative approach for promising cathode materials for capacitive deionization (CDI) is proposed. Several 3D Na4Ti9O20/N-doped carbon composite materials (3D NTO/N-C-x, x represents the hydrothermal reaction time) with high surface area are synthesized by pyrolysis of Ti-based metal–organic frameworks (Ti-MOFs) and a subsequent hydrothermal treatment strategy. Notably, the intrinsic interfacial interaction of the optimized 3D NTO/N-C-2 facilitates the synergy of the internal driving field and condensed phase interface, which is greatly beneficial to obtain more active sites for sodium ion storage and improved storage capacity (249 F g−1 at 1 A g−1). Furthermore, an all-faradaic-type 3D NTO/N-C-2//Ag@rGO full desalination cell shows high salt adsorption capacity (59.3 mg g−1) and stable cycling desalination ability (95% capacity retention rate over 20 cycles at 1.4 V). In addition, the mechanism of the zwitterion removal/release of the desalination cell is thoroughly investigated by electrochemical measurement. This work not only provides a reasonable strategy to establish cathode materials for CDI, but also may trigger the rapid development of Ti-based electrode materials in many frontier fields.

The nonlinear characteristics of wind power series and random fluctuation characteristics of wind resources have a harmful effect on stability of wind power prediction. This paper proposes a novel hybrid wind power short-term prediction model for improving precision and stability of wind power prediction. Firstly, the non-stationary wind power time series is decomposed by complete ensemble empirical mode decomposition - Lempel-Ziv complexity (CEEMD-LZC). Secondly, local linear embedding (LLE) is used to reduce the dimension of meteorological data with maintaining the essential structure of meteorological data. The integrated meteorological data predigested by LLE are treated as input of the prediction model. Finally, ant lion optimization (ALO) is utilized to optimize the weights and biases of extreme learning machine (ELM) network nodes to improve ELM prediction performance. The results of case studies show that the proposed model has a good forecasting effect and is more advantageous in 48h-ahead wind power forecasting.

Rhenium (Re) is a rare element in the earth’s crust and has wide range applications in industry, its effective secondary enrichment plays a crucial role in environment and energy field. On the basis of economy and resource sustainability, we report a facile and rapid process to prepare chitosan (CS) functionalized mesoporous silica composites for recovery of Re by a one-pot microwave-assisted synthesis method. Schiff base groups inside the nanostructure were functioned as active sites for Re adsorption. A series of characterization analysis indicated that the optimal adsorbent (SS-KIT-6-M4-15-CS3) possessed mesoporous channel and retained the ordered morphology of mesoporous silica skeleton. The maximum adsorption capacity for Re(Ⅶ) of the as-prepared adsorbent reached 261.81 mg·g−1 at pH 4, higher than that of other reported adsorbents. The SS-KIT-6-M4-15-CS3 showed excellent regeneration performance after eight adsorption–desorption cycles, and exhibited high selectivity for Re(Ⅶ). The prominent adsorption performance was attributed to the chelation between C = N and ReO4¯ according to FT-IR and XPS analysis. These findings showed encouraging potentiality of the adsorbent for recovering of Re(Ⅶ) in real industrial effluents.

A series of xwt%Al-SBA-15 catalysts prepared by modified wetness impregnation was investigated for γ-valerolactone (GVL) decarboxylation to butene. It was found that the impregnation of Al species not only remained the ordered mesoporous structure of parent SBA-15, but also created large amounts of Bronsted and Lewis acid sites on the surface of catalyst. The considerable amount of solid acid sites and the suitable Bronsted/Lewis acid ratio endowed 2.23 wt%Al-SBA-15 catalyst an excellent catalytic performance. Under the optimized conditions, the GVL conversion and butene yield can reach 99.8% and 96.6% at 320 °C, respectively. Mechanism studies indicated that the decarboxylation of γ-protonated PEA controlled speed of the whole reaction. Moreover, the catalytic activity of regenerated 2.23 wt%Al-SBA-15 catalyst was satisfactory after eight cycle tests, and the butene yield could still reach 92.2%.