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Grafting organophosphonic acids (PAs) on metal oxides has shown to be a flexible technology to tune the surface properties of metal oxides for various applications. The solvents applied in the commonly used synthesis method have associated impeding effect on tailoring the resulting modification degree. In this work, an alternative solid-phase manual grinding method is proposed that (i) is straightforward, (ii) can achieve controllable and higher modification degree, and (iii) excludes the use of solvent during the synthesis. Specifically, propylphosphonic acid (3PA) was grafted onto titania by manual grinding, and different modification degrees were obtained by varying the duration of the post-synthetic thermal treatment. Importantly, the solid-phase method can achieve a modification degree that is 25.0% higher than the maximal modification degree reached by the liquid-phase method, while its atom utilization efficiency is 4.8 times (toluene-based) or 7.5 times (water-based) that of the liquid-phase method. [ABSTRACT FROM AUTHOR]

Performance breakthrough of energy‐storage electrodes under commercial‐level mass loading (≥10 mg cm−2) are highly pursued but restricted by sluggish mass/charge transfer rates and kinetically unfavorable reaction sites. In response, through electrochemical microenvironment reconstitution, these limitations are broken by engineering synergy between vacancies and oxyanions in the active matrix (Rec‐NiCoExch), which showcases a record‐level areal capacitance of 10.9 C cm−2 with a high mass loading of 20 mg cm−2 and a retention of 72% at 100‐fold current density. Such a design further endows the hybrid supercapacitor with an areal capacity of 20.9 C cm−2 and an energy density of 4.6 mWh cm−2, outperforming most of the benchmark results. Theoretical calculation reveals that in situ evolved oxyanions not only act as the effective adsorption sites but also secure the oxygen vacancies, enabling the potential synergy toward improved electronic conductivity and enhanced reactivity of Ni sites. As a proof‐of‐concept, the as‐assembled quasi‐solid‐state micro‐supercapacitor deliveries an ultrahigh energy density of 111.5 µWh cm−2 and presents great potential in intermittent energy storage by the solar panel‐supercapacitor‐LED system. This work offers insights for constructing commercial‐level energy‐storage electrodes by mastering surface/interface engineering for practical applications. [ABSTRACT FROM AUTHOR]

This research investigates the effects of various curing regimes, the incorporation of titanium slag, and the utilization of quartz sand on the strength properties and shrinkage behavior of ultra-high-performance concrete (UHPC). By using low-heat silicate cement to prepare UHPC, this study conducted standard curing and steam curing, and comprehensively analyzed the macro and micro performance of UHPC under different curing conditions. The findings indicate that the application of steam curing markedly enhances the mechanical attributes of UHPC while efficiently decreasing its drying shrinkage. In the comparative tests, we found that the compressive strength of concrete that had undergone 2 days of steam curing was 9.15% higher than that of concrete cured for 28 days under standard conditions. In addition, under the same curing conditions, titanium slag sand had higher mechanical properties than quartz sand. Under standard curing conditions, the 28-day compressive strength of UHPC using titaniferous slag aggregate was 12.64% higher than that of UHPC using standard sand. Through the data analysis of XRD, TG, and MIP, we found that the content of Ca(OH)2 in the hydration products after steam curing was reduced compared to the standard curing conditions, and the pore structure had been optimized. The UHPC prepared with titanium slag sand has greater advantages in mechanical properties and drying shrinkage, and has a smaller pore structure than the UHPC prepared with quartz sand. Moreover, the use of titanium slag sand offers ecological and economic benefits, making it a more sustainable and cost-effective option for high-performance construction applications. [ABSTRACT FROM AUTHOR]

Short-term electricity load forecasting provides a basis for day-ahead energy scheduling. To improve the accuracy of short-term electricity load forecasts and deeply explore the temporal characteristics of load sequences, a method is proposed to extract predictable components of load sequences based on the secretary bird optimization algorithm (SBOA)-optimized successive variational mode decomposition (SVMD). This method decomposes the electricity load sequence into multiple subsequences under different time series. The combined forecasting architecture of the temporal convolutional network (TCN) and the bidirectional long short-term memory network (BiLSTM) is introduced to mine the temporal characteristics of each load component, resulting in short-term load forecasting outcomes. A case study is conducted using the annual electricity load data for the year 2018 from a specific region in Belgium. The experimental results show that the mean absolute error (MAE) of the TCN–BiLSTM model is reduced by 47.8%, 32.8%, and 11.5%, respectively, compared to other models. The root mean square error (RMSE) is reduced by 42.9%, 39.2%, and 11.3%, respectively, and the average goodness of fit R2 is reduced by 9.81%. [ABSTRACT FROM AUTHOR]