Polyaniline encapsulated Ti-MOF/CoS for efficient photocatalytic hydrogen evolution

We report the study of conductive polyaniline (PANI) chain embedded Ti-MOF functionalized with CoS as a cocatalyst for hydrogen evolution reaction (HER) application. The post synthetically modified hybrid photocatalyst PANI/Ti-MOF/CoS greatly influences the redox and e^? ? h⁺ separation process and exhibits an impressive rate of HER (～1322 μmol h^?1g^?1), suppressing the pristine Ti-MOF (～62 μmol h^?1g^?1) with apparent quantum yield (AQY) of ～3.2 and transient current response of ～46.4 μA cm^?2. In this system, Ti-MOF provides the circulation of Ti³⁺ and Ti⁴⁺ to the reaction of photocatalytic H₂ generation, where the additional PANI and CoS amended the performance of H₂ production through electron enrichment and thereby improving the stability and integrity of Ti-MOF. The Electrochemical studies demonstrated increased photocurrent by interweaving Ti-MOF crystal with PANI through cation-π interaction thereby enhancing interface connection and then promoting electron transfers. The charge dynamics revealed the initial charge transfer from photoexcited PANI to encapsulated MOF framework to boost the photocatalytic performance of the system. Further, the electron movement at the Ti-MOF/CoS interface is investigated through work function and electrochemical potential of electrons (Fermi level). DFT results demonstrate the importance of CoS in improving the photocatalytic performance of hybrid Ti-MOF catalyst, which leads to superior catalytic behaviour. These results establish that the encapsulation of catalytic active sites inside MOFs with desirable energy band gaps would be an ideal choice for the production of solar fuels.     

基于VMD和BSA-KELM的高陡边坡位移预测模型研究

边坡位移的时间序列曲线存在复杂的非线性特性,传统的预测模型精度不足以满足预测要求。为此提出了基于变分模态分解的鸟群优化-核极限学习机的预测模型,并用于河北省某水泥厂的边坡位移预测。该方法首先采用VMD把边坡位移序列分解为一系列的有限带宽的子序列,再对各子序列分别采用相空间重构并用核极限学习机预测,采用鸟群算法优化相空间重构的嵌入维度和KELM中惩罚系数和核参数三个数值,以取得最优预测模型。最后将各个子序列预测值叠加,得到边坡位移的最终预测值。结果表明：和KELM、BSA-KELM、EEMD-BSA-KELM模型相比,基于VMD的BSA-KELM预测精度更高,为边坡位移的预测提供一种有效的方法。     

IRS辅助的SWIPT系统中基于能效优先的波束成形设计与优化

以智能反射面(intelligent reflecting surface,IRS)辅助的无线携能通信(simultaneous wireless information and power transfer,SWIPT)系统为背景,研究了该系统中基于能效优先的多天线发送端有源波束成形与IRS无源波束成形联合设计与优化方法。以最大化接收端的最小能效为优化目标,构造在发送端功率、接收端能量阈值、IRS相移等多约束下的非线性优化问题,用交替方向乘子法(alternating direction method of multipliers,ADMM)求解。采用Dinkelbach算法转化目标函数,通过奇异值分解(singular value decomposition,SVD)和半定松弛(semi-definite relaxation,SDR)得到发送端有源波束成形向量。采用SDR得到IRS相移矩阵与反射波束成形向量。结果表明,该系统显著降低了系统能量收集(energy harvesting,EH)接收端的能量阈值。当系统总电路功耗为?15 dBm时,所提方案的用户能效为300 KB/J。当IRS反射阵源数与发送天线数均为最大值时,系统可达最大能效。     

Designing optical glasses by machine learning coupled with a genetic algorithm

Engineering new glass compositions have experienced a sturdy tendency to move forward from (educated) trial-and-error to data- and simulation-driven strategies. In this work, we developed a computer program that combines data-driven predictive models (in this case, neural networks) with a genetic algorithm to design glass compositions with desired combinations of properties. First, we induced predictive models for the glass transition temperature (T_g) using a dataset of 45,302 compositions with 39 different chemical elements, and for the refractive index (n_d) using a dataset of 41,225 compositions with 38 different chemical elements. Then, we searched for relevant glass compositions using a genetic algorithm informed by a design trend of glasses having high n_d (1.7 or more) and low T_g (500 °C or less). Two candidate compositions suggested by the combined algorithms were selected and produced in the laboratory. These compositions are significantly different from those in the datasets used to induce the predictive models, showing that the used method is indeed capable of exploration. Both glasses met the constraints of the work, which supports the proposed framework. Therefore, this new tool can be immediately used for accelerating the design of new glasses. These results are a stepping stone in the pathway of machine learning-guided design of novel glasses.     

Nanoraspberry-like palladium/spongy nickel oxide for electrooxidation of five light fuels

The spongy nickel oxide (SNO) was synthesized the solution combustion method. The SNO was selected as a promoter to boost the catalytic activity of nanoraspberry-like palladium (NRPd) toward electrooxidation of five light fuels (LFs): methanol, ethanol, formaldehyde, formic acid, and ethylene glycol. The X-ray powder diffraction, Fourier-transform infrared spectroscopy (FT-IR), scanning electron microscopy, and field emission scanning electron microscope techniques were used for the materials characterization. In comparison with nonpromoted Pd, the NRPd-SNO electrocatalyst shown an excellent efficiency in parameters like the electrochemical active surface area and anti-CO poisoning behavior. The turnover data and the parameters, including reaction order, activation energy, and the coefficients of electron transfer and diffusion, were evaluated for the each process of LFs electrooxidation. The outcome for NRPd-SNO activity toward LFs electrooxidation was compared to some reported electrodes. The SNO increases the removal of intermediates created in the oxidation of LFs that can poison the surface of palladium catalyst. This is due to the presence of the lattice oxygens in SNO structure and Ni switching between its high and low valances. The compatibility of the adsorption process of LFs on the surface of the NRPd-SNO catalyst with different isotherms was determined by studying the Tafel polarization and calculating the surface coverage.     

Surface Reconstruction Engineering with Synergistic Effect of Mixed-Salt Passivation Treatment toward Efficient and Stable Perovskite Solar Cells

Surface passivation treatment is a widely used strategy to resolve trap-mediated nonradiative recombination toward high-efficiency metal-halide perovskite photovoltaics. However, a lack of passivation with mixture treatment has been investigated, as well as an in-depth understanding of its passivation mechanism. Here, a systematic study on a mixed-salt passivation strategy of formamidinium bromide (FABr) coupled with different F-substituted alkyl lengths of ammonium iodide is demonstrated. It is obtained better device performance with decreasing chain length of the F-substituted alkyl ammonium iodide in the presence of FABr. Moreover, they unraveled a synergistic passivation mechanism of the mixed-salt treatment through surface reconstruction engineering, where FABr dominates the reformation of the perovskite surface via reacting with the excess PbI₂. Meanwhile, ammonium iodide passivates the perovskite grain boundaries both on the surface and top perovskite bulk through penetration. This synergistic passivation engineer results in a high-quality perovskite surface with fewer defects and suppressed ion migration, leading to a champion efficiency of 23.5% with mixed-salt treatment. In addition, the introduction of the moisture resisted F-substituted groups presents a more hydrophobic perovskite surface, thus enabling the decorated devices with excellent long-term stability under a high humid atmosphere as well as operational conditions.     

A novel strategy based on salp swarm algorithm for extracting the maximum power of proton exchange membrane fuel cell

Cell temperature and water content of the membrane have a significant effect on the performance of fuel cells. The current-power curve of the fuel cell has a maximum power point (MPP) that is needed to be tracked. This study presents a novel strategy based on a salp swarm algorithm (SSA) for extracting the maximum power of proton-exchange membrane fuel cell (PEMFC). At first, a new formula is derived to estimate the optimal voltage of PEMFC corresponding to MPP. Then the error between the estimated voltage at MPP and the actual terminal voltage of the fuel cell is fed to a proportional-integral-derivative controller (PID). The output of the PID controller tunes the duty cycle of a boost converter to maximize the harvested power from the PEMFC. SSA determines the optimal gains of PID. Sensitivity analysis is performed with the operating fuel cell at different cell temperature and water content of the membrane. The obtained results through the proposed strategy are compared with other programmed approaches of incremental resistance method, Fuzzy-Logic, grey antlion optimizer, wolf optimizer, and mine-blast algorithm. The obtained results demonstrated high reliability and efficiency of the proposed strategy in extracting the maximum power of the PEMFC.     

Effect of cooking temperature on texture and flavour binding of braised sauce porcine skin

To investigate the effect of cooking temperature (55, 65, 75, 85 and 95 °C) on texture and flavour binding of braised sauce porcine skin (BSPS), sensory acceptance, microstructure and flavour-binding capacity were investigated during the processing of BSPS. Samples cooked at 85 and 95 °C showed better texture and aroma scores. Hardness and chewiness of BSPS were obviously improved at 85 and 95 °C than control group. Collagen structure was significantly destroyed over 85 °C. The porcine skin collagen heated at 85 and 95 °C showed relatively higher flavour-binding capacity than other samples. The improvement of texture of BSPS was mainly attributed to the degradation of collagen. Higher aroma scores of BSPS were related to intense binding abilities with aroma compounds at 85 and 95 °C. Cooking at 85 or 95 °C could be an optimal cooking temperature for BSPS.     

Prediction of Chameleonic Efficiency

Chameleonic properties, i. e., the capacity of a molecule to hide polarity in non-polar environments and expose it in water, help achieving sufficient permeability and solubility for drug molecules with high MW. We present models of experimental measures of polarity for a set of 24 FDA approved drugs (MW 405-1113) and one PROTAC (MW 1034). Conformational ensembles in aqueous and non-polar environments were generated using molecular dynamics. A linear regression model that predicts chromatographic apparent polarity (EPSA) with a mean unsigned error of 10 Ų was derived based on separate terms for donor, acceptor, and total molecular SASA. A good correlation (R²=0.92) with an experimental measure of hydrogen bond donor potential, Δlog P_oct-tol, was found for the mean hydrogen bond donor SASA of the conformational ensemble scaled with Abraham's A hydrogen bond acidity. Two quantitative measures of chameleonic behaviour, the chameleonic efficiency indices, are introduced. We envision that the methods presented herein will be useful to triage designed molecules and prioritize those with the best chance of achieving acceptable permeability and solubility.