Composite Polybenzimidazole Membrane with High Capacity Retention for Vanadium Redox Flow Batteries

Currently, energy storage technologies are becoming essential in the transition of replacing fossil fuels with more renewable electricity production means. Among storage technologies, redox flow batteries (RFBs) can represent a valid option due to their unique characteristic of decoupling energy storage from power output. To push RFBs further into the market, it is essential to include low-cost materials such as new generation membranes with low ohmic resistance, high transport selectivity, and long durability. This work proposes a composite membrane for vanadium RFBs and a method of preparation. The membrane was prepared starting from two polymers, meta-polybenzimidazole (6 μm) and porous polypropylene (30 μm), through a gluing approach by hot-pressing. In a vanadium RFB, the composite membrane exhibited a high energy efficiency (~84%) and discharge capacity (~90%) with a 99% capacity retention over 90 cycles at 120 mA·cm⁻², exceeding commercial Nafion^® NR212 (~82% efficiency, capacity drop from 90% to 40%) and Fumasep^® FAP-450 (~76% efficiency, capacity drop from 80 to 65%).     

Graphene/activated carbon supercapacitors with sulfonated-polyetheretherketone as solid-state electrolyte and multifunctional binder

Sulfonated polyetheretherketone (SPEEK) has been synthesised by sulphonation process and used as the solid-state electrolyte, binder and surfactant for supercapacitors. Reduced graphene dispersed by SPEEK is used as a high-efficiency conducting additive in solid-state supercapacitors. It is found that SPEEK can improve the stability of the reduced graphene dispersion significantly, and therefore, the solid-state supercapacitors show a large decrease in IR drop and charge-transfer resistance (R_ct), resulting in a higher rate capability. The solid-state supercapacitors with the activated carbon/reduced graphene/SPEEK/electrode can be operated from 1 to 8 A/g and exhibit capacity retention of 93%. The noteworthy is more than twice higher value for capacity retention by comparison with the solid-state supercapacitors using activated carbon/reduced graphene/PVDF electrode (capacity retention is 36%). The cell of reduced graphene with SPEEK can be cycled over 5000 times at 5 A/g with no capacitance fading.     

保留时间两点校正反相高效液相色谱法测定持久性有机污染物的正辛醇-水分配系数

采用改进的反相高效液相色谱法(RP-HPLC)测定了持久性有机污染物(POPs)包括多环芳烃(PAHs)、多氯二苯并二恶英(PCDDs)、多氯二苯并呋喃(PCDFs)和十溴二苯乙烷(DBDPE)等的正辛醇-水分配系数(logKow)。采用保留时间双点校正法(DP-RTC)校正因色谱柱老化等引起的保留时间漂移。以37种有可靠logKow实验值的苯系物、PAHs、PCDD/Fs类似物为模型化合物,建立了logKow和外推至纯水相的保留因子logkw的定量结构-色谱保留关系(QSRR)模型,回归方程为logKow=(1.18±0.02)logkw+(0.36±0.11),其相关系数(R2)为0.985,交叉验证相关系数(R2cv)为0.983,标准偏差(SD)为0.16。进而,用4个已有可靠logKow实验值的验证化合物(联苯、芴、PCDD 1和PCDF 114)对模型进行了外部验证,表明RP-HPLC测得的logKow值与摇瓶法/慢搅法结果有很好的一致性,尤其是对疏水性强的化合物。采用该模型测定了29种特别受关注的POPs的logKow值,这些化合物的logKow实验值均未见报道。所建立的DP-RTC-HPLC是测定强疏水性POPs的logKow值的一种值得推荐的方法。     

Artificial intelligence–based models for the qualitative and quantitative prediction of a phytochemical compound using HPLC method

Isoquercitrin is a flavonoid chemical compound that can be extracted from different plant species such as Mangifera indica (mango), Rheum nobile , Annona squamosal , Camellia sinensis (tea), and coriander ( Coriandrum sativum L.). It possesses various biological activities such as the prevention of thromboembolism and has anticancer, antiinflammatory, and antifatigue activities. Therefore, there is a critical need to elucidate and predict the qualitative and quantitative properties of this phytochemical compound using the high performance liquid chromatography (HPLC) technique. In this paper, three different nonlinear models including artificial neural network (ANN), adaptive neuro-fuzzy inference system (ANFIS), and support vector machine (SVM),in addition to a classical linear model [multilinear regression analysis (MLR)], were used for the prediction of the retention time (tR) and peak area (PA) for isoquercitrin using HPLC. The simulation uses concentration of the standard, composition of the mobile phases (MP-A and MP-B), and pH as the corresponding input variables. The performance efficiency of the models was evaluated using relative mean square error (RMSE), mean square error (MSE), determination coefficient (DC), and correlation coefficient (CC). The obtained results demonstrated that all four models are capable of predicting the qualitative and quantitative properties of the bioactive compound. A predictive comparison of the models showed that M3 had the highest prediction accuracy among the three models. Further evaluation of the results showed that ANFIS–M3 outperformed the other models and serves as the best model for the prediction of PA. On the other hand, ANN–M3proved its merit and emerged as the best model for tR simulation. The overall predictive accuracy of the best models showed them to be reliable tools for both qualitative and quantitative determination.     

Development of supercritical fluid chromatography coupled with mass spectrometry method for characterization of a nonionic surfactant and comparison with liquid chromatography coupled with mass spectrometry method

The supercritical fluid chromatography coupled with mass spectrometry (SFC‐MS) method and liquid chromatography coupled with mass spectrometry (LC‐MS) method were developed for the separation and characterization of poly (ethylene oxide) methyl glucose sesquistearate (PEO‐Glu‐sesquistearate). The products of PEO‐Glu‐sesquistearate are composed of complex oligomers. The relationship between molecular structure of these oligomers and chromatographic retention behavior in both SFC and LC were discussed and compared. As compared with LC, hydrophobic moieties of compounds favor the fast elution in SFC. The different series can be better separated by LC, while the homologues compounds in same series can be better separated by SFC, and SFC‐MS provided more comprehensive structural information. Different series such as PEO‐distearate, PEO‐stearate, PEO, PEO‐Glu‐tetrastearate, PEO‐Glu‐tristearate, PEO‐Glu‐distearate, PEO‐Glu‐stearate, and PEO‐Glu were identified by MS/MS.     

Aligning retention time shifts in HPLC three‐dimensional spectra by icoshift approach combined with data arrangement methods and the release of a graphical user interface

High‐performance liquid chromatography coupled with photodiode array detection has been extensively applied in many fields and the peaks among the analyzed samples can be shifted due to the variations of instrumental and experimental conditions. In multivariate analysis, retention time alignment is an important pretreatment step. Hence, the shifted peaks in high‐performance liquid chromatography coupled with photodiode array detection three‐dimensional spectra should be aligned for further analysis. Being motivated by this purpose, the interval correlated shifting method combined with the proposed data arrangement methods are recommended and employed on high‐performance liquid chromatography coupled with photodiode array detection data as a demonstration. We validate the alignment performance of the proposed method through comparison the consistency of the retention time before and after alignment. The obtained results demonstrated that the proposed method is capable of successful aligning the employed data. Additionally, the interval correlated shifting method combined with the data arrangement modes is implemented in an easy‐to‐use graphical user interface environment and so can be operated easily by users not familiar with programming languages.     

Dual‐mode hydrophilic interaction normal phase and reversed phase liquid chromatography of polar compounds on a single column

Adopting a stationary phase convention circumvents problematic definition of the boundary between the stationary and the mobile phase in the liquid chromatography, resulting in thermodynamically consistent and reproducible chromatographic data. Three stationary phase definition conventions provide different retention data, but equal selectivity: (i) the complete solid phase moiety; (ii) the solid porous part carrying the active interaction centers; (iii) the volume of the inner column pores. The selective uptake of water from the bulk aqueous‐organic mobile phase significantly affects the volume and the properties of polar stationary phases. Some polar stationary phases provide dual‐mode retention mechanism in aqueous‐organic mobile phases, reversed‐phase in the water‐rich range, and normal‐phase at high concentrations of the organic solvent in water. The linear solvation energy relationship model characterizes the structural contributions of the non‐selective and selective polar interactions both in the water‐rich and organic solvent‐rich mobile phases. The inner‐pore convention provides a single hold‐up volume value for the retention prediction on the dual‐mode columns over the full mobile phase range. Using the dual‐mode monolithic polymethacrylate zwitterionic micro‐columns alternatively in each mode in the first dimension of two‐dimensional liquid chromatography, in combination with a short reversed‐phase column in the second dimension, provides enhanced sample information.     

亲核性1,2-重排为何迁移基团的构型保持不变*

亲核性1,2-重排反应是有机化学的重要反应之一,重排中离去基团的离去和迁移基团的迁移步骤既可以是分步的,也可以是协同的,但是迁移基团的构型始终保持不变。本文用超共轭效应和反应过程中有机立体电子效应解释了此现象,掌握一般规律,希望能够从教学上便于教师讲授和学生学习理解。     

手性有机酸薄层色谱保留指数的拓扑模型

基于Kier的分子连接性指数及邻接矩阵提出新型分子连接性指数（^mG_t^v）;引入手性指数（w_j）并建立了手性连接性指数（^mG_t^v）：^mG_t^v=^mG_t^v×w_j。^mG_t^v适用于手性分子、非手性分子及内消旋异构体的结构差异表征。用多元统计回归研究18种手性羟酸和氨基酸的薄层色谱保留指数（R_M）与^mG_t^v的定量构效关系,经最佳变量子集回归建立其四元数学模型,传统的判定系数（R²）为0.973,逐一剔除法（leave-one-out,LOO）的交互验证系数（Q²）为0.950,结果证明具有良好的稳健性及预测能力。根据进入该模型的4个手性连接性指数（⁰C_p^v、²C_p^v、C_ch^v、⁵C_p^v）可知,影响手性有机酸保留指数的主要因素是分子的二维结构特征和分子的手性特征以及柔韧性、折叠程度等三维结构因素。从上可见,新建手性连接性指数对手性有机酸的保留指数表征具有合理性与有效性,为预测手性有机酸的保留指数提供了一种有效方法。     

烷烃同系物气相色谱保留指数的分子拓扑研究

定义了分子中原子的平衡电负性,并用原子的平衡电负性对分子图进行着色,在距离矩阵的基础上结合分子中各原子的支化度构建了一种新的拓扑指数N1,N2和N3。该拓扑指数对分子结构实现惟一性表征,具有优良的结构选择性。将拓扑指数N1,N2和N3与烷烃在固定相角鲨烷(柱温50　℃)及SE-30(柱温80　℃)上的气相色谱保留指数进行多元线性回归,结果表明烷烃的气相色谱保留指数可分别定量描述为I(Squalane)=23.97842N1-3.86562N2+0.787379N3+42.33061,I(SE-30)=23.83937N1-3.5687N2+0.939876N3+22.11952。用上述回归方程对烷烃的气相色谱保留指数进行预测,结果表明预测值与实验值的平均相对误差均为1.31%,预测结果误差在实验误差范围内。