Application Of (CS)-C-137 fingerprinting technique to interpreting sediment production records from reservoir deposits in a small catchment of the Hilly Loess Plateau；China

IEECAS SKLLQG

Dust weather records in Beijing during 1860-1898 AD based on the Diary of Tonghe Weng

IEECAS SKLLQG

Using HPLC retention parameters to estimate fish bioconcentration factors of organic compounds

Reversed-phase high performance liquid chromatography (RP-HPLC) was employed to develop predictive models for fish bioconcentration factors (BCF) of organic compounds. Estimation of BCF from RP-HPLC retention parameters on octadecyl-bonded silica gel (ODS), cyanopropyl-bonded silica gel (CN), and phenyl-bonded silica gel (Ph) columns were investigated. The results show that, for a set of compounds belonging to different chemical classes, the CN stationary phase is the best one among the three columns and better than n-octanol/water model for BCF estimation. A multi-column RP-HPLC model, using the retention parameters on the CN and Ph columns as the variables of multiple linear regression equations, was further evaluated to estimate BCF of organic compounds belonging to different chemical classes, and the results show that the multi-column RP-HPLC model is better than that of any single RP-HPLC column for BCF estimation.

New uniform algorithm to predict reversed phase retention values under different gradient conditions

A new numerical emulation algorithm was established to calculate retention parameters in RP-HPLC with several retention times under different linear or nonlinear binary gradient elution conditions and further predict the retention time under any other binary gradient conditions. A program was written according to this algorithm and nine solutes were used to test the program. The prediction results were excellent. The maximum relative error of predicted retention time was less than 0.45%. (C) 2002 Elsevier Science B.V. All rights reserved.

Retention modeling and simultaneous optimization of pH value and gradient steepness in RP-HPLC using feed-forward neural networks

A novel approach is proposed for the simultaneous optimization of mobile phase pH and gradient steepness in RP-HPLC using artificial neural networks. By presetting the initial and final concentration of the organic solvent, a limited number of experiments with different gradient time and pH value of mobile phase are arranged in the two-dimensional space of mobile phase parameters. The retention behavior of each solute is modeled using an individual artificial neural network. An "early stopping" strategy is adopted to ensure the predicting capability of neural networks. The trained neural networks can be used to predict the retention time of solutes under arbitrary mobile phase conditions in the optimization region. Finally, the optimal separation conditions can be found according to a global resolution function. The effectiveness of this method is validated by optimization of separation conditions for amino acids derivatised by a new fluorescent reagent.

Retention modeling and optimization of pH value and solvent composition in HPLC using back-propagation neural networks and uniform design

A novel method for the optimization of pH value and composition of mobile phase in HPLC using artificial neural networks and uniform design is proposed. As the first step. seven initial experiments were arranged and run according to uniform design. Then the retention behavior of the solutes is modeled using back-propagation neural networks. A trial method is used to ensure the predicting capability of neural networks. Finally, the optimal separation conditions can be found according to a global resolution function. The effectiveness of this method is validated by optimization of separation conditions for both basic and acidic samples.

Abnormal phenomenon of the dependence of the retention factors for uncharged species on applied voltage in capillary electrochromatography

Polymethacrylate-based monolithic columns were prepared for capillary electrochromatography (CEC) by in situ copolymerization of butyl methacrylate (BMA), 2-acrylamido-2-methyl-1-propanesulfonic acid (AMPS), and ethylene dimethacrylate (EDMA) in the presence of a porogen in fused-silica capillaries of 100 mum I.D. The abnormal phenomenon that retention factors for neutral species decreases with applied voltage in CEC was observed. Capillary electrophoresis (CE) instruments usually require a period of time to increase voltage from 0 kV to desired value, which is called as ramp time. Such ramp time and any error in the determination of dead time should be taken into account during the accurate calculation of retention factors. After the correction of the retention factors, the plots of the corrected factors for alkylbenzene versus applied voltage were made, the absolute value of the plot slopes are less than 1.8 X 10(-4), Which indicates that the corrected retention times for neutral species do not show any dependence on applied voltage. Further, the plots of the corrected retention times for acidic and basic compounds versus the reciprocal of applied voltage were drawn, where the target compounds were eluted in neutral form. The very nice linearity of the plots was obtained. The linear correlation coefficients are over 0.999. Here, the slopes of the plots represent

New Efficiency Records for Stable Dye-Sensitized Solar Cells with Low-Volatility and Ionic Liquid Electrolytes

We report a high molar extinction coefficient heteroleptic polypyridyl ruthenium sensitizer, featuring an electron-rich 3,4-ethylenedioxythiophene unit in its ancillary ligand. A nanocrystalline titania film stained with this sensitizer shows an improved optical absorption, which is highly desirable for practical dye-sensitized solar cells with a thin photoactive layer, facilitating the efficient charge collection.