Highly magnetizable superparamagnetic colloidal aggregates with narrowed size distribution from ferrofluid emulsion

An empirical model for the concentrations of monomeric and micellized surfactants in solution is presented as a consistent approach for the quantitative analysis of data obtained with different experimental techniques from surfactant solutions. The concentration model provides an objective definition of the critical micelle concentration (cmc) and yields precise and well defined values of derived physical parameters. The use of a general concentration model eliminates subjective graphical procedures, reduces methodological differences, and thus allows one to compare directly the results of different techniques or to perform global fits. The application and validity of the model are demonstrated with electrical conductivity, surface tension, NMR chemical shift, and self-diffusion coefficient data for the surfactants SDS, CTAB, DTAB, and LAS. In all cases, the derived models yield excellent fits of the data. It is also shown that there is no need to assume the existence of different premicellar species in order to explain the chemical shifts and self-diffusion coefficients of SDS as claimed recently by some authors.     

Calibration of titration methods

Summary A calibration method is proposed which makes it possible to use titration techniques in the presence of systematic errors, even if these errors depend on the concentrations of the analytes. The approach uses an empirical calibration model which approximates the relationship between apparent (found) and true concentrations of the analytes. Also a calibration of the physical model of the titration process is proposed, as well as a method of determination of the model parameters, which are useful when analytes are determined by fitting the model to experimental data of titration. Both approaches, empirical and based on the physical model, may be applied jointly. The example presented reveals high efficiency of the proposed approach in cases when a deficient physicochemical model of the titration process is used in the determination of an analyte concentration (simulated titration data applied). The calibration proposed may be considered as a generalization of the titrant standardization used in the conventional volumetric analysis. It may be applied to all titration techniques and for all methods of end-point detection and determination of the concentration of analytes. It opens new possibilities for the development of titration methods. Permanent address: Department of Analytical Chemistry, Jagiellonian University, Karasia 3, PL-30-060 Krakow, Poland     

Linear free-energy relationships and the density functional theory: an analog of the hammett equation

Density functional theory has been applied to describe electronic substituent effects, especially in the pursuit of linear relationships similar to those observed from physical organic chemistry experiments. In particular, analogues for the Hammett equation parameters (sigma, rho) have been developed. Theoretical calculations were performed on several series of organic molecules in order to validate our model and for comparison with experimental results. The trends obtained by Hammett-like relations predicted by the model were found to be in qualitative agreement with the experimental data. The results obtained in this study suggest the applicability of similar correlation analysis based on theoretical methodologies that do not make use of empirical fits to experimental data can be useful in the study of substituent effects in organic chemistry.     

First-principles density-functional theory calculations of electron-transfer rates in azurin dimers

We have conceived and implemented a new method to calculate transfer integrals between molecular sites, which exploits few quantities derived from density-functional theory electronic structure computations and does not require the knowledge of the exact transition state coordinate. The method uses a complete multielectron scheme, thus including electronic relaxation effects. Moreover, it makes no use of empirical parameters. The computed electronic couplings can then be combined with estimates of the reorganization energy to evaluate electron-transfer rates that are measured in kinetic experiments: the latter are the basis to interpret electron-transfer mechanisms. We have applied our approach to the study of the electron self-exchange reaction of azurin, an electron-transfer protein belonging to the family of cupredoxins. The transfer integral estimates provided by the proposed method have been compared with those resulting from other computational techniques, from empirical models, and with available experimental data.     

Robustness properties of a robust partial least squares regression method

The presence of multicollinearity in regression data is no exception in real life examples. Instead of applying ordinary regression methods, biased regression techniques such as principal component regression and ridge regression have been developed to cope with such datasets. In this paper, we consider partial least squares (PLS) regression by means of the SIMPLS algorithm. Because the SIMPLS algorithm is based on the empirical variance-covariance matrix of the data and on least squares regression, outliers have a damaging effect on the estimates. To reduce this pernicious effect of outliers, we propose to replace the empirical variance-covariance matrix in SIMPLS by a robust covariance estimator. We derive the influence function of the resulting PLS weight vectors and the regression estimates, and conclude that they will be bounded if the robust covariance estimator has a bounded influence function. Also the breakdown value is inherited from the robust estimator. We illustrate the results using the MCD estimator and the reweighted MCD estimator (RMCD) for low-dimensional datasets. Also some empirical properties are provided for a high-dimensional dataset.     

Étude physique et numérique de la circulation cérébrale en pathologie carotidienne

A realistic and versatile physical model was built to simulate blood flow through the circle of Willis. Experimental data were then compared to those provided by numerical simulations. When the network is symmetrical and free of stenosis, the results of a linear model closely fit the experimental data. In presence of severe obstructive lesions of internal carotid arteries, the pressure drops induced by sudden changes of section or direction at the level of the communicating arteries must be taken into account. Introducing empirical flow-pressure drop relationships in the theoretical model, leads to an excellent agreement between experimental and simulated data. © 1999 Académie des sciences/Éditions scientifiques et médicales Elsevier SAS     

Extracting robust and physically meaningful pitzer parameters for thermodynamic properties of electrolytes from experimental data. Ridge regression as an aid to the problem of intercorrelation

The Pitzer interaction model for thermodynamic properties of electrolytes is reevaluated in view of available regression techniques for the statistical inference of Pitzer parameters from experimental data. It is concluded that ordinary least squares regression is not generally suited, because of the intrinsic correlations among the various predictor variables in the Pitzer model. The predictor variables all are some function of the concentration of the electrolyte considered. Ridge regression, a mathematically only slightly different procedure designed to overcome the problem of intercorrelations, often yields more robust estimates for the Pitzer parameters. The potential of RR is demonstrated by some examples for the system GaCl₃–HCl. The ridge estimates are expected to be closer to the physically true parameter values.     

Diffusion and Reaction Rates of the Yttrium Aluminium Garnet Synthesis using Different Techniques

The mathematical model of the yttrium aluminium garnet synthesis presented in this article. The model based on a system of non-stationary diffusion equations containing a non-linear term related to kinetics of reaction. Using computer-simulation tools and known experimental results we estimated the diffusion and reaction rates of the synthesis. Also it was shown that diffusion rate is a limited stage of the synthesis.     

Testing physical models of passive membrane permeation

The biophysical basis of passive membrane permeability is well-understood, but most methods for predicting membrane permeability in the context of drug design are based on statistical relationships that indirectly capture the key physical aspects. Here, we investigate molecular mechanics-based models of passive membrane permeability and evaluate their performance against different types of experimental data, including parallel artificial membrane permeability assays (PAMPA), cell-based assays, in vivo measurements, and other in silico predictions. The experimental data sets we use in these tests are diverse, including peptidomimetics, congeneric series, and diverse FDA approved drugs. The physical models are not specifically trained for any of these data sets; rather, input parameters are based on standard molecular mechanics force fields, such as partial charges, and an implicit solvent model. A systematic approach is taken to analyze the contribution from each component in the physics-based permeability model. A primary factor in determining rates of passive membrane permeation is the conformation-dependent free energy of desolvating the molecule, and this measure alone provides good agreement with experimental permeability measurements in many cases. Other factors that improve agreement with experimental data include deionization and estimates of entropy losses of the ligand and the membrane, which lead to size-dependence of the permeation rate.     

Activity coefficients and micellar equilibria. I. The mass action law model applied to aqueous solutions of sodium carboxylates at 298.15 K

Douhéret, G. and Viallard, A., 1982. Activity coefficients and micellar equilibria. I. The mass action law model applied to aqueous solutions of sodium carboxylates at 298.15 K. Fluid Phase Equilibria, 8: 233–250.A method of successive approximations is proposed in order to estimate five parameters used in the calculation of mean activity coefficients γ_± for sodium carboxylates in aqueous solution, as a function of concentration. A model has been developed assuming monodispersion of non-charged micelles; separate adjustment of the parameters allows estimates to be made of the separate contributions to the observed complex variation of γ_± as a function of molality. Thus, the monomer, premicellar and micellar ranges have been determined precisely; the critical values have been found to be in good agreement with previous results obtained from the successive treatment of apparent molal volumes by means of the mass action law and the phase separation model. Micelle aggregation numbers have also been determined and agree satisfactorily with data derived from various experimental techniques, mainly NMR spectroscopy; free enthalpies of micellization have been calculated.Estimation of the standard deviations σ_γ± reveals that the values computed for the mean activity coefficients lie within the experimental accuracy. It should be possible to obtain additional information advantageously by subsequent treatment by means of the phase separation model.     

Sensitivity and correlation analysis of the physical parameters in absorption,four-wave mixing,and Schlieren experiments

Experimental data that are used to determine rate coefficients depend not only upon reaction rates but also the physical properties of the measured species. Sensitivity coefficients are presented for the physical parameters of three general experimental techniques: a signal linearly dependent on the concentration of a species, a signal quadratically dependent on concentration, and a schlieren signal, which depends upon a bulk property of the system. With these, both the physical and chemical parameters of a model may be treated on a comparable basis. The similarities and differences between these techniques are illustrated in a simple example of radical formation via first-order precursor decomposition followed by second-order recombination. The results are then applied to two important examples: H₂ + O₂ and CH₃ + CH₃. In almost all cases, the experimental data contains more information about the physical parameters, such as the optical cross section, than the kinetic rate coefficients. Furthermore, if a physical parameter is not properly treated; strong correlations between it and rate coefficients will introduce significant systematic biases in the rate coefficient. © 1995 John Wiley & Sons, Inc.     

A kernel‐based method to determine optimal sampling times for the simultaneous estimation of the parameters of rival mathematical models

When several models are proposed for one and the same process, experimental design techniques are available to design optimal discriminatory experiments. However, because the experimental design techniques are model‐based, it is important that the required model predictions are not too uncertain. This uncertainty is determined by the quality of the already available data, since low‐quality data will result in poorly estimated parameters, which on their turn result in uncertain model predictions. Therefore, model discrimination may become more efficient and effective if this uncertainty is reduced first. This can be achieved by performing dedicated experiments, designed to increase the accuracy of the parameter estimates. However, performing such an additional experiment for each rival model may undermine the overall goal of optimal experimental design, which is to minimize the experimental effort. In this article, a kernel‐based method is presented to determine optimal sampling times to simultaneously estimate the parameters of rival models in a single experiment. The method is applied in a case study where nine rival models are defined to describe the kinetics of an enzymatic reaction (glucokinase). The results clearly show that the presented method performs well, and that a compromise experiment is found which is sufficiently informative to improve the overall accuracy of the parameters of all rival models, thus allowing subsequent design of an optimal discriminatory experiment. © 2009 Wiley Periodicals, Inc. J Comput Chem, 2009     

Densities, Refractive Indexes, and Excess Properties of Mixing of the n-Hexanol + Ethanenitrile + Dichloromethane Ternary System at 25°C

Excess molar volumes and excess refractive indexes of the n-hexanol + ethanenitrile + dichloromethane system and the three corresponding binary mixtures have been determined at 25°C, by measuring densities and refractive indexes. Different expressions exist in the literature to predict these excess properties from binary data. The empirical correlation of Cibulka is shown to be the best in this system. An estimation of excess molar volumes is also evaluated using a modified Heller equation, which depends on the refractive indexes of the mixtures. Comparison of the predictions by different methods with the experimental values of the physical properties has been made.     

A multitechnique approach to chemisorption studies: The N2-Ni(110) system

Complete characterization of an adsorbate system requires that many physical and chemical properties be determined from experimental data. Important quantities include: (1) the structure of the adsorbate phases; (2) thermodynamic quantities such as heats and entropies of adsorption and desorption; and (3) kinetic parameters which describe adsorption, desorption and ordering processes in the adsorbate phase. No single experimental technique can provide all of the necessary data over the complete range of coverages and temperatures and several techniques are usually required to minimize experimental ambiguities and artifacts. This review demonstrates the utility of such a multitechnique approach by describing a complete study of the chemisorption of molecular nitrogen of the nickel (110) surface. The techniques used are low-energy electron diffraction (LEED), ion scattering spectroscopy (ISS), infrared reflection absorption spectroscopy (IRRAS), X-ray photoelectron spectroscopy (XPS), ultraviolet photoelectron spectroscopy (UPS), work function change measurements, and thermal desorption spectroscopy (TDS). The data from these experimental studies are correlated and used to test theoretical models. Extensive physical and chemical data for the N₂/Ni(110) system are presented and compared with that of other molecular adsorption systems.     

An empirical model to predict temperature‐dependent thermal conductivity of amorphous polymers

Thermal conductivity in polymers has been theoretically and experimentally studied in good detail, but there is a need for more accurate models. Polymeric thermal conductivity exhibits a plateau‐like transition at temperatures around 10 K, which is not well accounted for by existing models. In this work, an empirical model that can predict temperature‐dependent thermal conductivity of amorphous polymers is developed. The model is based on kinetic theory and accounts for three sets of vibrational modes in polymers, and is developed using classical expressions, results of previous simulations, and experimental data. Fundamental material properties like density, monomer molecular weight, and speed of sound are the only input parameters. The model provides estimates for the locations of transitions between different sets of vibrational modes, an upper limit for the thermal conductivity, and temperature‐dependent thermal conductivity, which are in good agreement with experimental data. © 2017 Wiley Periodicals, Inc. J. Polym. Sci., Part B: Polym. Phys. 2017 , 55, 1160–1170     

Bootstrap method for the estimation of measurement uncertainty in spotted dual-color DNA microarrays

DNA microarrays permit the measurement of gene expression across the entire genome of an organism, but the quality of the thousands of measurements is highly variable. For spotted dual-color microarrays the situation is complicated by the use of ratio measurements. Studies have shown that measurement errors can be described by multiplicative and additive terms, with the latter dominating for low-intensity measurements. In this work, a measurement-error model is presented that partitions the variance into general experimental sources and sources associated with the calculation of the ratio from noisy pixel data. The former is described by a proportional (multiplicative) structure, while the latter is estimated using a statistical bootstrap method. The model is validated using simulations and three experimental data sets. Monte-Carlo fits of the model to data from duplicate experiments are excellent, but suggest that the bootstrap estimates, while proportionately correct, may be underestimated. The bootstrap standard error estimates are particularly useful in determining the reliability of individual microarray spots without the need for replicate spotting. This information can be used in screening or weighting the measurements.     

Analytical formulas for calculation of K X-ray production cross sections by alpha ions

In the present study, different procedures are followed to deduce the semi-empirical and the empirical K X-rayX-ray production cross sections induced by alpha ions from the available experimental data and the theoretical results of the ECPSSR model for elements with 20≤Z≤30. The deduced K X-ray production cross sections are compared with predictions from ECPSSR model and with other earlier works. Generally, the deduced K X-ray production cross sections obtained by fitting the available experimental data for each element separately give the most reliable values than those obtained by a global fit.     

A quantitative coarse-grain model for lipid bilayers

A simplified particle-based computer model for hydrated phospholipid bilayers has been developed and applied to quantitatively predict the major physical features of fluid-phase biomembranes. Compared with available coarse-grain methods, three novel aspects are introduced. First, the main electrostatic features of the system are incorporated explicitly via charges and dipoles. Second, water is accurately (yet efficiently) described, on an individual level, by the soft sticky dipole model. Third, hydrocarbon tails are modeled using the anisotropic Gay-Berne potential. Simulations are conducted by rigid-body molecular dynamics. Our technique proves 2 orders of magnitude less demanding of computational resources than traditional atomic-level methodology. Self-assembled bilayers quantitatively reproduce experimental observables such as electron density, compressibility moduli, dipole potential, lipid diffusion, and water permeability. The lateral pressure profile has been calculated, along with the elastic curvature constants of the Helfrich expression for the membrane bending energy; results are consistent with experimental estimates and atomic-level simulation data. Several of the results presented have been obtained for the first time using a coarse-grain method. Our model is also directly compatible with atomic-level force fields, allowing mixed systems to be simulated in a multiscale fashion.