The role of boron oxide and carbon amounts in the mechanosynthesis of ZrB2-SiC-ZrC nanocomposite via a self-sustaining reaction in the zircon/magnesium/boron oxide/graphite system

Herein, ZrSiO4/B2O3/Mg/C system was used to synthesize a ZrB2-based composite by means of a high energy ball milling process. A mechanically induced selfsustaining reaction was achieved in this system. A nanocomposite powder of ZrB2– SiC–ZrC was prepared with an ignition time of approximately 6 minutes of milling. The role of the stoichiometric amounts of B2O3 and carbon was investigated to clarify the governing mechanism for the formation of the productGobierno de España No. MAT2011-2298

Evolving neural network optimization of cholesteryl ester separation by reversed-phase HPLC

Cholesteryl esters have antimicrobial activity and likely contribute to the innate immunity system. Improved separation techniques are needed to characterize these compounds. In this study, optimization of the reversed-phase high-performance liquid chromatography separation of six analyte standards (four cholesteryl esters plus cholesterol and tri-palmitin) was accomplished by modeling with an artificial neural network–genetic algorithm (ANN-GA) approach. A fractional factorial design was employed to examine the significance of four experimental factors: organic component in the mobile phase (ethanol and methanol), column temperature, and flow rate. Three separation parameters were then merged into geometric means using Derringer’s desirability function and used as input sources for model training and testing. The use of genetic operators proved valuable for the determination of an effective neural network structure. Implementation of the optimized method resulted in complete separation of all six analytes, including the resolution of two previously co-eluting peaks. Model validation was performed with experimental responses in good agreement with model-predicted responses. Improved separation was also realized in a complex biological fluid, human milk. Thus, the first known use of ANN-GA modeling for improving the chromatographic separation of cholesteryl esters in biological fluids is presented and will likely prove valuable for future investigators involved in studying complex biological samples

Advances in structure elucidation of small molecules using mass spectrometry

The structural elucidation of small molecules using mass spectrometry plays an important role in modern life sciences and bioanalytical approaches. This review covers different soft and hard ionization techniques and figures of merit for modern mass spectrometers, such as mass resolving power, mass accuracy, isotopic abundance accuracy, accurate mass multiple-stage MS(n) capability, as well as hybrid mass spectrometric and orthogonal chromatographic approaches. The latter part discusses mass spectral data handling strategies, which includes background and noise subtraction, adduct formation and detection, charge state determination, accurate mass measurements, elemental composition determinations, and complex data-dependent setups with ion maps and ion trees. The importance of mass spectral library search algorithms for tandem mass spectra and multiple-stage MS(n) mass spectra as well as mass spectral tree libraries that combine multiple-stage mass spectra are outlined. The successive chapter discusses mass spectral fragmentation pathways, biotransformation reactions and drug metabolism studies, the mass spectral simulation and generation of in silico mass spectra, expert systems for mass spectral interpretation, and the use of computational chemistry to explain gas-phase phenomena. A single chapter discusses data handling for hyphenated approaches including mass spectral deconvolution for clean mass spectra, cheminformatics approaches and structure retention relationships, and retention index predictions for gas and liquid chromatography. The last section reviews the current state of electronic data sharing of mass spectra and discusses the importance of software development for the advancement of structure elucidation of small molecules

Optimization of the cavity size for AM1-SCRF calculations of electrode potentials in aqueous solution

A procedure for optimization of the cavity size for AM1-SCRF calculations of the electrode potentials in aqueous solution is presented. Comparison between the calculated electrode potentials of some benzoquinones and naphthoquinones obtained using the scaled cavity size and the experimental values suggests that the optimum cavity is placed at 1.4 times the van der Waals radii. Also, the electrode potentials of [2,5-bis(1-aziridinyl)-1,4-benzoquinones] with a wide range of substituents were calculated using the AM1-SCRF method. The calculated electrode potentials of these compounds using the optimum cavities give an r.m.s. error of 28 mV compared with an r.m.s. of 49 mV for the values obtained using the recommended radii for SCRF calculation

Model-based analysis for kinetic complexation study of Pizda and Cu(II)

In the present work, the multivariate kinetic complexation of a new synthesized ligand, 1-(2"-hydroxyl cyclohexyl)-3'-[aminopropyl]-4-[3'-aminopropyl]piperazine (Pizda) and Cu²⁺ in 50% ethanol-water solution is investigated using the UV-vis stopped-flow technique and state-of-the-art multi-wavelength numerical analysis. Model-based least squares fitting analysis or hard modeling is a specific part of chemometrics which is based on mathematical relationships for describing the measurements. Some recent developments include the incorporation of the effects of non-ideal experimental conditions into the fitting algorithm so it can substantially simplify experimental procedures. In this study no buffers are required because pH changes are taken into computations. Some 21 multi-wavelength kinetic measurements, taken at various initial concentrations of [H⁺] were analyzed globally, i.e. simultaneously applying an all inclusive reaction mechanism and a common set of species spectra. Using numerical analysis, the pH of the experimental solutions was allowed to vary as a consequence of the proceeding reactions. This enabled the complete kinetic analysis of the formation and dissociation of Cu(Pizda)ⁿ⁺. Here protonation equilibria have been directly incorporated into the rate law, so thus variable pH values have been allowed during each measurement. Using the independently estimated stability constants (from spectrophotometric and potentiometric measurements) for the Cu(Pizda) ⁿ+ complexes, a total of six rate constants and one protonation constant could be elucidated. The results of the analysis include the concentration distribution and spectra of all chemical species involved in the reaction. A low standard deviation and residual profiles obtained validate the results