Vibrational Spectra of Magnesium Hydrogenphosphate Trihydrate and of its Manganese Analogue

Abstract

The infrared (IR) and Raman spectra of MgHPO₄. 3H₂O and of a series of partially deuterated analogues as well as the IR spectra of MnHPO₄. 3H₂O have been recorded and interpreted. The analysis of the IR spectra in the HOD bending region rules out the possibility of existence of H₃OC⁺ ions in the structure.     

Development of models for prediction of the antioxidant activity of derivatives of natural compounds

Antioxidants are important for maintaining the appropriate balance between oxidizing and reducing species in the body and thus preventing oxidative stress. Many natural compounds are being screened for their possible antioxidant activity. It was found that a mushroom pigment Norbadione A, which is a pulvinic acid derivative, shows an antioxidant activity; the same was found for other pulvinic acid derivatives and structurally related coumarines. Based on the results of in vitro studies performed on these compounds as a part of this study quantitative structure–activity relationship (QSAR) predictive models were constructed using multiple linear regression, counter-propagation artificial neural networks and support vector regression (SVR). The models have been developed in accordance with current QSAR guidelines, including the assessment of the models applicability domains. A new approach for the graphical evaluation of the applicability domain for SVR models is suggested. The developed models show sufficient predictive abilities for the screening of virtual libraries for new potential antioxidants.     

Determination of the composition of human urinary calculi composed of whewellite, weddellite and carbonate apatite using artificial neural networks

More than half of the analyzed calculi from patients from Macedonia are composed of whewellite, weddellite and carbonate apatite (as single components or in binary or ternary mixtures). In order to develop a simple and satisfactorily reliable method for quantitative analysis of urinary calculi, the possibility was explored to employ artificial neural networks (ANNs) as a tool for such a purpose. By changing the number of input and hidden neurons, a search was made for the three-layered feed-forward ANN which would give the best performance. The root-mean-square errors (RMSE) for the test samples are: 0.035 for whewellite, 0.064 for weddellite and 0.078 for carbonate apatite. The accuracy of the method was checked using standard-addition method on real samples. The discrepancies between calculated and predicted mass fraction of constituents were in the range acceptable for use of the proposed method in clinical laboratories.     

Fourier Transform Vibrational Spectra of Magnesium Hydrogenphosphate Trihydrate. I. The O-H Stretching Region∗

Abstract

The Fourier transform (FT) infrared and Raman spectra of newberyite, MgHPH₄ - 3H₂O are studied in the region where the stretching vibrations of the water molecules (protiated and deuterated) and the O-H/O-D stretches of the hydrogenphosphate anions are expected to appear. The O-H stretching vibrations give rise to a complex feature known as the A,B,C trio. Since neither of the maxima found below 3000 cm^?1 represents a true band arising from a given fundamental, it is pointless to correlate their frequencies with the observed O…O distances. In the water stretching region, the two bands with highest frequencies undoubtedly correspond to the anti symmetric and symmetric stretch of one type of the water molecules. The stretching vibrations of one of the remaining two types of H₂O molecules are clearly uncoupled and the O-H oscillator involved in the weaker hydrogen bond is responsible for a band at 3376 cm^?1 whereas the rest of the water stretchings are apparently overlapped yielding the complex band below 3320 cm^?1. Thus the situation is again complicated and the correlations between the frequencies and the O_w…O distances are inappropriate. The two bands at highest frequencies (3522 and 3483 cm^?1 at RT) exhibit a positive temperature coefficient.

     

Determination of the composition of sialoliths composed of carbonate apatite and albumin using artificial neural networks

The determination of the components of the sialoliths is important both from the point of view of chances for a successful medical treatment of the patients and because the prevention of further re-occurrence of sialolithiasis depends upon the knowledge of the nature of the constituents of the concrements. Despite the fact that infrared spectroscopy is widely used for the determination of the composition of sialoliths, urinary calculi and bladder stones, we found no data for any chemometric method developed for such purposes. Here, a method is presented for quantitative determination of the content of salivary calculi composed of albumin and carbonate apatite (one of the most often found constituents in the analyzed calculi from the patients from Macedonia) using artificial neural networks (ANN). The results were checked on real samples using the standard addition method. The precision of the method was estimated using the relative standard deviation, which shows that it is suitable for routine analysis.     

Classification of perovskites with supervised self-organizing maps

In this work supervised self-organizing maps were used for structural classification of perovskites. For this purpose, structural data for total number of 286 perovskites, belonging to ABO3 and/or A2BB'O6 types, were collected from literature: 130 of these are cubic, 85 orthorhombic and 71 monoclinic. For classification purposes, the effective ionic radii of the cations, electronegativities of the cations in B-position, as well as, the oxidation states of these cations, were used as input variables. The parameters of the developed models, as well as, the most suitable variables for classification purposes were selected using genetic algorithms. Two-third of all the compounds were used in the training phase. During the optimization process the performances of the models were checked using cross-validation leave-1/10-out. The performances of obtained solutions were checked using the test set composed of the remaining one-third of the compounds. The obtained models for classification of these three classes of perovskite compounds show very good results. Namely, the classification of the compounds in the test set resulted in small number of discrepancies (4.2-6.4%) between the actual crystallographic class and the one predicted by the models. All these results are strong arguments for the validity of supervised self-organizing maps for performing such types of classification. Therefore, the proposed procedure could be successfully used for crystallographic classification of perovskites in one of these three classes.     

Prediction of the unit cell edge length of cubic A 2 2+ BB′O6 perovskites by multiple linear regression and artificial neural networks

The unit cell edge length, a, of a set of complex cubic perovskites having the general formula A ₂ ²⁺ BB′O₆ is predicted using two methodologies: multiple linear regression and artificial neural neworks. The unit cell edge length is expressed as a function of six independent variables: the effective ionic radii of the constituents (A, B and B′), the electronegativities of B and B′, and the oxidation state of B. In this analysis, 147 perovskites of the A ₂ ²⁺ BB′O₆ type, having the cubic structure and belonging to the Fm3m space group, are included. They are divided in two sets; 98 compounds are used in the calibration set and 49 are used in the test set. Both models give consistent results and could be successfully use to predict the lattice cell parameter of new members of this series.     

Simultaneous determination of composition of human urinary calculi by use of artificial neural networks

A new chemometric method, which uses artificial neural networks (ANN), is presented for determination of the composition of urinary calculi. The selected constituents were whewellite, weddellite, and uric acid from which approximately 40% of the urinary calculi obtained from Macedonia patients are composed. The results for the synthetic mixtures were better then those obtained by partial least squares (PLS) regression or by the principal component regression (PCR), because neural networks have better prediction capacity. The generalization abilities of the optimized neural networks were checked using the standard addition method on carefully selected real natural samples.     

Fourier Transform Vibrational Spectra of Magnesium Hydrogenphosphate Trihydrate H. The 2000-370 cm−1 Region

The Fourier transform infrared and Raman spectra of newberyite, MgHPO₄·3H₂-O, were studied in the 2000-370 cm-l region. Also investigated were the spectra of a series of partially deuterated analogues. By comparing the spectra recorded at room temperature and those obtained at the boiling temperature of liquid nitrogen and by studying the spectra of the series of partially deuterated newberyite an assignment was proposed for the observed bands. The spectra are fully in line with the crystallographic data and prove that the title compound is a true crystalline hydrate and does not contain H₃O⁺ ions in its structure.