Synthese und Charakterisierung neuer Alkali-Metall Oxometallate erhalten über die Azid/Nitrat-Route

During this PhD thesis, azide/nitrate route has been confirmed to be an efficient tool in the synthesis of alkali-metal oxometalates. As a particularly beneficial feature, azide/nitrate route enables to approach such metastable oxometalates, which are not in reach via classical oxide-acid-base reactions. Especially, with this method it was possible to synthesize new ternary oxides containing low valences and uncommon coordination numbers (CN) of the respective alkali ions (K, Rb, Cs) and transition metal (Ni). Most significantly, this method allows to precisely fix the oxygen content of the target compound, and thus the valence state of transition metal, by the starting azide/nitrate ratio. Along this approach, we have been able to synthesize two families of low dimensional, intrinsically doped oxocuprates(II/III) and oxonickelates(II/III). In addition, the influence of the kind of alkalimetal on the secondary structure as well as physical properties of the one dimensional polyoxometalate anion was examined. Also, introduction of the alkaline earth metal azides in the azide/nitrate route has resulted in a the new phase displaying unusual structural features.Im Rahmen der vorliegenden Dissertation wurde gezeigt, dass die Azid-Nitrat-Route ein effizientes Werkzeug zur Synthese von Alkalimetal-oxometallaten darstellt. Ein besonders herauszustellender Vorteil dieser Methode ist die möglich gewordene Synthese metastabiler Oxometallate welche nicht durch die klassische Oxid-Säure-Base-Reaktion hergestellt werden können. So war es möglich neue ternäre Oxide, mit ungewöhnlicher Koordinationszahl (CN) der Alkali- (K, Rb, Cs) sowie der Übergangsmetalle (Ni und Cu) und ungewöhnlich niedriger Oxidationszahl des Nickels, darzustellen. Das Bedeutsame dieser Methode stellt vor allem die genaue Einstellung des Sauerstoffgehalts und somit der Oxidationszahl des Übergangsmetalls, über das Verhältnis von Azid zu Nitrat, in der Zielverbindung dar. Anhand dieses Vorgehens war es uns möglich zwei Klassen niederdimensionaler, intrinsisch dotierter Oxocuprate (II/III) und -nickelate (II/III) darzustellen. Zusätzlich wurde der Einfluss des jeweiligen Alkalimetalls auf die Sekundärstruktur wie auch die physikalischen Eigenschaften des eindimensionalen Polyoxometallatanions untersucht. Ebenso führte die Verwendung von Erdalkalimetallaziden in der Azid-Nitrat-Route zu einer neuen Phase mit ungewöhnlichen strukturellen Eigenheiten

Selection of the suitable polymer for supercritical fluid assisted preparation of carvedilol solid dispersions

Solid dispersions production is one of the substantial approaches for improvement of poor drug solubility. Additionally, supercritical fluid assisted method for preparation of solid dispersions can offer many advantages in comparison to the conventional melting or solvent-evaporation methods. Miscibility analysis provides valuable guidance for selection of the most appropriate polymeric carrier for dispersion of the drug of interest. In addition to the increased drug release rate, solid dispersions should have proper mechanical attributes in order to be successfully formulated in the final solid dosage form such as tablet. Therefore, several pharmaceutical grade polymers have been selected for development of BCS Class II drug carvedilol (CARV) solid dispersions. They were compared based on behavior in supercritical CO 2 and affinity towards CARV calculated from the miscibility analysis. By utilization of the supercritical CO 2 assisted method, solid dispersions of CARV with the selected (co)polymers (polyvinylpyrrolidone (PVP), hydroxypropyl methylcellulose (HPMC), Soluplus® and Eudragit®) were obtained. Properties of the prepared CARV-polymer dispersions were observed by the polarizing and scanning electron microscopy and analyzed by differential scanning calorimetry and Fourier transform infrared spectroscopy. CARV was additionally characterized by X-ray powder diffraction. Furthermore, in vitro dissolution studies and dynamic compaction analysis were performed on the selected samples of solid dispersions. Among the studied polymers, PVP and HPMC have been identified as polymers with the highest affinity towards CARV, based on the calculated δ p values. This has been also confirmed with the highest dissolution efficiency of CARV-PVP and CARV-HPMC solid dispersions. Solid state characterization indicated that CARV was dispersed either molecularly, or in the amorphous form, depending on interactions with each polymer. Determination of CARV-PVP and CARV-HPMC mechanical properties revealed that CARV-PVP solid dispersion has superior compactibility and tabletability. Therefore, CARV-PVP solid dispersion has been highlighted as the most appropriate for the further development of tablets as the final dosage form. Presented study provides an example for efficient approach for development of poorly soluble drug solid dispersion with satisfactory tableting properties.This is the peer-reviewed version of the following article: Đuriš, J., Milovanović, S., Medarević, Đ., Dobričić, V., Dapčević, A.,& Ibrić, S.. (2019). Selection of the suitable polymer for supercritical fluid assisted preparation of carvedilol solid dispersions. International Journal of Pharmaceutics Elsevier Science Bv, Amsterdam., 554, 190-200. [https://doi.org/10.1016/j.ijpharm.2018.11.015]Published version [http://technorep.tmf.bg.ac.rs/handle/123456789/4335

Simulated-annealing-based genetic algorithm for modeling the optical constants of solids

We propose a simulated-annealing-based genetic algorithm for solving model parameter estimation problems. The algorithm incorporates advantages of both genetic algorithms and simulated annealing. Tests on computer-generated synthetic data that closely resemble optical constants of a metal were performed to compare the efficiency of plain genetic algorithms against the simulated-annealing-based genetic algorithms. These tests assess the ability of the algorithms to and the global minimum and the accuracy of values obtained for model parameters. Finally, the algorithm with the best performance is used to fit the model dielectric function to data for platinum and aluminum. (C) 1997 Optical Society of America

Optimization and Prediction of Ibuprofen Release from 3D DLP Printlets Using Artificial Neural Networks

The aim of this work was to investigate effects of the formulation factors on tablet printability as well as to optimize and predict extended drug release from cross-linked polymeric ibuprofen printlets using an artificial neural network (ANN). Printlets were printed using digital light processing (DLP) technology from formulations containing polyethylene glycol diacrylate, polyethylene glycol, and water in concentrations according to D-optimal mixture design and 0.1% w/w riboflavin and 5% w/w ibuprofen. It was observed that with higher water content longer exposure time was required for successful printing. For understanding the effects of excipients and printing parameters on drug dissolution rate in DLP printlets two different neural networks were developed with using two commercially available softwares. After comparison of experimental and predicted values of in vitro dissolution at the corresponding time points for optimized formulation, the R2 experimental vs. predicted value was 0.9811 (neural network 1) and 0.9960 (neural network 2). According to difference f1 and similarity factor f2 (f1 = 14.30 and f2 = 52.15) neural network 1 with supervised multilayer perceptron, backpropagation algorithm, and linear activation function gave a similar dissolution profile to obtained experimental results, indicating that adequate ANN is able to set out an input–output relationship in DLP printing of pharmaceutics

Magnetic properties of doped LaMnO3 ceramics obtained by a polymerizable complex method

Substituted lanthanum manganites with the general formula A(1-x) B (x) MnO3 (A = La, B = Ca, SraEuro broken vertical bar) have attracted a lot of attention due to their exceptional electric and magnetic properties. In this work, pure and Ca2+, Sr2+-doped LaMnO3 (LMO) with the concentrations of dopants 30% Ca2+ (LCMO), 30% Sr2+ (LSMO) and 15% Ca2+ + 15% Sr2+ (LCSMO) (in mol. %) were synthesized by polymerizable complex method. Bulk samples were prepared by sintering at 1300 A degrees C for 4 h in oxygen atmosphere. It was found that sintering in oxygen atmosphere enables preparation of single phase ceramics with rhombohedral crystal structure. Chemically prepared fine, submicronic precursor powders provided uniform microstructure and grain size distribution in final ceramics. As a result, pure and doped LMO ceramics with excellent microstructural and magnetic properties were obtained. Depending on the composition, magnetic measurements showed high saturation magnetizations (up to 93 emu/g), with values of the Curie temperature in the range 180-390 K and magnetoresistance up to 67%

Synthesis of pure and doped LaMnO3 powders from citrate precursors

In this work pure and doped LMO were prepared using modified Pechini method from lanthanum and manganese citrates. Lanthanum citrate was prepared starting from La2O3, while manganese citrate was prepared from Mn(NO3)(2). Valence state of the manganese was controlled by adjusting pH value of the solution and confirmed by EPR and UV/VIS analysis. Thermal treatment conditions for preparation of LMO powders were determined from TG/DTA of dried precursors. XRD results confirmed that pure perovskite phase was successfully prepared in single LMO and Ca-doped LMO. SEM and measurements of specific surface area of the powders showed the existence of large agglomerates consisting of submicronic primary particles.Research Trends in Contemporary Materials Science, 8th Conference of the Yugoslav-Materials-Research-Society (Yu-MRS), Sep 04-08, 2006, Herceg Novi, Montenegr

Optimization and prediction of ibuprofen release from 3D DLP printlets using artificial neural networks

© 2019 by the authors. Licensee MDPI, Basel, Switzerland. The aim of this work was to investigate effects of the formulation factors on tablet printability as well as to optimize and predict extended drug release from cross-linked polymeric ibuprofen printlets using an artificial neural network (ANN). Printlets were printed using digital light processing (DLP) technology from formulations containing polyethylene glycol diacrylate, polyethylene glycol, and water in concentrations according to D-optimal mixture design and 0.1% w/w riboflavin and 5% w/w ibuprofen. It was observed that with higher water content longer exposure time was required for successful printing. For understanding the effects of excipients and printing parameters on drug dissolution rate in DLP printlets two different neural networks were developed with using two commercially available softwares. After comparison of experimental and predicted values of in vitro dissolution at the corresponding time points for optimized formulation, the R2 experimental vs. predicted value was 0.9811 (neural network 1) and 0.9960 (neural network 2). According to difference f1 and similarity factor f2 (f1 = 14.30 and f2 = 52.15) neural network 1 with supervised multilayer perceptron, backpropagation algorithm, and linear activation function gave a similar dissolution profile to obtained experimental results, indicating that adequate ANN is able to set out an input–output relationship in DLP printing of pharmaceutics

Multi Response Optimization of the Functional Properties of Rubber Seed – Shear Butter Based Core Oil Using D-Optimal Mixture Design

In this study, rubber seed/shea butter oil was used to formulate core oil. The formulated core oil was characterised. D-optimal mixture design was used for multi response optimisation of the functional properties of rubber seed-shea butter coil oil. Desirable values for some responses might be obtained from a factor combination while for others responses not so desirable values. Through multiple response optimisations, a factor setting that gives the desirable values for all responses was obtained. The selected optimum mixture setting for the formulated core oil is 65.937% Rubber seed and 34.063% Shea butter oil at desirability of 0.924. Under the optimum condition the functional properties of the core oil was found to be 39.57KN/M2, 626.85KN/M2, 36.63KN/M2, 593.906KN/M2, 412.605 and 167.309s for Green Compressive Strength, Dry Compressive Strength, Green Tensile Strength, Dry Tensile Strength, Permeability and Collapsibility respectively. The optimum conditions were validated with less than 0.2% error. The functional properties of the formulated core oil was compared to the functional properties of linseed core oil. It was found that rubber seed-shea butter core oil can be used for producing cores suitable for Aluminium casting

Prediction of possible CaMnO3 modifications using an ab initio minimization data-mining approach

We have performed a crystal structure prediction study of CaMnO3 focusing on structures generated by octahedral tilting according to group-subgroup relations from the ideal perovskite type (Pm (3) over barm), which is the aristotype of the experimentally known CaMnO3 compound in the Pnma space group. Furthermore, additional structure candidates have been obtained using data mining. For each of the structure candidates, a local optimization on the ab initio level using density-functional theory (LDA, hybrid B3LYP) and the Hartree--Fock (HF) method was performed, and we find that several of the modifications may be experimentally accessible. In the high-pressure regime, we identify a post-perovskite phase in the CaIrO3 type, not previously observed in CaMnO3. Similarly, calculations at effective negative pressure predict a phase transition from the orthorhombic perovskite to an ilmenite-type (FeTiO3) modification of CaMnO3