VALIDATED STABILITY INDICATING SPECTROSCOPIC METHOD FOR ESTIMATION OF DEGRADATION BEHAVIOUR OF VALSARTAN AND HYDROCHLOROTHIAZIDE IN TABLET FORMULATION

A simple, accurate and precise UV spectrometric method has been developed for the simultaneous determination of valsartan and hydrochlorothiazide in tablet dosage form. Spectra of valsartan and hydrochlorothiazide in methanol and water (50:50 V/V) show λ max at 250.0 nm and 271.4 nm, respectively. Valsartan and hydrochlorothiazide are subjected to various stress conditions like acid, alkali, thermal and photolytic degradation. Beer’s law was obeyed in concentration range of 4- 24 µg mL-1 for valsartan and 0.5-3 µg mL-1 for hydrochlorothiazide at their respective wavelengths. The proposed method was successfully applied to tablet dosage form for determination of both drugs. The percentage recovery of valsartan and hydrochlorothiazide were found to be 100.19 % and 99.51 %, respectively. A novel accurate and precise stability indicating spectroscopic method has been developed for estimation of valsartan and hydrochlorothiazide.

Predicting the inhibition efficiencies of magnesium dissolution modulators using sparse machine learning models

The degradation behaviour of magnesium and its alloys can be tuned by small organic molecules. However, an automatic identification of effective organic additives within the vast chemical space of potential compounds needs sophisticated tools. Herein, we propose two systematic approaches of sparse feature selection for identifying molecular descriptors that are most relevant for the corrosion inhibition efficiency of chemical compounds. One is based on the classical statistical tool of analysis of variance, the other one based on random forests. We demonstrate how both can—when combined with deep neural networks—help to predict the corrosion inhibition efficiencies of chemical compounds for the magnesium alloy ZE41. In particular, we demonstrate that this framework outperforms predictions relying on a random selection of molecular descriptors. Finally, we point out how autoencoders could be used in the future to enable even more accurate automated predictions of corrosion inhibition efficiencies.

DEGRADATION OF NONWOVEN FABRICS SUITABLE FOR WET WIPES BURIED IN SOIL

In this research, biodegradation behaviour of nonwoven fabrics suitable for wet wipes having different fibre types such as regenerated cellulose (viscose and Tencel), polyethylene terephthalate (PET) and their blends were investigated. Each nonwoven fabric was buried in soil and test samples were controlled in regular periods. Visual appearance was reported and examined by photographs and microscopic views. According to the changes in visual appearance and weight loss, biodegradation was examined in a systematic way. It has been observed that regenerated cellulose nonwoven fabrics and the PET nonwoven fabrics show big difference under the same degradation conditions. PET fibre content delays biodegradation in the soil and degradation behaviour is similar the content of PET fibre in fabric structure. The higher PET, lower degradation, and the higher cellulosic fibre, the higher degradation was determined for nonwoven fabrics suitable for wet wipes.

Crystallization and degradation behaviour of multiblock copolyester blends in Langmuir monolayers

Supporting the wound healing of soft tissues requires fixation devices becoming more elastic while degrading. To address this unmet need, we designed a blend of degradable multiblock copolymers, which is cross-linked by PLA stereocomplexation combining two soft segments differing substantially in their hydrolytic degradation rate. The degradation path and concomitant structural changes are predicted by Langmuir monolayer technique. The fast hydrolysis of one soft segment leads to a decrease of the total polymer mass at constant physical cross-linking density. The corresponding increase of the average spacing between the network nodes suggests the targeted increase of the blend’s flexibility. Graphic abstract

Factorial experimentation on photodegradation of historical paper by polychromatic visible radiation

Quantification of the degradation behaviour of heritage objects is essential to manage the rate of degradation and hence optimise their lifetime. In this research, a 23 full factorial experiment was carried out to deepen the understanding of the photodegradation of historical rag paper induced by continuous polychromatic visible radiation. Oxygen concentration, relative humidity and illuminance were investigated as the three environmental factors of primary concern. The effects of these factors on the rate constant of change in diffuse reflectance and tristimulus discolouration were investigated by analysis of variance and multiple linear regression. The three main effects were found to contribute the most to the rate of photodegradation of historical paper, among which relative humidity played the most important role whereas illuminance played the least. This observation is likely to hold when extrapolating the experimental conditions to real conditions in collection storage and display.