Growth, structural, thermal, and optical characteristics of L-asparagine monohydrate doped magnesium sulphate heptahydrate semiorganic crystals

A novel semi-organic crystal has been grown using slow evaporation technique by doping organic compound L-asparagine monohydrate (C4H8N2O3·H2O) with inorganic material Magnesium sulphate heptahydrate (MgSO4·7H2O). The crystallographic parameters like strain, dislocation density and crystallite size were calculated by powder X-ray diffraction method. Functional groups were identified and bond length, force constants were calculated from FT-IR spectroscopy. Energy dispersive X-ray (EDX) analysis was used to identify the constituent elements of the crystal. Kinetic and thermodynamic parameters, such as, activation energy Ea, change in Gibb's free energy (ΔG) and change in enthalpy (ΔH) have been determined by thermogravimetric analysis (TGA) analysis. Ea, ΔH and ΔG show positive values and change in entropy (ΔS) shows negative ones. The thermal degradation behavior of the crystals has been analyzed by differential scanning calorimetry (DSC) analysis. Various optical constants such as optical band gap, lattice dielectric constant, absorbance, extinction coefficient, the ratio of free charge carrier concentration to the effective mass, Urbach energy, optical and electrical conductivities were estimated from UV-vis transmittance data. High optical conductivity (1010 s-1) justifies the good photo response nature of the semi-organic crystal.

Fast and reliable analysis of pH-responsive nanocarriers for drug delivery using microfluidic tools

During the last decades, there has been growing interest in the application of functionalized mesoporous nanomaterials as stimuli-responsive carriers for drug delivery. However, at present there is not a standardized methodology to evaluate their performance. The limitations of the different techniques reported in literature give rise to the necessity for new, simple, and cost-effective alternatives. This work constitutes a step forward in the development of advanced in vitro procedures for testing the behavior of nanocarriers, proposing a novel microfluidic platform. To test the capacity of the reported tool, the performance of amino-functionalized MCM-41 nanoparticles has been assessed. These materials show a pH-responsive mechanism, which prevents the drug release at acidic conditions, maximizing its distribution at neutral pH, thus, the selected release medium mimicked gastrointestinal conditions. As a first approximation, the delivery of Ru(bipy)32+ was evaluated, proving the advantages of the proposed microfluidic system: i) continuous flow of particles and media, ii) rigorous control of the residence time, temperature and pH, iii) enhanced mixing, iv) possibility to simulate different human body conditions and, v) possible integration with the continuous synthesis of nanocarriers. Finally, the microfluidic tool was used to analyze the delivery of the anti-inflammatory drug ibuprofen.

Thermal degradation model of used surgical masks based on machine learning methodology

Background

The COVID-19 pandemic has leveraged facial masks to be one of the most effective measures to prevent the spread of the virus, which thereby has exponentially increased the usage of facial masks that lead to medical waste mismanagements which pose a serious threat to life. Thermal degradation or pyrolysis is an effective treatment method for the used facial mask wastes and this study aims to investigate the thermal degradation of the same.

Methods

Predicted the TGA experimental curves of the mask components using a Machine Learning model known as Artificial Neural Network (ANN).

Significant findings

Three different parts of the mask namely- ribbon, body, and corner were separated and used for the analysis. The thermal degradation behavior is studied using Thermogravimetric Analysis (TGA) and this is crucial for determining the reactivity of the individual mask components as they are subjected to a range of temperatures. Using the curves obtained from TGA, kinetic parameters such as Activation energy (E) and Pre-exponential factor (A) were estimated using the Coats-Redfern model-fitting method. Using the determined kinetic parameters, thermodynamic quantities such as a change in Enthalpy (ΔH), Entropy (ΔS), and Gibbs-Free energy (ΔG) were also calculated. Since TGA is a costly and time-consuming process, this study attempted to predict the TGA experimental curves of the mask components using a Machine Learning model known as Artificial Neural Network (ANN). The dataset obtained at a heating rate of 10°C/min was used to train the 3 different neural networks corresponding to the mask components and it showed an excellent agreement with experimental data (R² > 0.99). Through this study, a complex chemical process such as thermal degradation was modelled using Machine Learning based on available experimental parameters without delving into the intricacies and complexities of the process.

Influence of varying thermal treatment on bioactive material with equal Ca/P ratio: A local drug delivery system for bone regeneration

Designing a biomaterial with excellent bioactivity, biocompatibility, mechanical strength, porosity, and osteogenic properties is essential to incorporate therapeutic agents in order to promote efficient bone regeneration. The work intended to prepare bioactive glass with tailor-made equal Ca/P (CP) ratio to obtain clinophosinaite (Cpt) as dominant phase. Clinophosinaite (Na₃ CaPSiO₇ ) is one of the rarest phases of bioactive glass (BG), which is supposed to play key role in bioactivity. The novelty of this work is to track the required sintering temperature to attain equimolar calcium phosphate-containing clinophosinaite phase and its behavior. Further, its consequent physicochemical and biological properties were analyzed. Phase transition from Rhenanite to Cpt, and later the Cpt emerged as dominant phase with increase of calcination temperature from 700 to 1000°C was studied. The quantifying evolution of Cpt with Rhenanite over increasing annealing temperature also results with the major morphological modifications. BET analysis confirmed the surface area and porosity (Type-IV mesoporous) were gradually elevated upto 900°C, which had contrary effect on mechanical strength. Formation of hydroxyl carbonate apatite (HCA) layer confirmed the bioactivity of the prepared samples at varying time intervals. The CP samples demonstrated better hemocompatibility in post-immersion (i.e., less than 1% of lysis) when compared with pre-immersion. Enhanced protein adsorption and cumulative release (85%) of Simvastatin (SIM) drug was attained at 900°C treatment.

Thermal Stability of Polycaprolactone Grafted Densely with Maleic Anhydride Analysed Using the Coats-Redfern Equation

The plastic waste problem has recently attracted unprecedented attention globally. To reduce the adverse eff ects on environments, biodegradable polymers have been studied to solve the problems. Poly(ε-caprolactone) (PCL) is one of the common biodegradable plastics used on its own or blended with natural polymers because of its excellent properties after blending. However, PCL and natural polymers are difficult to blend due to the polymers' properties. Grafted polymerization of maleic anhydride and dibenzoyl peroxide (DBPO) with PCL is one of the improvements used for blending immiscible polymers. In this study, we first focused on the effects of three factors (stirring time, maleic anhydride (MA) amount and benzoyl peroxide amount) on the grafting ratio with a maximum value of 4.16% when applying 3.000 g MA and 1.120 g DBPO to 3.375 g PCL with a stirring time of 18 h. After that, the grafting condition was studied based on the kinetic thermal decomposition and activation energy by the Coats-Redfern method. The optimal fitting model was confirmed by the determination coefficient of nearly 1 to explain the contracting volume mechanism of synthesized PCL-g-MA. Consequently, grafted MA hydrophilically augmented PCL as the reduced contact angle of water suggests, facilitating the creation of a plastic-biomaterial composite.

SPHRINT - Printing Drug Delivery Microspheres from Polymeric Melts

This paper describes a simple, straightforward, and rapid method for producing microspheres from molten polymers by merely printing them in an inkjet-like manner onto a superoleophobic surface (microsphere printing, hence SPHRINT). Similar to 3D printing, a polymer melt is deposited onto a surface; however, in contrast to 2D or 3D printing, the surface is not wetted (i.e. exhibiting high contact angles with liquids, above 150°, due to its low surface energy), resulting in the formation of discrete spherical microspheres. In this study, microspheres were printed using polycaprolactone and poly(lactic-co-glycolic acid) loaded with a model active pharmaceutical ingredient-ibuprofen (IBU). The formation of microspheres was captured by high-speed imaging and was found to involve several physical phenomena characterized by non-dimensional numbers, including the thinning and breakup of highly viscous, weakly elastic filaments, which are first to be described in pure polymer melts. The resulting IBU-loaded microspheres had higher sphericity, reproducible sizes and shapes, and superior drug encapsulation efficiencies with a distinctly high process yield (>95%) as compared to the conservative solvent-based methods used presently. Furthermore, the microspheres showed sustained release profiles.