IN VITRO IN VIVO STUDIES ON FLOATING MICROSPHERES FOR GASTRORETENTIVE DRUG DELIVERY SYSTEM: A REVIEW

The purpose of writing this review on gastroretentive drug delivery systems (GRDDS) was to compile the recent literature with a special focus on various gastroretentive approaches that have recently become leading methodologies in the field of site-specific orally administered controlled release drug delivery. One of the complex processes in the human body is gastric emptying, as it is highly variable, which makes the in vivo performance of the drug delivery systems uncertain. GRDDS has gained immense popularity in the field of oral drug delivery recently. It is a widely employed approach to retain the dosage form in the stomach for an extended period of time and release the drug slowly that can address many challenges associated with the conventional oral delivery system. Conventional drug delivery systems may not overcome the issues imposed by the gastrointestinal tract (GIT) such as incomplete release of drugs, decrease in dose effectiveness, and frequent dose requirement. To overcome this variability, a controlled drug delivery system with a prolonged gastric residence time of >12 h in the stomach can be of great practical importance for drugs with an absorption window in the upper small intestine. GRDFs enable prolonged and continuous release of the drug to the upper part of the GIT and thus significantly extend the duration of drug release and improve the bioavailability of drugs that have a narrow therapeutic window; by this way, they prolong dosing interval and increase compliance

Heat Transfer at the Interface of Graphene Nanoribbons with Different Relative Orientations and Gaps

Because of their high thermal conductivity, graphene nanoribbons (GNRs) can be employed as fillers to enhance the thermal transfer properties of composite materials, such as polymer-based ones. However, when the filler loading is higher than the geometric percolation threshold, the interfacial thermal resistance between adjacent GNRs may significantly limit the overall thermal transfer through a network of fillers. In this article, reverse non-equilibrium molecular dynamics is used to investigate the impact of the relative orientation (i.e., horizontal and vertical overlap, interplanar spacing and angular displacement) of couples of GNRs on their interfacial thermal resistance. Based on the simulation results, we propose an empirical correlation between the thermal resistance at the interface of adjacent GNRs and their main geometrical parameters, namely the normalized projected overlap and average interplanar spacing. The reported correlation can be beneficial for speeding up bottom-up approaches to the multiscale analysis of the thermal properties of composite materials, particularly when thermally conductive fillers create percolating pathways

The impact of physicochemical features of carbon electrodes on the capacitive performance of supercapacitors: A machine learning approach

Hybrid electric vehicles and portable electronic systems use supercapacitors for energy storage owing to their fast charging discharging rates, long life cycle, and low maintenance. Specific capacitance is regarded as one of the most important performance-related characteristics of a supercapacitor's electrode. In the current study, Machine Learning (ML) algorithms were used to determine the impact of various physicochemical properties of carbon-based materials on the capacitive performance of electric double-layer capacitors. Published experimental datasets from 147 references (4899 data entries) were extracted and then used to train and test the ML models, to determine the relative importance of electrode material features on specific capacitance. These features include current density, pore volume, pore size, presence of defects, potential window, specific surface area, oxygen, and nitrogen content of the carbon-based electrode material. Additionally, categorical variables as the testing method, electrolyte, and carbon structure of the electrodes are considered as well. Among five applied regression models, an extreme gradient boosting model was found to best correlate those features with the capacitive performance, highlighting that the specific surface area, the presence of nitrogen doping, and the potential window are the most significant descriptors for the specific capacitance. These findings are summarized in a modular and open-source application for estimating the capacitance of supercapacitors given, as only inputs, the features of their carbon-based electrodes, the electrolyte and testing method. In perspective, this work introduces a new wide dataset of carbon electrodes for supercapacitors extracted from the experimental literature, also giving an instance of how electrochemical technology can benefit from ML models.Comment: Manuscript and associated Supplementary Informatio

Nanoscale thermal properties of carbon nanotubes/epoxy composites by atomistic simulations

Carbon nanotubes/epoxy composites are increasingly employed in several industrial fields, because of the enhanced material properties provided by the nanofillers. In particular, the thermal conductivity of these nanocomposites is determined by heat transfer mechanisms occurring over multiple scales, thus causing a complex relation between effective response and microscopic characteristics of the material. Here, the thermal properties of epoxy composites reinforced by carbon nanotubes are investigated using atomistic simulations. For a better understanding of how the effective thermal conductivity arises from the characteristics of the composite at the nanoscale, the thermal properties of its constituents are studied separately according to different geometrical, physical and chemical characteristics. The thermal conductivity of carbon nanotubes and epoxy resin alone is first investigated by molecular dynamics; then, the Kapitza resistance at the nanotube-nanotube and nanotube-epoxy interfaces is studied as well. The effective thermal conductivity of the carbon nanotubes/epoxy composite is finally computed and the observed behavior interpreted on the basis of the properties of the nanofillers, matrix and interfaces alone. Results - verified against effective medium theory predictions - show that, for the considered configurations, the effective thermal conductivity of the nanocomposite increases with the nanotube length and volume fraction, with the curing degree of the epoxy and system temperature. In perspective, the presented approach could be employed to investigate other constitutive materials or properties of nanocomposites

Atomistic to Mesoscopic Modelling of Thermophysical Properties of Graphene-Reinforced Epoxy Nanocomposites

This research addresses the need for a multiscale model for the determination of the thermophysical properties of nanofiller-enhanced thermoset polymer composites. Specifically, we analyzed the thermophysical properties of an epoxy resin containing bisphenol-A diglyceryl ether (DGEBA) as an epoxy monomer and dicyandiamide (DICY) and diethylene triamine (DETA) as cross-linking agents. The cross-linking process occurs at the atomistic scale through the formation of bonds among the reactive particles within the epoxy and hardener molecules. To derive the interatomic coarse-grained potential for the mesoscopic model and match the density of the material studied through atomic simulations, we employed the iterative Boltzmann inversion method. The newly developed coarse-grained molecular dynamics model effectively reproduces various thermophysical properties of the DGEBA-DICY-DETA resin system. Furthermore, we simulated nanocomposites made of the considered epoxy additivated with graphene nanofillers at the mesoscopic level and verified them against continuum approaches. Our results demonstrate that a moderate amount of nanofillers (up to 2 wt.%) increases the elastic modulus and thermal conductivity of the epoxy resin while decreasing the Poisson’s ratio. For the first time, we present a coarse-grained model of DGEBA-DICY-DETA/graphene materials, which can facilitate the design and development of composites with tunable thermophysical properties for a potentially wide range of applications, e.g., automotive, aerospace, biomedical, or energy ones

Vaccination Status and Outcome of Patients at a Dedicated COVID-19 Centre, Delhi, India: A Retrospective Study

Introduction: Coronavirus Disease-2019 (COVID-19) vaccine provides strong protection against transmission, serious illness, hospitalisation, and death. As India carried out robust vaccination drive covering more than two third of its population, the study was aimed to highlight the effects of vaccination status of patient on the outcome of COVID-19 infection. Aim: To describe the relation of vaccination with disease severity and its outcome during the third wave of COVID-19. Materials and Methods: It was a single-centre retrospective, cross-sectional study conducted in a dedicated COVID-19 Hospital (Guru Tegh Bahadur Hospital) in Delhi, India. A total of 257 patients were admitted between 10th January 2022 to 9th February 2022, and 246 were included in the study. For each individual, demographic, and clinical data was collected. Vaccination data was extracted via the CoWin platform which included vaccine type, as well as date of administration. The profile of patients was established based on clinical examination, laboratory data, nursing record and radiological record during the course of hospitalisation. The clinical outcome was described as discharge, length of hospital stays, and in-hospital death in relation to the vaccination status. Statistical analysis was done using Statistical Package for the Social Sciences (SPSS), version 22.0. Results: Total of 246 patients were divided into three groups- 97 were fully vaccinated, 46 were partially vaccinated and 103 were unvaccinated. Both vaccinated and unvaccinated groups had similar percentage of co-morbidities i.e. 61.3% vs 63.5%. Those who were fully vaccinated were more likely to maintain saturation at room air 30.9% vs 26.1% vs 3.9%, had lesser requirements of mechanical ventilation (6.2% vs 15.2% vs 21.4%), shorter duration of hospital stay (4.2 vs 5.3 vs 7.2 days), and lesser mortality (9.3% vs 21.7% vs 33%) as compared to the partially vaccinated and unvaccinated patients respectively. Conclusion: The beneficial effect of the vaccination was observed in severity, mortality, morbidity, and lesser number of hospitalisations. Hence, vaccination coverage was critical in reducing the severity in reducing the and the hospitalisation in third wave of COVID-19

Mesoscopic modeling and experimental validation of thermal and mechanical properties of polypropylene nanocomposites reinforced by graphene-based fillers

The development of nanocomposites relies on structure-property relations, which necessitate multiscale modeling approaches. This study presents a modelling framework that exploits mesoscopic models to predict the thermal and mechanical properties of nanocomposites starting from their molecular structure. In detail, mesoscopic models of polypropylene (PP) and graphene based nanofillers (Graphene (Gr), Graphene Oxide (GO), and reduced Graphene Oxide (rGO)) are considered. The newly developed mesoscopic model for the PP/Gr nanocomposite provides mechanistic information on the thermal and mechanical properties at the filler-matrix interface, which can be then exploited to enhance the prediction accuracy of traditional continuum simulations by calibrating the thermal and mechanical properties of the filler-matrix interface. Once validated through a dedicated experimental campaign, this multiscale model demonstrates that with the modest addition of nanofillers (up to 2 wt.%), the Young's modulus and thermal conductivity show up to 35% and 25% enhancement, respectively, while the Poisson's ratio slightly decreases. Among the different combinations tested, PP/Gr nanocomposite shows the best mechanical properties, whereas PP/rGO demonstrates the best thermal conductivity. This validated mesoscopic model can contribute to the development of smart materials with enhanced mechanical and thermal properties based on polypropylene, especially for mechanical, energy storage, and sensing applications.Comment: Manuscript (37 pages) and Supplementary Information (8 pages