The Curing Kinetics of Multiscale [Ni(EDTA)]-2 Intercalated Zn-Al Layered Double Hydroxides: Glass Fiber–Epoxy Composite Prepreg

In the present research, the effect of Zn2Al layered double hydroxides (LDH) and nickel (II)-EDTA complex intercalated LDH (LDH-[Ni(EDTA)]-2) on the cure kinetics of glass fiber/epoxy prepreg (GEP) was explored using nonisothermal differential scanning calorimetry (DSC). The results showed that LDH caused a shift in the cure temperature toward lower temperatures while accelerating the curing of epoxy prepregs. The use of LDH-[Ni(EDTA)]-2 more profoundly influenced the acceleration of the curing process. The curing kinetics of prepregs was assessed through the differential isoconversional Friedman (FR) technique and the integration method of Flynn–Wall–Ozawa (FWO) and Kissinger–Akahira–Sunose (KAS). A decrease was detected in the E α value of glass fiber/LDH-[Ni(EDTA)]-2/epoxy (GELP) and glass fiber/LDH-[Ni(EDTA)]-2/epoxy (GELNiP) prepregs at small cure degrees relative to GEP, suggesting the catalytic effect of LDH or LDH-[Ni(EDTA)]-2 on the initial epoxy/amine reaction. Furthermore, LDH-[Ni(EDTA)]-2 performed better due to the catalyst role of nickel (II). Moreover, the activation energy exhibited lower reliance on the degree of conversion in the cases of GELP and GELNiP rather than pure epoxy prepregs. An autocatalytic model was used to evaluate the curing behavior of the system. Based on the results, the curing reaction of the epoxy prepreg can be described by the autocatalytic Šesták-Berggren model even after the incorporation of LDH or LDH-[Ni(EDTA)]-2. The kinetic parameters of the autocatalytic model (such as E α , A , m , n ) and the equations explaining the curing behavior of prepregs were introduced as well whose predictions were in line with the experimental findings.

Thermal Stability Analysis of Lithium-Ion Battery Electrolytes Based on Lithium Bis(trifluoromethanesulfonyl)imide-Lithium Difluoro(oxalato)Borate Dual-Salt

Lithium-ion batteries with conventional LiPF6 carbonate electrolytes are prone to failure at high temperature. In this work, the thermal stability of a dual-salt electrolyte of lithium bis(trifluoromethanesulfonyl)imide (LiTFSI) and lithium difluoro(oxalato)borate (LiODFB) in carbonate solvents was analyzed by accelerated rate calorimetry (ARC) and differential scanning calorimetry (DSC). LiTFSI-LiODFB dual-salt carbonate electrolyte decomposed when the temperature exceeded 138.5 °C in the DSC test and decomposed at 271.0 °C in the ARC test. The former is the onset decomposition temperature of the solvents in the electrolyte, and the latter is the LiTFSI-LiODFB dual salts. Flynn-Wall-Ozawa, Starink, and autocatalytic models were applied to determine pyrolysis kinetic parameters. The average apparent activation energy of the dual-salt electrolyte was 53.25 kJ/mol. According to the various model fitting, the thermal decomposition process of the dual-salt electrolyte followed the autocatalytic model. The results showed that the LiTFSI-LiODFB dual-salt electrolyte is significantly better than the LiPF6 electrolyte in terms of thermal stability.

Trend Analysis Modelling and Prediction of Epidemic COVID-19 for US, Italy, Spain and Pakistan

The evidence of Covid19 outbreak was first received in December 2019 in China and it spread out rapidly on the map of the world. The cases of Coronavirus are increasing day by day around the world due to which mortality rate raises hastily. In the matter of days, WHO declared Covid19 as pandemic of the decade. So far, it is controlled by taking strict precautions in terms of lockdown and supervised treatments at the hospital. As its epidemic is severely breaking the scale, there is a necessity to recognize and evaluate its extension in people on each new day. We collected time series data from January 22, to April 28, 2020 which includes the number of confirmed patients (CP) and reported deaths (RD) of 186 countries all around the world. We choose to evaluate the data for US, Italy, Spain and Pakistan. We are selecting here the data up to April 28, 2020, however the data is automatically updated from Humanitarian Data Exchange on daily basis for all the countries suffering from this pandemic. In this study, three parameters logistic (autocatalytic) model is applied to characterize the disease which determine the size of epidemic with the most populated hit cases around the world respectively and predict the life cycle of COVID 19 cases by using Gaussian based prediction model. It is determined that there are worst numbers of cases of Coronavirus that are found in US and the number of CPs and RDs grow exponentially around the world underneath Spain, Italy, UK and France etc. The epicentre of this pandemic was the city of Wuhan, China. The firm defence that has been taken is to quarantine the people and the patients were cured in organized hospitals.

Autocatalytic Model for Covid-19 Progression in a Country

Herewith we present a computational model for the forecasting of cumulative diagnosed cases of Covid-19 pneumonia within a country. The only explicit parameter of the model is the population density. The implicit parameter is a moving average ambient temperature, currently integrated into the kinetic constants. Other finer details pertaining to the mechanism of the pathogen SARS-CoV-2 spread within a given region are implicitly manifested in the exponent parameters derived from the non-linear fitting of the published data on Covid-19 occurrence. The performance of the model is demonstrated on a few selected countries, and on the Diamond Princess cruising ship outbreak. The model might be used as an aiding tool for the policy makers regarding the decisions on the containment measures and quarantine regime required.

Modelling the kinetics and structural property evolution of a versatile reaction: aqueous HCN polymerization

The structural characterization and kinetics of HCN polymers were studied and the Kamal autocatalytic model can describe this aqueous precipitation polymerization.

Light Induced Degradation of Nitrocellulose Lacquer Thin Films for Conservation of Art Objects

To better understand light induced changes in polymeric coatings commonly used to protect metal artifacts, this work details the decomposition of thin (∼100nm) nitrocellulose-based lacquer films on silver, copper, and gold. Samples were exposed to various wavelengths of light including, UVA (∼340nm), UVB (312nm), and UVC (254nm), under controlled temperature and humidity. Decomposition was characterized using reflection absorption spectroscopy (RAS) and monitoring infrared absorbance bands. The loss of NO2 functional groups was observed and the decrease was fit to a simple two step autocatalytic model involving primary and secondary decomposition steps. The decomposition rate under UVC light exposure was rapid and similar for all substrates. Rate constants for the primary and secondary steps were similar in magnitude and only mildly dependent on temperature. For UVB light exposure, all reaction rates were much slower and secondary decomposition was much faster relative to the primary decomposition step. Decomposition under all conditions resulted in the formation of oxidized species with an infrared spectrum similar to that of carboxylic acids.