RESUMEN
The fracture of polymer networks is tied to the molecular behavior of strands within the network, yet the specific molecular-level processes that determine the mechanical limits of a network remain elusive. Here, the question of reactivity-guided fracture is explored in otherwise indistinguishable end-linked networks by tuning the relative composition of strands with two different mechanochemical reactivities. Increasing the substitution of less mechanochemically reactive ("strong") strands into a network comprising more reactive ("weak") strands has a negligible impact on the fracture energy until the strong strand content reaches approximately 45%, at which point the fracture energy sharply increases with strong strand content. This aligns with the measured strong strand percolation threshold of 48 ± 3%, revealing that depercolation, or the loss of a percolated network structure, is a necessary criterion for crack propagation in a polymer network. Coarse-grained fracture simulations agree closely with the tearing energy trend observed experimentally, confirming that weak strand scissions dominate the failure until the strong strands approach percolation. The simulations further show that twice as many strands break in a mixture than in a pure network.
RESUMEN
Since the starting of the year 2020, the whole world is facing a challenge due to an outbreak of an unprecedented COVID-19 pandemic owing to a novel coronavirus. Here, a modified susceptible-infected-recovered-dead model has been used to analyze the time series data of the pandemic for five countries. It is established that the present model is capable of simultaneously explaining the temporal evolution of active-infected, recovered, and dead population of all these five countries. The key parameters governing the temporal evolution of the spread of this pandemic are estimated and compared.
