Caracterização do processo de gelificação de soluções quitosana utilizando reometria e espalhamento dinâmico da luz

Gels consist of soft materials with vast use in several activities, such as in pharmaceutical industry, food science, and coatings/textile applications. In order to obtain these materials, the process of gelification, that can be physical (based on physical interactions) and/or chemical (based on covalent crosslinking), has to be carried out. In this work we used dynamic light scattering (DLS) and rheometry to monitor the covalent gelification of chitosan solutions by glutaraldehyde. Intensity correlation function (ICF) data was obtained from DLS and the exponential stretched Kohrausch-William-Watts function (KWW) was fitted to them. The parameters of the KWW equation, β, Γ and C were evaluated. These methods were effective in clarifying the process of sol-gel transition, with the emergence of non-ergodicity, and determining the range of gelation observed in about 10-20 minutes. The dependence between apparent viscosity on reaction time was used to support the discussion proposed.

O paradoxo da superdifusão de uma caminhada aleatória com memória exponencial

The random walk models with temporal correlation (i.e. memory) are of interest in the study of anomalous diffusion phenomena. The random walk and its generalizations are of prominent place in the characterization of various physical, chemical and biological phenomena. The temporal correlation is an essential feature in anomalous diffusion models. These temporal long-range correlation models can be called non-Markovian models, otherwise, the short-range time correlation counterparts are Markovian ones. Within this context, we reviewed the existing models with temporal correlation, i.e. entire memory, the elephant walk model, or partial memory, alzheimer walk model and walk model with a gaussian memory with profile. It is noticed that these models shows superdiffusion with a Hurst exponent H > 1/2. We study in this work a superdiffusive random walk model with exponentially decaying memory. This seems to be a self-contradictory statement, since it is well known that random walks with exponentially decaying temporal correlations can be approximated arbitrarily well by Markov processes and that central limit theorems prohibit superdiffusion for Markovian walks with finite variance of step sizes. The solution to the apparent paradox is that the model is genuinely non-Markovian, due to a time-dependent decay constant associated with the exponential behavior. In the end, we discuss ideas for future investigations.