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João Valeriano

Publications and source records attributed to João Valeriano.

2 recordsLinked to original sources

Flow spatial structure determines pattern instabilities in nonlocal models of population dynamics

We investigate how environmental flows influence spatial pattern formation and population dynamics using two nonlocal models of population dynamics, which we couple to two different stationary flows. Combining numerical simulations and analytical approximations, we show that the spatial structure of the flow's velocity field determines the pattern formation instability. For a simple shear flow, where one of the primary axes of the population pattern can become aligned with the flow, the onset of pattern formation remains unaffected. In contrast, a vortex flow delays the pattern instability relative to the no-flow case. The velocity field, therefore, interacts with the spatial feedbacks responsible for pattern formation in complex ways, which also leads to different oscillatory time series of population abundance. In some cases, the population undergoes regular oscillations with a characteristic frequency, while in others, the dynamics exhibits long erratic transients with no well-defined period before settling into a more regular behavior.

q-bio.PE↗

Colloidal structure, energy extensivity and Monte Carlo sampling properties of improved short-range interaction models for surfactant-coated magnetic nanoparticles

The standard DLVO theory offers a limited description of ionic-surfacted magnetic colloids in near aggregation regimes. Correcting the electrical double layer term for ionic surfactants is not enough to successfully simulate the systems. The correction of the van der Waals energy divergence at short interparticle distances is fundamental for proper Monte Carlo sampling of nanoparticles' configurations. We compare different short-range interaction models and show that a more detailed model leads to Monte Carlo simulations that better match theoretical expectations. Studying the energy scaling with the number of particles, we observe a slight deviation from energy extensivity across all models, small but still detectable via Akaike's information criterion. The more detailed model predicts a strong effect of particle-size dispersity on the transition between overall attraction and repulsion. More precise modeling can significantly affect numerical predictions, in particular, the effect of particle-size dispersity on the spatial structure of colloids with high volume fraction. This emphasizes the importance of nailing down better models for describing complex colloidal dispersions.

cond-mat.soft↗