Emergence of chaos in a spatially confined reactive system

In spatially restricted media, interactions between particles and local fluctuations of density can lead to important deviations of the dynamics from the unconfined, deterministic picture. In this context, we investigated how molecular crowding can affect the emergence of chaos in small reactive systems. We developed to this end an amended version of the Willamowski–Rössler model, where we account for the impenetrability of the reactive species. We analyzed the deterministic kinetics of this model and studied it with spatially-extended stochastic simulations in which the mobility of particles is included explicitly. We show that homogeneous fluctuations can lead to a destruction of chaos through a fluctuation-induced collision between chaotic trajectories and absorbing states. However, an interplay between the size of the system and the mobility of particles can counterbalance this effect so that chaos can indeed be found when particles diffuse slowly. This unexpected effect can be traced back to the emergence of spatial correlations which strongly affect the dynamics. The mobility of particles effectively acts as a new bifurcation parameter, enabling the system to switch from stationary states to absorbing states, oscillations or chaos

Nonlinear behavior and fluctuation-induced dynamics in the photosensitive Belousov–Zhabotinsky reaction

The photosensitive Belousov–Zhabotinsky (pBZ) reaction has been used extensively to study the properties of chemical oscillators. In particular, recent experiments revealed the existence of complex spatiotemporal dynamics for systems consisting of coupled micelles (V ≺ 10−21 L) or droplets (V ≈ [10−8–10−11] L) in which the pBZ reaction takes place. These results have been mostly understood in terms of reaction–diffusion models. However, in view of the small size of the droplets and micelles, large fluctuations of concentrations are to be expected. In this work, we investigate the role of fluctuations on the dynamics of a single droplet with stochastic simulations of an extension of the Field–Körös–Noyes (FKN) model taking into account the photosensitivity. The birhythmicity and chaotic behaviors predicted by the FKN model in the absence of fluctuations become transient or intermittent regimes whose lifetime decreases with the size of the droplet. Simple oscillations are more robust and can be observed even in small systems (V > 10−12 L), which justifies the use of deterministic models in microfluidic systems of coupled oscillators. The simulations also reveal that fluctuations strongly affect the efficiency of inhibition by light, which is often used to control the kinetics of these systems: oscillations are found for parameter values for which they are supposed to be quenched according to deterministic predictions

Coding and decoding of oscillatory Ca2+ signals

About 30 years after their first observation, Ca2+ oscillations are now recognised as a universal mechanism of signal transduction. These oscillations are driven by periodic cycles of release and uptake of Ca2+ between the cytoplasm and the endoplasmic reticulum. Their frequency often increases with the level of stimulation, which can be decoded by some molecules. However, it is becoming increasingly evident that the widespread core oscillatory mechanism is modulated in many ways, depending on the cell type and on the physiological conditions. Interplay with inositol 1,4,5-trisphosphate metabolism and with other Ca2+ stores as the extracellular medium or mitochondria can much affect the properties of these oscillations. In many cases, these finely tuned characteristics of Ca2+ oscillations impact the physiological response that is triggered by the signal. Moreover, oscillations are intrinsically irregular. This randomness can also be exploited by the cell. In this review, we discuss evidences of these additional manifestations of the versatility of Ca2+ signalling

Deterministic limit of intracellular calcium spikes

In nonexcitable cells, global Ca2þ spikes emerge from the collective dynamics of clusters of Ca2þ channels that are coupled by diffusion. Current modeling approaches have opposed stochastic descriptions of these systems to purely deterministic models, while both paradoxically appear compatible with experimental data. Combining fully stochastic simulations and mean-field analyses, we demonstrate that these two approaches can be reconciled. Our fully stochastic model generates spike sequences that can be seen as noise-perturbed oscillations of deterministic origin, while displaying statistical properties in agreement with experimental data. These underlying deterministic oscillations arise from a phenomenological spike nucleation mechanism

Reconstructing stochastic attractors from nanoscale experiments on a non-equilibrium reaction

We studied the catalytic NO2(g) + H2(g)/Pt system on model platinum catalysts with nanoscale spatial resolution by means of field emission microscopy (FEM). While the surface of the catalyst is in a non-reactive state at low H2 partial pressure, bursts of activity are observed when increasing this parameter. These kinetic instabilities subsequently evolve towards self-sustained periodic oscillations for a wide range of pressures. Combining time series analyses and numerical simulations of a simple reaction model, we clarify how these observations fit in the traditional classification of dynamical systems. In particular, reconstructions of the probability density around oscillating trajectories show that the experimental system defines a crater-like structure in probability space. The experimental observations thus correspond to a noise-perturbed limit cycle emerging from a nanometric reactive system. This conclusion is further supported by comparison with stochastic simulations of the proposed chemical model. The obtained results and simulations pave the way towards a better understanding of reactive nanosystems

Reconstructing stochastic attractors from nanoscale experiments on a non-equilibrium reaction

We studied the catalytic NO2(g) + H2(g)/Pt system on model platinum catalysts with nanoscale spatial resolution by means of field emission microscopy (FEM). While the surface of the catalyst is in a non-reactive state at low H2 partial pressure, bursts of activity are observed when increasing this parameter. These kinetic instabilities subsequently evolve towards self-sustained periodic oscillations for a wide range of pressures. Combining time series analyses and numerical simulations of a simple reaction model, we clarify how these observations fit in the traditional classification of dynamical systems. In particular, reconstructions of the probability density around oscillating trajectories show that the experimental system defines a crater-like structure in probability space. The experimental observations thus correspond to a noise-perturbed limit cycle emerging from a nanometric reactive system. This conclusion is further supported by comparison with stochastic simulations of the proposed chemical model. The obtained results and simulations pave the way towards a better understanding of reactive nanosystems

Stochastic numerical models of oscillatory phenomena

The use of time series for integrating ordinary differential equations to model oscillatory chemical phenomena has shown benefits in terms of accuracy and stability. In this work, we suggest to adapt also the model in order to improve the matching of the numerical solution with the time series of experimental data. The resulting model is a system of stochastic differential equations. The stochastic nature depends on physical considerations and the noise relies on an arbitrary function which is empirically chosen. The integration is carried out through stochastic methods which integrate the deterministic part by using one-step methods and approximate the stochastic term by employing Monte Carlo simulations. Some numerical experiments will be provided to show the effectiveness of this approach