Effects of dissolved gases on partial anodic passivation phenomena at copper microelectrodes immersed in aqueous NaCl

Anodic passivation for copper exposed to aqueous NaCl (model seawater) is rate limited by diffusion of a poorly soluble Cu(I) chloro species. As a result, a protective layer of CuCl forms on copper metal (with approx. 1 μm thickness) that is then put under strain at more positive applied potentials with explosive events causing current spikes and particulate product expulsion. In this report, the mechanism for this explosive film rupture and particle expulsion process is shown to occur (i) in the absence of underlying anodic gas evolution, and (ii) linked to the presence/nature of gaseous solutes. The film rupture event is proposed to be fundamentally dependent on gas bubble nucleation (triggered by the release of interfacial stress) with surface tension effects by dissolved gases affecting the current spike pattern. Oxygen O2, hydrogen H2, and helium He suppress current spikes and behave differently to argon Ar, nitrogen N2, and carbon dioxide CO2, which considerably enhance current spikes. Vacuum-degassing the electrolyte solution results in behaviour very similar to that observed in the presence of helium. The overall corrosion rate for copper microelectrodes is compared and parameters linked to passivation and corrosion processes are discussed.</p

Forecasting resilience profiles of the run-up to regime shifts in nearly-one-dimensional systems

The forecasting of sudden, irreversible shifts in natural systems is a challenge of great importance, whose realization could allow pre-emptive action to be taken to avoid or mitigate catastrophic transitions, or to help systems adapt to them. In recent years, there have been many advances in the development of such early warning signals. However, much of the current toolbox is based around the tracking of statistical trends and therefore does not aim to estimate the future time scale of transitions or resilience loss. Metric-based indicators are also difficult to implement when systems have inherent oscillations which can dominate the indicator statistics. To resolve these gaps in the toolbox, we use additional system properties to fit parsimonious models to dynamics in order to predict transitions. Here, we consider nearly-one-dimensional systems-higher dimensional systems whose dynamics can be accurately captured by one-dimensional discrete time maps. We show how the nearly one-dimensional dynamics can be used to produce model-based indicators for critical transitions which produce forecasts of the resilience and the time of transitions in the system. A particularly promising feature of this approach is that it allows us to construct early warning signals even for critical transitions of chaotic systems. We demonstrate this approach on two model systems: of phosphorous recycling in a shallow lake, and of an overcompensatory fish population.</p