There is a growing interest in the study of coupled plasma-liquid systems because of their applications to biomedicine, biological and chemical disinfection, agriculture, and other areas. Optimizing these applications requires a fundamental understanding of the coupling between phases. Though much progress has been made in this regard, there is still more to be done. One area that requires more research is the transport of electrons across the plasma-liquid interface. Some pioneering works (Rumbach et al 2015 Nat. Commun. 6, Rumbach et al 2015 J. Phys. D: Appl. Phys. 48 424001) have begun revealing the near-surface liquid characteristics of electrons. However, there has been little work to determine the near-surface gas phase electron characteristics. Without an understanding of the near-surface gas dynamics, modellers are left to make assumptions about the interfacial conditions. For instance it is commonly assumed that the surface loss or sticking coefficient of gas-phase electrons at the interface is equal to 1. In this work we explore the consequences of this assumption and introduce a couple of ways to think about the electron interfacial condition. In one set of simulations we impose a kinetic condition with varying surface loss coefficient on the gas phase interfacial electrons. In a second set of simulations we introduce a Henry's law like condition at the interface in which the gas-phase electron concentration is assumed to be in thermodynamic equilibrium with the liquid-phase electron concentration. It is shown that for a range of electron Henry coefficients spanning a range of known hydrophilic specie Henry coefficients, the gas phase electron density in the anode can vary by orders of magnitude. Varying reflection of electrons by the interface also has consequences for the electron energy profile; increasing reflection may lead to increasing thermalization of electrons depending on choices about the electron energy boundary condition. This variation in anode electron density and energy as a function of the interface characteristics could also lead to significant variation in near-surface gas chemistries when such reactions are included in the model; this could very well in turn affect the reactive species impinging on the liquid surface. We draw the conclusion that in order to make more confident model predictions about plasma-liquid systems, finer scale simulations and/or new experimental techniques must be used to elucidate the near-surface gas phase electron dynamics.

Two analytic traditions characterize fMRI language research. One relies on averaging activations across individuals. This approach has limitations: because of inter-individual variability in the locations of language areas, any given voxel/vertex in a common brain space is part of the language network in some individuals but in others, may belong to a distinct network. An alternative approach relies on identifying language areas in each individual using a functional 'localizer'. Because of its greater sensitivity, functional resolution, and interpretability, functional localization is gaining popularity, but it is not always feasible, and cannot be applied retroactively to past studies. To bridge these disjoint approaches, we created a probabilistic functional atlas using fMRI data for an extensively validated language localizer in 806 individuals. This atlas enables estimating the probability that any given location in a common space belongs to the language network, and thus can help interpret group-level activation peaks and lesion locations, or select voxels/electrodes for analysis. More meaningful comparisons of findings across studies should increase robustness and replicability in language research.