RESUMEN
Gas diffusion layers (GDLs) are usually coated with a hydrophobic agent to achieve a delicate balance between liquid and gas phases to maximize mass transport. Yet, most GDL numerical models to date have assumed an average contact angle for all materials, thereby eliminating the possibility of studying the role of the polytetrafluoroethylene (PTFE) content. This study introduces two mixed wettability algorithms to predict the mixed wetting behavior of GDLs composed of multiple materials. The algorithms employ contact angle and distance to solid materials to determine the critical capillary pressure for each pore voxel. The application of the algorithms to the estimation of capillary pressure vs saturation curves for two GDLs, namely, a micro-computed tomography (µ-CT) reconstructed SGL 39BA GDL and a stochastically reconstructed Toray 120C GDL, showed that, in agreement with experimental data, the addition of PTFE resulted in a decrease in saturation at a given capillary pressure. For Toray-120C, the mixed wettability model was capable of reproducing experimentally observed features in the intrusion curve at low saturation that could not be reproduced with a single wettability model, providing a clear link between PTFE coverage and intrusion at low saturation. Numerical results also predicted an increased breakthrough pressure and a decrease in saturation with increasing PTFE, in agreement with experimental observations. The decreased saturation at breakthrough improves gas transport through the layer while maintaining the layer's ability to remove water. Diffusivity simulations confirm the increase in diffusivity at breakthrough with increasing PTFE, thereby providing a rationale for the addition of PTFE, as well as for the optimal amount. This study emphasizes the importance of multimaterial wetting models and calls for more detailed investigations into PTFE and ionomer distributions in GDLs and catalyst layers, respectively.
RESUMEN
Rapid environmental change is reshaping ecosystems and driving species loss globally. Carnivore populations have declined and retracted rapidly and have been the target of numerous translocation projects. Success, however, is complicated when these efforts occur in novel ecosystems. Identifying refuges, locations that are resistant to environmental change, within a translocation framework should improve population recovery and persistence. American martens (Martes americana) are the most frequently translocated carnivore in North America. As elsewhere, martens were extirpated across much of the Great Lakes region by the 1930s and, despite multiple translocations beginning in the 1950s, martens remain of regional conservation concern. Surprisingly, martens were rediscovered in 2014 on the Apostle Islands of Lake Superior after a putative absence of >40 yr. To identify the source of martens to the islands and understand connectivity of the reintroduction network, we collected genetic data on martens from the archipelago and from all regional reintroduction sites. In total, we genotyped 483 individual martens, 43 of which inhabited the Apostle Islands (densities 0.42-1.46 km-2 ). Coalescent analyses supported the contemporary recolonization of the Apostle Islands with progenitors likely originating from Michigan, which were sourced from Ontario. We also identified movements by a first-order relative between the Apostle Islands and the recovery network. We detected some regional gene flow, but in an unexpected direction: individuals moving from the islands to the mainland. Our findings suggest that the Apostle Islands were naturally recolonized by progeny of translocated individuals and now act as a source back to the reintroduction sites on the mainland. We suggest that the Apostle Islands, given its protection from disturbance, complex forest structure, and reduced carnivore competition, will act as a potential refuge for marten along their trailing range boundary and a central node for regional recovery. Our work reveals that translocations, even those occurring along southern range boundaries, can create recovery networks that function like natural metapopulations. Identifying refuges, locations that are resistant to environmental change, within these recovery networks can further improve species recovery, even within novel environments. Future translocation planning should a priori identify potential refuges and sources to improve short-term recovery and long-term persistence.