Quantifying the Resistive Losses of the Catalytic Layers in Anion-Exchange Membrane Fuel Cells

The existing gap in the ability to quantify the impacts of resistive losses on the performance of anion-exchange membrane fuel cells (AEMFCs) during the lifetime of their operation is a serious concern for the technology. In this paper, we analyzed the ohmic region of an operating AEMFC fed with pure oxygen followed by CO2 -free air at various operating currents, using a combination of electrochemical impedance spectroscopy (EIS) and a novel technique called impedance spectroscopy genetic programming (ISGP). Presented here for the first time in this work, we isolated and quantified the individual effective resistance (Reff ) values occurring in the AEMFC and their influence on performance as operating conditions change. We believe that this first work is vital to help distinguish the influence of the individual catalytic and mass-transfer processes in this technology thereby providing valuable data to the AEMFC community, with potentially wider applicability to other electrochemical devices where individual physical processes occur simultaneously and need to be sequestered for deeper understanding.

Impact of COVID-19 policies on pedestrian traffic and walking patterns

The spread of COVID-19 pandemic provoked new policies and restrictions, which had an unprecedented impact on urban mobility and traffic on local and global scales. While changes in motorized traffic were investigated and monitored throughout the recent pandemic crisis in many cities around the world, not much was done on the changes in pedestrian street-traffic and walking patterns during this time. This study aims to identify, quantify, and analyze the changes in pedestrian traffic and walking patterns induced by COVID-19 policies. The "first wave" period of COVID-19 policies in Tel-Aviv, Israel, is used as a case study in this work. The analysis includes over 116 million pedestrian movement records documented by a network of 65 Bluetooth sensors, between 1.2.2020 and 26.7.2020, with a comparison to the equivalent time in 2019 that signifies "normal" pre-COVID-19 conditions. The results show clear correlation between the various COVID-19 policy restrictions and pedestrian count. The shifts to work-from-home and closure of businesses were highly correlated with changes in walking patterns during weekdays, while distinguishing changes in commercial and residential street segments. Nevertheless, while the restrictions dramatically influenced pedestrian movement volume and time of walking, it did not significantly change where people chose to walk, signifying the essentialness of attractive streets, parks and squares for citizens living in urban areas. This study shows how policy affects walking behavior in cities, demonstrating the potential of passive crowdsourced sensing technologies to provide urban planners and decision makers an efficient tool for monitoring and evaluating pedestrian infrastructure implementation in cities.