Discrete-Particle Model to Optimize Operational Conditions of Proton-Exchange Membrane Fuel-Cell Gas Channels.

Operation of proton-exchange membrane fuel cells is highly deteriorated by mass transfer loss, which is a result of spatial and temporal interaction between airflow, water flow, channel geometry, and its wettability. Prediction of two-phase flow dynamics in gas channels is essential for the optimization of the design and operating of fuel cells. We propose a mechanistic discrete particle model (DPM) to delineate dynamic water distribution in fuel cell gas channels and optimize the operating conditions. Similar to the experimental observations, the model predicts seven types of flow regimes from isolated, side wall, corner, slug, film, and plug flow droplets for industrial temporal and spatial scales. Consequently, two-phase flow regime maps are proposed. The results suggest that an increase in water accumulation in the channel is related to the increase in the water cluster density emerging from the gas diffusion layer rather than the increased water flow rate through constant water pathways. From a modeling perspective, the DPM replicated well volume-of-fluid channel simulation results in terms of saturation, water coverage ratio, and interface locations with an estimated 5 orders of magnitude increase in calculation speed.

Operando Liquid Pressure Determination in Polymer Electrolyte Fuel Cells.

Extending the operating range of fuel cells to higher current densities is limited by the ability of the cell to remove the water produced by the electrochemical reaction, avoiding flooding of the gas diffusion layers. It is therefore of great interest to understand the complex and dynamic mechanisms of water cluster formation in an operando fuel cell setting as this can elucidate necessary changes to the gas diffusion layer properties with the goal of minimizing the number, size, and instability of the water clusters formed. In this study, we investigate the cluster formation process using X-ray tomographic microscopy at 1 Hz frequency combined with interfacial curvature analysis and volume-of-fluid simulations to assess the pressure evolution in the water phase. This made it possible to observe the increase in capillary pressure when the advancing water front had to overcome a throat between two neighboring pores and the nuanced interactions of volume and pressure evolution during the droplet formation and its feeding path instability. A 2 kPa higher breakthrough pressure compared to static ex situ capillary pressure versus saturation evaluations was observed, which suggests a rethinking of the dynamic liquid water invasion process in polymer electrolyte fuel cell gas diffusion layers.

Development and evaluation of a dimensionless mechanistic pan coating model for the prediction of coated tablet appearance.

A mathematical, mechanistic tablet film-coating model has been developed for pharmaceutical pan coating systems based on the mechanisms of atomisation, tablet bed movement and droplet drying with the main purpose of predicting tablet appearance quality. Two dimensionless quantities were used to characterise the product properties and operating parameters: the dimensionless Spray Flux (relating to area coverage of the spray droplets) and the Niblett Number (relating to the time available for drying of coating droplets). The Niblett Number is the ratio between the time a droplet needs to dry under given thermodynamic conditions and the time available for the droplet while on the surface of the tablet bed. The time available for drying on the tablet bed surface is critical for appearance quality. These two dimensionless quantities were used to select process parameters for a set of 22 coating experiments, performed over a wide range of multivariate process parameters. The dimensionless Regime Map created can be used to visualise the effect of interacting process parameters on overall tablet appearance quality and defects such as picking and logo bridging.