The role of tortuosity in filtration efficiency: a general network model for filtration

Filters are composed of a complex network of interconnected pores each with tortuous paths. We present a general network model to describe a filter structure comprising a random network of interconnected pores, relaxing traditional assumptions made with simplified theoretical models. We use the model to examine the dependence of the filter performance on both its underlying pore structure (expressed through the pore interconnectivity and porosity gradient) and the feed composition (expressed through the size of the contaminants). We find that a simple scaling allows the performance curves over a wide range of the filter material properties to be mapped onto a single master curve. We also study the link between the tortuosity of a filter and its resulting performance, leading to further self-similarity observations. When we vary the properties of the feed, however, the performance curves are distinct from one another and do not collapse onto a single master curve. Our network model allows us to probe the behaviour of a complex and realistic filter configuration within a framework that is easy to implement and study, enabling accelerated testing and reducing experimental costs in filtration challenges

The role of tortuosity in filtration efficiency: a general network model for filtration

Filters are composed of a complex network of interconnected pores each with tortuous paths. We present a general network model to describe a filter structure comprising a random network of interconnected pores, relaxing traditional assumptions made with simplified theoretical models. We use the model to examine the dependence of the filter performance on both its underlying pore structure (expressed through the pore interconnectivity and porosity gradient) and the feed composition (expressed through the size of the contaminants). We find that a simple scaling allows the performance curves over a wide range of the filter material properties to be mapped onto a single master curve. We also study the link between the tortuosity of a filter and its resulting performance, leading to further self-similarity observations. When we vary the properties of the feed, however, the performance curves are distinct from one another and do not collapse onto a single master curve. Our network model allows us to probe the behaviour of a complex and realistic filter configuration within a framework that is easy to implement and study, enabling accelerated testing and reducing experimental costs in filtration challenges.</br