Integration of a pore-network modeling framework in tomographic visualization workflow

多孔材料在许多先进技术中发挥着关键作用，从用于储能的电池到用于净水的过滤**膜。基于这些多孔材料的设备的性能在很大程度上取决于孔隙空间的实际内部结构。气孔(和固体)相的性质(即**大小、形状、取向和连通性)都会对性能产生至关重要的影响。现在，使用先进的X射线断层扫描设备，也称为CAT扫描，可以以微米级的分辨率直接**可视化内部结构。分析结构并以高效和准确的方式提取所需的**信息仍然是一个持续的挑战。总部位于蒙特利尔的**对象研究系统公司(ORS)为这些应用开发尖端软件。拟议的项目**旨在通过整合申请者研究实验室开发的软件**OpenPNM来增强他们的产品，该软件能够将孔隙空间抽象为网络表示。这一功能是ORS用户**高度要求的功能，它将允许通过基于图像的模拟非常有效地估计材料的运输特性**。这将使更高的吞吐量筛选潜在**材料，因为模拟比实验室测试更快，并将有助于诊断性能差，从而指出**方法优化材料，更好的电池和更清洁的水。

Porous materials play a key role in many advanced technologies, from batteries for energy storage to filtration**membranes for water purification. The performance of devices based on these porous materials depends**greatly on the actual internal structure of the pore space. Properties of the pore (and solid) phases (i.e. the**sizes, shapes, orientations and connectivity), can all have an overriding impact on the performance. Direct**visualization of the internal structures with micron-scale resolution is now possible using advanced x-ray**tomography equipment, also known as cat-scans. Analyzing the structures and extracting the desired**information in an efficient and accurate way remains an ongoing challenge. The Montreal-based company,**Object Research Systems (ORS), develops leading edge software for these applications. The proposed project**aims to enhance their product by incorporating the software developed in the applicant's research lab,**OpenPNM, which enables the abstraction of the pore space to a network representation. This functionality, a**highly requested feature among ORS's users, will allow extremely efficient estimations of transport properties**of the materials via image-based simulations. This will enable higher through-put screening of potential**materials since simulations are faster than lab tests, and will help diagnose poor performance thus point the**way to optimized materials, better batteries, and cleaner water.