X-ray Microscopy of Particulate Matter in Automotive Filters

空气中的颗粒物（PM）对人类健康和环境构成危害，在日益严格的监管以及燃油效率和催化剂金属成本等经济驱动因素的推动下，已经开发出先进的过滤技术来减少PM的危害。该项目使用x射线断层扫描和电子显微镜对颗粒物进行成像，并观察颗粒物过滤器中雾化PM的捕获情况。该项目解释了为什么排气过滤器会根据PM的大小和成分而产生不同的效果，为什么颗粒过滤器会随着时间的推移而老化，以及未来如何更好地设计和制造过滤器。此外，它开发了一种独特的流动系统，能够观察各种过滤器的原位过滤，包括HEPA和呼吸防护设备（“口罩”）。该方法是将同步加速器x射线辐射（钻石光源）与该学生开发的新型专用原位气溶胶流动系统相结合。然后在层析数据集上使用复杂的3D图像分析，应用高性能计算进行图像处理和机器学习算法进行图像分割和测量。过滤器的几何形状和结构的特点是评估在运行期间观察到的颗粒物质在过滤器内的积累。这涉及EPSRC在催化、燃烧工程、制造技术、颗粒技术以及图像和视觉计算方面的研究领域。

Airborne particulate matter (PM) presents a hazard to human health and the environment and advanced filtration technologies have been developed to reduce the harm of PM, driven by tightening regulation and economic drivers such as fuel efficiency and the cost of catalyst metals. This project uses x-ray tomography and electron microscopy to image particulate matter and to observe the capture of aerosolized PM within particulate filters. The project addresses why exhaust filters can have variable effectiveness according to sizes and composition of PM, why particulate filters age over time, and how filters may be better designed and manufactured in the future. Furthermore, it develops a unique flow system able to observe In situ filtration in a variety of filters including HEPA and respiratory protective equipment ('face masks').The approach is to combine synchrotron x-ray radiation (Diamond Light Source) with an new purpose built in situ aerosol flow system developed by the student. Sophisticated 3D image analysis is then used on the tomographic datasets applying high performance computation for image processing and machine learning algorithms for image segmentation and measurement. The characteristics of the filter geometry and construction are assessed in relation to the observed build up of particulate matter in the filter during operation.This addresses EPSRC research areas in Catalysis, Combustion engineering, Manufacturing technologies, Particulate technology and Image and vision computing.