Development and Application of Chemical Sensing Technology for Additive Manufacturing

增材制造（AM）是一种先进的制造技术，可将数字设计转换为具有功能特性的复杂结构，适用于各种工业应用，包括航空航天，生物医学和融合。激光粉末床熔融（LPBF）是增材制造的一种形式，它使用激光束熔化薄粉末及其支撑基板，形成连续的熔池，然后固化成所需的形状。用于形成熔池的强激光能量会在相互作用区诱发羽流，形成不希望的特征（例如孔隙和裂纹）以及组件的成分变化，这两者都可能对产品质量和性能有害。传统的现场监测捕获了过程动力学的各个方面，但不能提供足够的信息来解释激光-羽流相互作用及其在LPBF期间的影响。因此，激光羽流动力学背后的潜在物理理解仍然不清楚。在这个项目中，我们将设计、建造和使用一种用于AM的化学传感仪器，该仪器可以在LPBF期间检测和分析羽流化学。开发这种用于AM的化学传感仪器（包括软件和硬件）需要高信噪比、时间分辨率和长期运行稳定性。该仪器将能够在打印过程中监测羽流动力学，旨在最大限度地减少增材制造部件的成分变化，并推断出最佳参数，以形成不产生羽流的熔池，最终提高增材制造过程的生产率。这个多学科研究项目将结合主管小组在仪器设计、增材制造、机器学习、光谱学、信号和图像处理方面的能力。该项目还将提供一个扩展到博士学位的机会，最终目标是将化学传感系统集成到商业AM系统中，展示其在工业环境中的影响。

Additive manufacturing (AM) is an advanced manufacturing technology that converts digital designs into complex structures with functional properties for a variety of industrial applications, including aerospace, biomedical, and fusion. Laser powder bed fusion (LPBF) is a form of AM that uses a laser beam to fuse a thin powder and its supporting substrate, forming sequential melt pools which are then solidified into desired shapes. The intense laser energy delivered to form the melt pool can induce a plume at the interaction zone, forming undesirable features (e.g. porosity and cracks) and compositional variations in the component, both of which can be detrimental to the product quality and performance. Traditional in situ monitoring captures aspects of the process dynamics but does not provide sufficient information to explain the laser-plume interaction and its impact during LPBF. Therefore, the underlying physical understanding behind the laser-plume dynamics remains unclear. In this project, we will design, build, and employ a chemical sensing instrument for AM that enables the detection and analysis of the plume chemistry during LPBF. The development of such a chemical sensing instrument (including software and hardware) for AM would require a high signal-to-noise ratio, temporal resolution, and long-term operational stability. This instrument will enable monitoring of the plume dynamics during printing, aim to minimise the compositional variations in the AM parts, and deduce optimum parameters to form melt pools without plume generation, ultimately improving the productivity of the AM process. This multidisciplinary research project will combine the capabilities in the supervisors' groups in instrument design, additive manufacturing, machine-learning, spectroscopy, signal, and image processing. The project will also offer an opportunity to extend to a PhD with the ultimate goal to integrate the chemical sensing system to a commercial AM system, demonstrating its impact in an industrial context.