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，用于各种工业应用，包括航空航天，生物医学和聚变。激光粉末床熔融（LPBF）是AM的一种形式，其使用激光束将薄粉末及其支撑基底熔融，形成连续的熔池，然后将其固化成所需的形状。为形成熔池而输送的强激光能量可在相互作用区处诱发羽流，从而在部件中形成不期望的特征（例如孔隙和裂纹）和成分变化，这两者都可能对产品质量和性能有害。传统的原位监测捕捉的过程动力学的方面，但没有提供足够的信息来解释激光羽流的相互作用及其在LPBF的影响。因此，激光羽流动力学背后的基本物理理解仍然不清楚。在这个项目中，我们将设计，建造，并采用一个化学传感仪器AM，使LPBF期间的羽流化学检测和分析。开发这种用于AM的化学传感仪器（包括软件和硬件）将需要高信噪比、时间分辨率和长期操作稳定性。该仪器将能够在打印过程中监测羽流动态，旨在最大限度地减少AM部件中的成分变化，并推导出最佳参数，以在不产生羽流的情况下形成熔池，最终提高AM工艺的生产率。这个多学科的研究项目将联合收割机在仪器设计，增材制造，机器学习，光谱学，信号和图像处理的主管组的能力。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.