Multimodal Correlative Tomography for Advanced Materials Development

用于先进材料开发的多模态相关断层扫描

• 批准号: RGPIN-2022-04996
• 负责人: Phillion, Andre
• 金额: $ 4.66万
• 依托单位: McMaster University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=758265
• 关键词: Multimodal; Correlative; Tomography; Advanced; Materials

The structure of materials is inherently 3D in nature with many important events occurring well beneath the surface. Emerging 3D multi-scale, multi-faceted, and time-lapsed imaging techniques are now beginning to be brought together as "multimodal correlative tomography" to acquire unique 3D knowledge of microstructure and the way it evolves when mechanically deformed or heated to high temperatures. This approach provides significantly deeper insight to structure-property-processing relationships than what is gained when imaging uncorrelated regions of a sample or when imaging using 2D methods. The long-term goal of this NSERC Discovery Grant is to develop multimodal correlative tomography as a key method for revealing novel insight into the performance and failure mechanisms of advanced engineering materials. In the short-term the objective is to improve multimodal correlative tomography workflows i.e. to address technical challenges relating to imaging-workflows, materials testing stages, and alignment of images between scans that limit this technique's widespread use in materials R&D. The short-term objective will be realized through four sub-objectives that apply this approach to advanced material systems. Specifically we will investigate how the structure of Li-ion battery and hydrogen fuel cell materials change during operation, how new additively manufactured beta-Ti alloys deform, and how ternary analogues to AA 7XXX alloys solidify. These material systems were selected due to their great potential to help reduce in-transportation greenhouse gas emissions and thus to support action on Climate Change. The multi-scale nature of the research will be realized by combining X-ray Computed Tomography with Focused Ion Beam electron Tomography. The use of both X-ray and electron imaging modalities provide us with access to unique 3D multi-faceted materials data from different probes: structure, chemical composition, and grain crystallography. By developing bespoke test stages, we will conduct time-lapsed 3D imaging experiments that follow microstructure evolution under controlled environmental conditions. We will develop new analysis methods to correlate the multiple data sets together, and concisely interpret the 3D images. The proposed research will have significant benefits on Canadian society and industry as well as greatly advance 3D imaging as a key materials engineering characterization method. The high quality 3D multi-scale, multi-faceted, and time-lapsed materials-data that we acquire will create new fundamental materials knowledge of battery, fuel cell, and metallic alloys that is critical for rapidly bringing new material designs to the market. The developed multimodal correlative tomography workflows will help position Canada as a world leader in this field, supporting advanced materials development with applications ranging from additive manufacturing to biomaterials to renewable resources.

材料的结构本质上是三维的，许多重要的事件都发生在地表之下。新兴的3D多尺度，多方面和时间推移成像技术现在开始被汇集在一起，作为“多模态相关断层扫描”，以获得独特的微观结构的3D知识，以及当机械变形或加热到高温时的演变方式。这种方法提供了显着更深入的洞察结构-性能-处理的关系时，获得的成像不相关的区域的样品或使用2D方法成像时。该NSERC发现资助的长期目标是开发多模态相关断层扫描，作为揭示先进工程材料性能和失效机制的新见解的关键方法。在短期内，目标是改善多模态相关断层扫描工作流程，即解决与成像工作流程，材料测试阶段和扫描之间的图像对齐相关的技术挑战，这些挑战限制了该技术在材料研发中的广泛应用。短期目标将通过将这种方法应用于先进材料系统的四个子目标来实现。具体来说，我们将研究锂离子电池和氢燃料电池材料的结构在运行过程中如何变化，新型增材制造的β-Ti合金如何变形，以及AA 7 XXX合金的三元类似物如何固化。之所以选择这些材料系统，是因为它们在帮助减少运输中温室气体排放方面具有巨大潜力，从而支持应对气候变化的行动。 将X射线计算机断层扫描与聚焦离子束电子断层扫描相结合，实现研究的多尺度性。X射线和电子成像模式的使用为我们提供了从不同探头获得独特的3D多方面材料数据的机会：结构，化学成分和晶粒晶体学。通过开发定制的测试平台，我们将在受控的环境条件下进行随时间推移的3D成像实验，以跟踪微观结构的演变。我们将开发新的分析方法，将多个数据集关联在一起，并简洁地解释3D图像。拟议的研究将对加拿大社会和工业产生重大利益，并大大推进3D成像作为一种关键的材料工程表征方法。我们获得的高质量3D多尺度，多方面和时间推移的材料数据将创建电池，燃料电池和金属合金的新基础材料知识，这对于快速将新材料设计推向市场至关重要。开发的多模态相关断层扫描工作流程将有助于将加拿大定位为该领域的世界领导者，支持先进材料开发，应用范围从增材制造到生物材料再到可再生资源。