A hyperspectral Raman imaging systems for process analytical technology developments

用于过程分析技术开发的高光谱拉曼成像系统

• 批准号: RTI-2020-00218
• 负责人: Duchesne, Carl
• 金额: $ 8.4万
• 依托单位: Université Laval
• 依托单位国家: 加拿大
• 项目类别: Research Tools and Instruments
• 财政年份: 2019
• 资助国家: 加拿大
• 起止时间: 2019-01-01 至 2020-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=693009
• 关键词: hyperspectral; Raman; imaging; systems; process

A hyperspectral Raman imaging system is requested in this RTI proposal. It will support the research programs of 5 co-applicants located in 2 Canadian universities. The co-applicants need hyperspectral imaging equipment to develop innovative process analytical technologies (PAT) for real-time process monitoring and product quality control in important fields for the Canadian economy: advanced materials, energy and oil sands, CO2 capture technology, bio-energy and bio-based products, and pharmaceutical production. The applicants have reached the limit of the Near Infrared Chemical Imaging (NIR-CI) equipment they have been using in most of their collaborative research projects. There are three main issues with the current NIR-CI system: 1) it is highly sensitive to moisture adsorbed on surfaces, which interferes with the quantification of compounds of interest, 2) it is insensitive to inorganic compounds, 3) the spatial resolution of the chemical images is too low to achieve the desired limit of detection. NIR spectroscopy is based on photon absorption by polar molecular groups whereas Raman is based on inelastic scattering of radiations by symmetrical (non-polar) functional groups. This makes both methods complementary; molecules that cannot be detected with one method can be easily detected with the other. The Raman system will provide a more specific fingerprint of the materials allowing to discriminate classes of molecules and inorganic compounds, in particular. It will allow increasing the spatial resolution of the chemical images with respect to NIR (i.e. lower detection limit) which is required in most of the projects. Raman is also insensitive to water, which is a common interferent (moisture adsorbed on material surfaces) strongly affecting the NIR spectrum. The Raman equipment will provide further development and foster innovation in the collaborative research programs led by the co-applicants. It will also be used for training a significant number highly qualified personnel in these fields.

该 RTI 提案要求采用高光谱拉曼成像系统。它将支持位于加拿大两所大学的 5 名共同申请人的研究项目。共同申请人需要高光谱成像设备来开发创新的过程分析技术（PAT），用于加拿大经济重要领域的实时过程监控和产品质量控制：先进材料、能源和油砂、二氧化碳捕获技术、生物能源和生物基产品以及药品生产。申请人在大多数合作研究项目中使用的近红外化学成像（NIR-CI）设备已经达到了极限。当前的 NIR-CI 系统存在三个主要问题：1）它对表面吸附的水分高度敏感，这会干扰目标化合物的定量；2）它对无机化合物不敏感；3）化学图像的空间分辨率太低，无法达到所需的检测限。近红外光谱基于极性分子基团的光子吸收，而拉曼光谱基于对称（非极性）官能团对辐射的非弹性散射。这使得两种方法互补；用一种方法无法检测到的分子可以用另一种方法轻松检测到。拉曼系统将提供更具体的材料指纹，特别是能够区分分子和无机化合物的类别。它将允许提高大多数项目所需的化学图像相对于 NIR 的空间分辨率（即较低的检测限）。拉曼对水也不敏感，水是一种常见的干扰物（材料表面吸附的水分），会强烈影响近红外光谱。拉曼设备将在共同申请人领导的合作研究项目中提供进一步的发展并促进创新。它还将用于培训这些领域的大量高素质人才。