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Phase-specific optical in situ detection of iron-based nanoparticle aerosols

Phase-specific optical in situ detection of iron-based nanoparticle aerosols
铁基纳米颗粒气溶胶的相特异性光学原位检测
批准号:
524965916
负责人:
Professor Dr. Christof Schulz
金额:
$0.0万
依托单位国家:
德国
项目类别:
Research Grants
财政年份:
--
资助国家:
德国
项目状态:
未结题
起止时间:

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英文摘要
Iron oxide exists in different crystal phases with distinctly different physical properties. Gas-phase nanoparticle synthesis is a promising method promising for producing specific material phases with useful catalytic or magnetic properties by varying the temperature profile and concentration of the oxidizing species. To date, however, there is no way to determine the phase (and thus the composition of FexOy) in situ during their formation in the reactor, and analysis of the product alone is not sufficient because the pathways to the final product remain unclear. In this project, we will develop an approach that takes advantage of the distinct optical properties of different iron oxide phases (magnetite (Fe3O4): dark brown, hematite (alpha-Fe2O3): red, maghemite (gamma-Fe2O3): reddish brown) and metallic iron nanoparticles (gray) to enable quantitative in situ measurements of the respective phases during their formation. The phase-dependent optical properties result in specific spectral absorption and thermal light emission in nanoparticle aerosols. The spectral properties will be analyzed using aerosolized model materials characterized ex situ. The new method is then applied to nanoparticle aerosols that are produced in a microwave plasma reactor using iron pentacarbonyl as precursor, ranging from metallic to fully oxidized depending on the oxygen added. Data analysis of absorption and emission measurements in axially symmetric flows is supported by tomographic reconstruction from spatially 1-dimensional resolved absorption and emission measurements. The in situ measurements are supported by laser-based methods (LIBS and Raman). The resulting method for in situ detection of nanoparticle phases will support process understanding and design and enable the step from empirical trial-and-error approaches to targeted synthesis.
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