Multi-Spectral Digital Holography for Aerosol Material Characterization

用于气溶胶材料表征的多光谱数字全息术

• 批准号: 2107715
• 负责人: Matthew Berg
• 金额: $ 39.92万
• 依托单位: Kansas State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-06-01 至 2025-05-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2107715&HistoricalAwards=false
• 关键词: Multi; Spectral; Digital; Holography; Aerosol

Aerosols are small particles of solid or liquid material dispersed in a gas and they are common in everyday life. Familiar examples include the water-droplets forming clouds, the dust and combustion particles forming haze, and pollen particles emitted by plants. When in the atmosphere, aerosols affect the Earth’s energy budget by absorbing and scattering sunlight, which can lead to cooling or heating effects on the climate. The amount of light absorbed or scattered is determined by the shape, size, and composition of a particle. Consequently, it is of interest to develop methods to determine these properties of aerosol particles, whether that be to better understand their impact on the climate or as a way to study what types of particles are present in a given environment. This project develops a new way to characterize aerosols where images of free-flowing particles are obtained without the need to collect or immobilize the particles. The core of the approach involves digital holography (DH), which is functionally analogous to microscopy, except no lenses are needed and particle images are focused post-measurement in computational manner. The images obtained thus reveal the shape and size of the particles under investigation. In the conventional approach, however, the images are gray-scale in nature, and so, there is little sensitivity to the particle’s material. By extending DH to operate at three wavelengths (colors) simultaneously, this project brings color to the particle images. This presents the possibility of gaining particle-material information in a non-contact manner. Systematic studies of particles of different shapes and materials will be conducted to determine the quality of the color images. By applying a color analysis to such images, the project will test the ability to merge shape, size, and color information to differentiate between particle types. The outcome of this work could significantly advance the ability to characterize aerosols across multiple domains of scientific and applied interests.With conventional DH, gray-scale images of individual aerosol particles can be obtained in a contact-free manner. This capability has been adopted by numerous scientists and has advanced our understanding for the size and shape of particles in the atmosphere. What is missing in DH, however, is information about the particle material. By extending the principles of DH across the spectral domain, this project will bring color to images of free-flowing aerosol particles. The project applies chromaticity analysis to the images as a quantitative way to describe the colors exhibited. Because particles of different material absorb and reflect colors differently, this analysis has the potential to distinguish between categories of material. For example, mineral dust (MD) particles with radiatively absorbing components like iron oxides could be distinguished from particles with strongly scattering components like silicates. Biological particles could be distinguished from MD. The work will focus on the coarse mode aerosol (CMA), i.e., particles larger than one micrometer. Such particles are ubiquitous and include, e.g., wind-blown MD and biological particles. Not only is a particle’s size and shape revealed with DH, but the interference nature of the method allows the particle’s extinction cross section to be measured as well. The project will assemble a collection of CMA particles, characterize their material composition with X-ray diffraction and other analytical techniques, and perform chromaticity analysis on stationary particles from the collection. By aerosolizing these samples and capturing color DH images of the free-flowing particles, the study can test the ability of the analysis to associate observed particles with categories of known materials. The outcomes of the work will establish the feasibility and utility of color DH for aerosol characterization, from which future efforts could develop instruments for field studies of the atmospheric CMA at an unprecedented level of detail.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

气溶胶是分散在气体中的固体或液体物质的小颗粒，它们在日常生活中很常见。常见的例子包括形成云的水滴，形成霾的灰尘和燃烧颗粒，以及植物散发的花粉颗粒。在大气中，气溶胶通过吸收和散射阳光影响地球的能量收支，这可能导致对气候的冷却或加热效应。吸收或散射的光的量由颗粒的形状、大小和组成决定。因此，开发确定气溶胶颗粒的这些特性的方法是有意义的，无论是为了更好地了解它们对气候的影响，还是作为一种研究特定环境中存在何种颗粒的方法。该项目开发了一种新的方法来表征气溶胶，其中获得自由流动颗粒的图像，而无需收集或收集颗粒。该方法的核心涉及数字全息术（DH），其功能类似于显微镜，除了不需要透镜并且粒子图像以计算方式在测量后聚焦。由此获得的图像揭示了所研究颗粒的形状和大小。然而，在传统方法中，图像本质上是灰度的，因此对颗粒的材料几乎不敏感。通过将DH扩展到同时在三个波长（颜色）下工作，该项目为粒子图像带来了颜色。这提供了以非接触方式获得颗粒材料信息的可能性。将对不同形状和材料的颗粒进行系统研究，以确定彩色图像的质量。通过对这些图像进行颜色分析，该项目将测试合并形状，大小和颜色信息以区分颗粒类型的能力。这项工作的成果可以显着提高跨多个领域的科学和应用interests.With传统的DH，单个气溶胶颗粒的灰度图像，可以在一个非接触的方式获得气溶胶特征的能力。这种能力已被许多科学家采用，并提高了我们对大气中颗粒物大小和形状的认识。然而，DH中缺少的是关于颗粒材料的信息。通过将DH的原理扩展到光谱域，该项目将为自由流动的气溶胶颗粒的图像带来色彩。该项目将色度分析应用于图像，作为描述所展示颜色的定量方法。由于不同材料的颗粒吸收和反射颜色的方式不同，因此这种分析有可能区分材料类别。例如，具有辐射吸收成分（如氧化铁）的矿物粉尘（MD）颗粒可以与具有强散射成分（如硅酸盐）的颗粒区分开。生物颗粒可与MD相区分。这项工作将集中在粗模式气溶胶（CMA），即，大于1微米的颗粒。这样的颗粒是普遍存在的并且包括，例如，风吹MD和生物颗粒。不仅是一个粒子的大小和形状显示与DH，但该方法的干涉性质允许粒子的消光截面进行测量。该项目将收集CMA颗粒，用X射线衍射和其他分析技术表征其材料成分，并对收集的静止颗粒进行色度分析。通过雾化这些样品并捕获自由流动颗粒的彩色DH图像，该研究可以测试分析将观察到的颗粒与已知材料类别相关联的能力。这项工作的成果将建立气溶胶特性的可行性和实用性的颜色DH，从未来的努力可以开发仪器的大气CMA的现场研究在一个前所未有的详细程度。这个奖项反映了NSF的法定使命，并已被认为是值得通过使用基金会的智力价值和更广泛的影响审查标准进行评估的支持。

项目成果

Tutorial: Aerosol characterization with digital in-line holography

• DOI: 10.1016/j.jaerosci.2022.106023
• 发表时间: 2022-05-31
• 期刊: JOURNAL OF AEROSOL SCIENCE
• 影响因子: 4.5
• 作者: Berg，Matthew J.

Backscatter multiple wavelength digital holography for color micro-particle imaging

• DOI: 10.1364/ao.441509
• 发表时间: 2022-02-10
• 期刊: APPLIED OPTICS
• 影响因子: 1.9
• 作者: Giri, Ramesh;Berg, Matthew J.
• 通讯作者: Berg, Matthew J.

Electromagnetic coupling and determination of the structure factor of fractal aggregates

• DOI: 10.1016/j.jqsrt.2022.108451
• 发表时间: 2022-11
• 期刊: Journal of Quantitative Spectroscopy and Radiative Transfer
• 影响因子: 2.3
• 作者: C. Argentin;M. Berg;M. Mazur;R. Ceolato;J. Yon