Carbon Nanoparticles in Combustion: A Multiscale Perspective

燃烧中碳纳米颗粒奖摘要：多尺度视角提案编号：cts-0553764；首席研究员：洛杉矶维奥利研究所：密歇根大学安娜堡分校纳米颗粒排放与两个紧迫的环境问题有关--细颗粒对健康的影响和全球变暖。流行病学研究表明，发病率增加与测量到的环境颗粒物浓度增加之间存在相关性。高数量浓度和小尺寸的纳米颗粒导致在肺深处的高沉降率。已发现超细颗粒(0.1微米)可促进急性肺反应，并削弱巨噬细胞(肺部的清道夫细胞)吞噬和清除细胞外环境中颗粒的能力。因此，燃烧源排放的纳米颗粒是一个非常严重的健康问题，因为它们的大小和与它们相关的致癌物质。因此，重要的是要确定大气颗粒物的化学和物理性质。燃烧是人类不断向大气中注入颗粒物的主要过程。更重要的是，这些颗粒以具有纳米尺寸的团簇的形式以物理上可能的最小尺寸产生。这一提议的主要特点是通过在不同的(空间/时间)区域使用新的模拟方法，对燃烧环境中纳米颗粒的形成进行了创新的多尺度表征。使用原子模型，如分子动力学，可以让我们以一种特定的化学方式跟踪纳米颗粒形成过程中发生的变化，提供关于纳米颗粒的化学结构和构型及其团聚的信息。碳纳米颗粒的团聚受到延伸到介观尺度的大长度和时间尺度的运动的影响，即长度为一微米或更长，时间为一微秒或更长。为了增加模拟中可获得的时间和长度尺度，并能够模拟纳米颗粒的组装，有必要在更粗粒度(CG)的水平上描述颗粒。该提案的主要研究目标是使用独特的多尺度粗粒化方法来研究纳米颗粒的凝聚和组装。使用这种方法，分子系统中整个原子组之间的有效力被映射为分子(或纳米颗粒)上粗粒位置的简单得多的有效力。这些所产生的力实际上是粗粒化位置(即原子组)之间的平均力的势。结果，系统的有效相空间的大小显著减小，以及昂贵的力计算的数量也大大减少。CG模型将允许本项目中纳米粒子系统的模拟在长度和时间尺度上向上过渡，以便更好地获取受这些尺度影响的性质。这种方法提供了纳米颗粒自组装问题中各种时间和长度尺度之间的联系，以及理解碳纳米颗粒结构和生长背后的原子相互作用的前所未有的机会。集成的多尺度模拟方法提供了对碳氢化合物燃烧过程中产生的细颗粒结构的详细、分子水平的描述。利用这种新方法获得的结果，将有可能将这项研究显著扩大到重要方向，如这些颗粒物对人类健康和全球变暖的影响。将实验研究和理论模拟相结合，在多层次的时间和粒度尺度上，将增加对纳米颗粒形成和转化的整体理解。这是智力贡献的一个重要方面，超越了在任何一个尺度上增加的科学理解。拟议的研究活动将通过开发计算模型来推动发现，该模型将首次阐明纳米颗粒形成的化学具体方式的机制。拟议项目的更广泛的教育影响也将是重大的，通过研究生直接参与研究项目，以及在科学教育和代表性不足的群体中开展外联活动。研究和教育活动的结合将通过计算化学和分子建模的教学来增进理解，这将使学生有机会更深入地了解使用这些基于多媒体的方法进行有效教学所涉及的物理和化学过程。

Award Abstract for Carbon Nanoparticles in Combustion: A Multiscale PerspectiveProposal Number: CTS-0553764; Principal Investigator: Violi, AngelaInstitution: University of Michigan Ann ArborParticulate emissions in the nanoparticle size range are related to two pressing environmental problems - the health impacts of fine particles and global warming. Epidemiological studies have shown a correlation between increased morbidity and increases in measured ambient particulate concentrations. The high number concentration and small size of nanoparticles lead to high rates of deposition deep in the lung. The ultrafine particles ( 0.1 micron) have been found to promote acute pulmonary response, and they impair the ability of the macrophages (the scavenger cells in lungs) to engulf and remove particles from the extracellular milieu. Therefore, nanoparticles emitted by combustion sources are a very serious health concern because of both their size and the carcinogens with which they are associated. It is therefore important to characterize the chemical and physical properties of atmospheric particles. Combustion is the main process through which man continuously injects particles into the atmosphere. More importantly, these particles are produced at the smallest sizes physically possible in the form of clusters with nanometric dimensions The key feature of this proposal is its innovative multiscale characterization of nano-particle formation in combustion environments, through the use of novel simulation methodologies at disparate (spatial/temporal) regimes. The use of atomistic models, such as Molecular Dynamics, can allow us to follow the transformations that occur during nanoparticle formation in a chemically specific way, providing information on both the chemical structure and the configuration of the nanoparticles and their agglomeration. Carbonaceous nanoparticle agglomeration is influenced by large length and time scale motions that extend to mesoscopic scales, i.e., one micrometer or more in length and one microsecond or more in time. In order to increase the time and length scales accessible in simulations and be able to simulate nanoparticle assembly, it is necessary to describe the particles on a more coarse-grained (CG) level. The primary research objective of this proposal is to study nanoparticle coagulation and assembly using an unique multi-scale coarse-graining approach. With this methodology the effective forces between whole groups of atoms in the molecular system are mapped into much simpler effective forces for coarse-grained sites on the molecules (or nanoparticles). These resulting forces are, in effect, the potential of mean forces between the coarse-grained sites (i.e., groupings of atoms). As a result, the effective phase space of the system is significantly reduced in size, as are the number of costly force calculations. The CG model will allow the simulations of the nanoparticle systems in this project to bridge upward in both length and time scale, so as to better access the properties influenced by those scales. This approach provides a connection between the various time and length scales in the nanoparticle self-assembly problem, together with an unprecedented opportunity for the understanding of the atomistic interactions underlying carbonaceous nanoparticle structures and growth. The integrated multi-scale simulation approach provides a detailed, molecular level description of the structure of fine particles, which are generated during the combustion of hydrocarbons. With the results obtained using this novel approach, it will be possible to significantly broaden this research into important directions, such as the influence of these particles on human health and global warming. The integration of experimental studies and theoretical simulations, in multi-level time and particle size scales, will increase the overall understanding of nanoparticle formation and transformation. This is an important aspect of the intellectual contribution, beyond the increased scientific understanding at any one scale. The research activities proposed will advance discovery through the development of computational models that will elucidate for the first time ever the mechanisms of nanoparticle formation in a chemically specific way.The broader educational impacts of the proposed project will be significant as well, through the direct involvement of graduate students in the research project, as well as outreach activities in scientific education and to underrepresented groups. The research and educational activities combined will advance understanding through the teaching of computational chemistry and molecular modeling, which will provide students the opportunity to gain a deeper understanding of the physical and chemical processes involved using these multimedia-based approaches for effective teaching.