A Multiscale Model for Restructuring of Atmospheric Soot Particles

大气烟灰颗粒重构的多尺度模型

• 批准号: 2222104
• 负责人: Alexei Khalizov
• 金额: $ 61.96万
• 依托单位: New Jersey Institute of Technology
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-11-01 至 2025-10-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2222104&HistoricalAwards=false
• 关键词: Multiscale; Model; Restructuring; Atmospheric; Soot

This project is focused on the development of a multiscale model to predict the evolution of soot particles during atmospheric processing. The nature of soot particles can change after emission through restructuring when they come in contact with trace gas chemicals and water vapor in the atmosphere. Advances in modeling the atmospheric processing of soot will help to reduce uncertainties in the atmospheric lifetime of soot and also will improve the assessment of the impacts of soot on air quality, human health, and climate.This effort will address outstanding questions on the origin and magnitude of changes to soot aggregates, including: (1) the stress induced by condensate located in junctions between monomers and monomer branches, and (2) the forces holding together the individual monomers. A Discrete Element Method (DEM) model will be developed in which soot restructuring is driven by stresses from a growing or shrinking layer of condensate and resisted by necks between monomers. The DEM model will be parameterized using atomic-level simulations and lab experiments. Experiments will be conducted using mass-mobility measurements, electron microscopy, and atomic force microscopy to obtain the required neck parameters (number and size distribution, strength, and atomic structure). Two major soot aging mechanisms will be considered: the condensation of trace-gas chemicals to form coatings, and the subsequent cloud processing of coated soot particles.This project will provide interdisciplinary training for graduate and undergraduate students and young researchers in a rich interdisciplinary environment.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.

该项目的重点是开发多尺度模型，以预测大气加工过程中烟灰颗粒的演变。烟灰颗粒在与痕量气体化学物质和大气中的水蒸气接触时，烟灰颗粒的性质可能会改变。 Advances in modeling the atmospheric processing of soot will help to reduce uncertainties in the atmospheric lifetime of soot and also will improve the assessment of the impacts of soot on air quality, human health, and climate.This effort will address outstanding questions on the origin and magnitude of changes to soot aggregates, including: (1) the stress induced by condensate located in junctions between monomers and monomer branches, and (2) the forces holding together the individual单体。将开发一个离散的元素方法（DEM）模型，其中烟灰重组是由凝结物的增长或收缩层的应力驱动的，并由单体之间的颈部抵抗。 DEM模型将使用原子级模拟和实验室实验进行参数化。实验将使用质量运动测量，电子显微镜和原子力显微镜进行，以获得所需的颈部参数（数量和尺寸分布，强度和原子结构）。将考虑两种主要的烟灰老化机制：痕量气体化学物质形成涂料，随后对涂层的烟灰颗粒的云处理处理。该项目将为研究生和本科生提供跨学科的培训。 标准。