Aromatic Compound and Soot Precursor Formation in Diffusion Flames

摘要- Pfefferle 这是一项研究碳氢化合物的增长机制，导致形成的碳烟和碳烟前体的扩散火焰条件下，这样的条件是相关的最实际的燃烧条件。 目的是确定燃烧条件和燃料结构对芳环化合物和碳烟形成途径的影响。 研究了单一燃料火焰和掺有低浓度各种碳氢化合物的甲烷扩散火焰。 烟尘体积分数为0.1 ppm，烟尘的形态和组成，多环芳烃（PAH），和稳定的中间物种存在于1 ppm以上的水平和测量。 在扩散火焰中重要的特定反应途径的研究也在分子束采样良好的混合反应器，以获得详细的反应参数。 这种方法允许快速，定量的物种采样扩散火焰与显着的烟尘负荷。 反应产物使用真空紫外（VUV）光电离检测。 烟尘测量技术允许检测亚ppm烟尘体积分数，并包括测量可能是成熟烟尘的直接前体的半透明颗粒。 利用该技术，可以区分前驱体颗粒和成熟烟灰，分析其成分，并跟踪石墨化过程。 与不完全燃烧有关的烟尘和PAH被认为是主要的健康危害。 对这些物质的形成和特性进行详细研究，可以确定哪些系统构成更大的威胁，并提出控制战略。

Abstract - Pfefferle This is a study of hydrocarbon growth mechanisms that lead to the formation of soot and soot precursors under diffusion flame conditions; such conditions are relevant to most practical combustion conditions. The objective is to determine the effects of combustion conditions and fuel structure on the formation pathways of aromatic ring compounds and soot. Both single-fuel flames and methane diffusion flames doped with low concentrations of various hydrocarbons are studied. Soot volume fraction to 0.1 ppm, morphology and composition of soot, polycyclic aromatic hydrocarbons (PAH), and stable intermediate species present at levels above 1 ppm and measured. Particular reaction pathways important in the diffusion flames are studies also in a molecular-beam-sampled well-mixed reactor to obtain detailed reaction parameters. This methodology allows fast, quantitative species sampling in diffusion flames with significant soot loadings. Reaction products are detected using vacuum ultraviolet (VUV) photoionization. The soot measurement technique allows detection of sub-ppm soot volume fractions and includes measurement of the translucent particles that may be the direct precursors of mature soot. With this technique, precursor particles can be discriminated from mature soot, their composition analyzed, and the process of graphitization followed. Soot and PAH associated with incomplete combustion are recognized as major health hazards. Detailed studies of the formation and character of these materials can identify which systems pose the greater threats and also suggest control strategies.