清晨好,您是今天最早来到科研通的研友!由于当前在线用户较少,发布求助请尽量完整的填写文献信息,科研通机器人24小时在线,伴您科研之路漫漫前行!

Modeling soot formation in flames and reactors: Recent progress and current challenges

烟灰 燃烧 炭黑 热解 碳纤维 甲烷 纳米技术 工艺工程 材料科学 化学 有机化学 工程类 复合数 复合材料 天然橡胶
作者
Murray J. Thomson
出处
期刊:Proceedings of the Combustion Institute [Elsevier]
卷期号:39 (1): 805-823 被引量:14
标识
DOI:10.1016/j.proci.2022.07.263
摘要

The study of soot has long been motivated by its adverse impacts on health and the environment. However, this combustion knowledge is also relevant to the production of carbon black and hydrogen via methane pyrolysis which are important commodities. Over the last decade, steady progress has been made in the development of detailed continuum models of soot formation in flames and reactors. Developing more comprehensive models has often been motivated by the need for predicting soot formation over a wider range of conditions (e.g., temperature, pressure, fuels). Measurements with novel experimental techniques have given us new insights into the chemistry, particle dynamics and optical properties of soot particles and even molecules and radicals forming them. Also, multi-scale modeling has enabled us to translate the detailed mechanisms of soot processes based on first principles into computationally efficient but accurate continuum models of soot formation in flames and reactors. However, important questions remain including (1) what is the mechanism of soot inception and surface growth, (2) which gas-phase species are involved in soot inception and surface growth (3) how surface growth and oxidation are affected by soot surface properties. Proposed models need to be evaluated against experimental data over a wide range of conditions to determine their predictive strength. These questions are critical for the accurate prediction of soot formation in flames and its emissions from engines. However, this knowledge can also be used to develop predictive process design and optimization tools for carbon black and other nanocarbon formation in reactors.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
大幅提高文件上传限制,最高150M (2024-4-1)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
xianyaoz完成签到 ,获得积分10
4秒前
风起枫落完成签到 ,获得积分10
21秒前
光亮的自行车完成签到 ,获得积分10
22秒前
亮总完成签到 ,获得积分10
25秒前
29秒前
Somnus完成签到 ,获得积分10
31秒前
科研通AI2S应助smile采纳,获得10
35秒前
海鹏完成签到 ,获得积分10
37秒前
47秒前
迅速的幻雪完成签到 ,获得积分10
59秒前
bookgg完成签到 ,获得积分10
1分钟前
jjaigll12完成签到 ,获得积分10
1分钟前
1分钟前
单小芫完成签到 ,获得积分10
1分钟前
su完成签到 ,获得积分10
1分钟前
小阿博发布了新的文献求助10
1分钟前
小阿博发布了新的文献求助10
1分钟前
温如军完成签到 ,获得积分10
1分钟前
1分钟前
艮爚完成签到 ,获得积分10
1分钟前
酷炫的尔丝完成签到 ,获得积分10
1分钟前
琉璃岁月发布了新的文献求助10
1分钟前
logolush完成签到 ,获得积分10
1分钟前
1分钟前
yinyin完成签到 ,获得积分10
2分钟前
QJZ完成签到 ,获得积分10
2分钟前
小阿博发布了新的文献求助10
2分钟前
NexusExplorer应助小阿博采纳,获得10
2分钟前
神勇的天问完成签到 ,获得积分10
2分钟前
qq完成签到 ,获得积分10
2分钟前
饼子完成签到 ,获得积分10
2分钟前
zh完成签到 ,获得积分10
3分钟前
wwwwwl完成签到 ,获得积分10
3分钟前
3分钟前
3分钟前
丰知然应助雪山飞龙采纳,获得10
3分钟前
小阿博发布了新的文献求助10
3分钟前
CodeCraft应助小阿博采纳,获得10
3分钟前
雪山飞龙完成签到,获得积分10
3分钟前
蟲先生完成签到 ,获得积分10
3分钟前
高分求助中
Licensing Deals in Pharmaceuticals 2019-2024 3000
Cognitive Paradigms in Knowledge Organisation 2000
Effect of reactor temperature on FCC yield 2000
How Maoism Was Made: Reconstructing China, 1949-1965 800
Medical technology industry in China 600
Introduction to Spectroscopic Ellipsometry of Thin Film Materials Instrumentation, Data Analysis, and Applications 600
Promoting women's entrepreneurship in developing countries: the case of the world's largest women-owned community-based enterprise 500
热门求助领域 (近24小时)
化学 医学 生物 材料科学 工程类 有机化学 生物化学 物理 内科学 纳米技术 计算机科学 化学工程 复合材料 基因 遗传学 催化作用 物理化学 免疫学 量子力学 细胞生物学
热门帖子
关注 科研通微信公众号,转发送积分 3311249
求助须知:如何正确求助?哪些是违规求助? 2943948
关于积分的说明 8516779
捐赠科研通 2619328
什么是DOI,文献DOI怎么找? 1432227
科研通“疑难数据库(出版商)”最低求助积分说明 664536
邀请新用户注册赠送积分活动 649815