Sonoprocessing of oil: Asphaltene declustering behind fine ultrasonic emulsions

乳化燃料 沥青质 乳状液 化学工程 材料科学 燃烧 破损 油滴 化学 复合材料 有机化学 工程类
作者
Elia Colleoni,Gianmaria Viciconte,Chiara Canciani,Saumitra Saxena,Paolo Guida,William L. Roberts
出处
期刊:Ultrasonics Sonochemistry [Elsevier BV]
卷期号:98: 106476-106476 被引量:8
标识
DOI:10.1016/j.ultsonch.2023.106476
摘要

Despite the transition toward carbon-free energy carriers, liquid fossil fuels are expected to occupy an important market share in the future. Therefore, it is crucial to develop innovative technology for better combustion reducing the emissions of pollutants associated with their utilization. Water in oil (w/o) emulsions contribute to greener combustion, increasing carbon efficiency and reducing emissions. Water content, emulsions stability, and droplet size distributions are key parameters in targeting the efficient use of emulsions as combustibles. In particular, for fixed water content, the finer the emulsion, the better its beneficial effect on combustion. In this work, two emulsions, mechanically and ultrasonically generated, were compared. Cryogenic scanning electron microscopy (cryo-SEM) allowed the visualization of water droplets inside the oily matrix. No surfactants were added to the oil, due to its high asphaltenic content. Asphaltene molecular aggregates, namely clusters, act as natural surfactants stabilizing the emulsions by arranging at w/o interface and forming a rigid film. The asphaltenic rigid film is clearly visualized in this work and compared for the two emulsions. The results showed finer water droplets in the ultrasonically generated emulsion, together with a reduction in the thickness of the asphaltenic film. Ultrasonically induced cavitation favored the de-clustering (breakage of intermolecular forces) of asphaltene molecules. Thus, smaller clusters allowed to stabilize smaller water droplets resulting in an ultra-fine emulsion, which improves the combustion performances of the fuel.
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
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
刚刚
dopamine完成签到,获得积分0
2秒前
达芙完成签到,获得积分10
2秒前
PANYIAO完成签到,获得积分10
2秒前
明亮的念梦完成签到 ,获得积分10
3秒前
chyvayne完成签到,获得积分10
3秒前
4秒前
Akim的应助被c程序语言采纳,获得10
4秒前
5秒前
干净一鸣发布了新的文献求助10
5秒前
Akim的应助被Awen采纳,获得10
5秒前
6秒前
CLW发布了新的文献求助10
6秒前
6秒前
molihuakai的应助被man采纳,获得10
6秒前
7秒前
脑洞疼的应助被刘先生采纳,获得10
7秒前
7秒前
ssmffryjj888完成签到,获得积分10
8秒前
master发布了新的文献求助10
8秒前
10秒前
喵笙之夜发布了新的文献求助10
11秒前
12秒前
12秒前
顺鑫发布了新的文献求助10
12秒前
13秒前
杨雯娜完成签到,获得积分10
14秒前
耍酷的指甲油完成签到,获得积分10
15秒前
Akim的应助被以太歌声采纳,获得10
15秒前
xiongjie发布了新的文献求助10
16秒前
龙猫发布了新的文献求助10
17秒前
17秒前
18秒前
18秒前
喜羊羊完成签到,获得积分10
18秒前
星辰大海的应助被干净一鸣采纳,获得30
18秒前
innocence发布了新的文献求助10
18秒前
hq发布了新的文献求助10
18秒前
pe完成签到,获得积分10
18秒前
ZSXL完成签到,获得积分10
20秒前
高分求助中
(应助此贴封号)通过应助OA文献获取积分 10000
Rosenblum, Global Change Biology 800
The Student's Guide to Social Neuroscience 600
Computational Chemical Reaction Engineering: Modeling, Simulation, and Design with MATLAB 600
Organizational Behavior 510
Management and the Arts 510
A Will for the Machine: Computerization, Automation, and the Arts in South Africa 400
热门求助领域 (近24小时)
化学 材料科学 医学 生物 计算机科学 工程类 纳米技术 内科学 物理 有机化学 化学工程 生物化学 复合材料 光电子学 细胞生物学 心理学 量子力学 催化作用 物理化学 电极
热门帖子
关注 科研通微信公众号,转发送积分 7811081
求助须知:如何正确求助?哪些是违规求助? 9342785
关于积分的说明 20514212
捐赠科研通 7403993
什么是DOI,文献DOI怎么找? 3329655
关于科研通互助平台的介绍 2476408
邀请新用户注册赠送积分活动 2348584