Soot inception: Carbonaceous nanoparticle formation in flames

JW Martin, M Salamanca, M Kraft - Progress in Energy and Combustion …, 2022 - Elsevier
The route by which gas-phase molecules in hydrocarbon flames form condensed-phase
carbonaceous nanoparticles (incipient soot) is reviewed. These products of incomplete …

A review of recent research results on soot: The formation of a kind of carbon-based material in flames

J **, G Yang, J Cai, Z Gu - Frontiers in Materials, 2021 - frontiersin.org
As a product generated from incomplete combustion, soot is harmful to people's health and
the environment. In recent decades, much attention has been paid to the control of soot …

Effects of adding cyclohexane, n-hexane, ethanol, and 2, 5-dimethylfuran to fuel on soot formation in laminar coflow n-heptane/iso-octane diffusion flame

H Chu, Y Ya, X Nie, F Qiao, E Jiaqiang - Combustion and Flame, 2021 - Elsevier
The molecular structure strongly affects the fuel sooting propensity. This study aims to
investigate the effects of oxygen-free and oxygen-containing aliphatic and aromatic …

Effects of ammonia on morphological characteristics and nanostructure of soot in the combustion of diesel surrogate fuels

K Zhang, Y Xu, Y Li, Y Liu, B Wang, H Wang… - Journal of Hazardous …, 2023 - Elsevier
The morphological characteristics and nanostructure of soot particles in pure n-heptane (C 7
H 16) and n-heptane/ammonia co-flow diffusion flames were analyzed and compared using …

Soot formation in n-heptane/air laminar diffusion flames: effect of toluene addition

X Nie, J Qi, S Feng, Y Liu, B Qiu, H Chu - Fuel Processing Technology, 2022 - Elsevier
The mixture of n-heptane and toluene is regarded as surrogate fuel for diesel. Under the
premise of a certain carbon flow rate, the particle size, nanostructure, microcrystalline size …

A machine learning model for predicting threshold sooting index (TSI) of fuels containing alcohols and ethers

MAA Qasem, VCO van Oudenhoven, AA Pasha… - Fuel, 2022 - Elsevier
In this work, a machine learning based model using artificial neural networks (ANN) was
developed for the prediction of threshold sooting index (TSI) of fuels containing oxygenated …

Smoke point prediction of oxygenated fuels using neural networks

MAA Qasem, EM Al-Mutairi, AGA Jameel - Fuel, 2023 - Elsevier
Smoke point (SP) is an important fuel property that characterizes the propensity of aviation
jet fuels and kerosene to form soot. In the present study, an artificial neural network (ANN) …

Bio-derived lactones–Combustion and exhaust emissions of a new class of renewable fuels

J Frost, P Hellier, N Ladommatos - Energy Conversion and Management, 2023 - Elsevier
The use of bioderived drop-in fuels is an essential step in the reduction in fossil fuel usage.
While ethanol and biodiesel are known quantities, the use of novel biomass that does not …

Biodiesel surrogate and ethane evaluation for green carbon black and turquoise hydrogen synthesis via thermal plasma

R Lawson, S Dasappa, J Diab, M McCormick… - Energy Conversion and …, 2024 - Elsevier
The impact of feedstock variation on conversion, yield (hydrogen and solid carbon), carbon
black size, structure and morphology is examined by means of a thermal plasma reactor. In …

[BOEK][B] Thermoacoustic combustion instability control: Engineering applications and computer codes

D Zhao - 2023 - books.google.com
Thermoacoustic Combustion Instability Control: Engineering Applications and Computer
Codes provides a unique opportunity for researchers, students and engineers to access …