Soot-in-Oil 3D Volume Reconstruction Through the Use of Electron Tomography: An Introductory Study

Significance Statement

In this work, we investigate the development and application of electron tomograpy for characterisation of soot agglomerates as a new capability to yield information on the volumetric character of fractal nanoparticles.

Soot is formed during combustion of hydrocarbon fuel in automotive engines due to non-stoichiometric, incomplete combustion conditions. Fuel-rich zones formed due to inadequate mixing of the fuel-air mixture prior to ignition, typically in direct injection engines, lead to the formation of soot. Most of the soot is expelled from the cylinder with the exhaust gases while a small proportion is transferred to the lubricating oil. Limiting the exhaust gas soot nanoparticles of both diesel and gasoline engines is one of the main objectives of new proposed emission regulations across the globe. Soot accumulation in oil can lead to lubricant performance deteriorating and severe engine wear. Soot thickening increases oil viscosity, penalising fuel economy and increasing CO2 emissions. This is a factor limiting the service life of the oil, typically requiring a change of 4 litres of lubricant every 13,000 km of vehicle use. In 2011, there were 28.5 million diesel cars licensed for use on the roads in Great Britain. Based on such figures, 114 million litres of oil have to be regularly replaced. If the concept of ‘sealed for life’ engines is to become reality a better understanding of soot behaviour in engine oil is also of paramount importance.

Characterisation of soot permits effective study of in-cylinder soot formation processes and accurate modelling enhancing fundamental knowledge. Characterisation of morphological parameters enhances understanding of soot as an atmospheric pollutant, soot-related engine wear, and detailed design of improved lubricant oils, fuel additives. Filtration and soot oxidation processes in particulate filters also depend on accurate information on soot particle size, shape and structure.

Typically, two-dimensional transmission electron microscopy (TEM) images have been used extensively in the characterisation of both exhaust soot and so-called soot-in-oil. However, considering the fractal and highly irregular nature of soot particles the apparent morphology of a particle can change beyond recognition when seen from two-dimensional images. As TEM images are 2D projections of 3D objects, calculations of some 3D parameters are inferred by application of approximations. Accuracy in the measurement of 3D morphological properties is of upmost importance for the design and optimisation of the future low soot emission vehicles. Electron tomography volume reconstruction generates three-dimensional soot models allowing for surface area and volume to be measured. Morphological and microstructural features of soot particulate can then be investigated allowing for 3D properties to be measured and for the true 3D nature of soot particles to be accounted for entirely. The proposed work demonstrates the feasibility of electron tomography for three-dimensional characterisation of soot nanoparticles; proposing a new methodology to give measurable 3D soot models that are of practical use to industry.

  

 Soot-in-Oil 3D Volume Reconstruction Through the Use of Electron Tomography: An Introductory Study.Advances in Engineering

 

About the author

Dr La Rocca is Assistant Professor of Thermofluids, Faculty of Engineering at the University of Nottingham and Course Director for the Mechanical Engineering courses. Dr La Rocca is a Chartered Engineer, Member of the Institute of Mechanical Engineers and Member of the SAE International; this highlights dedication to maintaining competence and committing to professional development.

His research and development expertise are in areas of internal combustion engines for light duty passenger vehicles for both spark ignition and diesel engines. These include combustion, performance and emissions. He has attracted funding in these areas and published highly cited papers in leading journals; with more than 50 high quality publications as papers, chapter in books and conference contributions and has a Scopus h Index is 8. He has a strong track record in experimental research in collaboration with industry. Dr La Rocca leads the Soot Diagnostic Suite at the University of Nottingham focusing the development of novel soot characterisation techniques. His future research focuses on the characterisation of morphological parameters to enhance understanding of soot as an atmospheric pollutant, soot-related engine wear, detailed design of improved lubricant oils and fuel additives. The novel diagnostics tools developed by his research group are also used to design and optimise particulate filters as well as modelling nanofluids.

E-mail: [email protected]

Journal Reference

Tribology Letters, January 2016, 61:8.

La Rocca, Campbell, W. Fay, Orhan

Engine Research Group, Department of Mechanical, Materials and Manufacturing Engineering, University of Nottingham, University Park, Nottingham, NG7 2RD, UK

Abstract

Understanding soot nanoparticle interaction with oil additives and the causes of soot-induced thickening would assist in lubricant formulation, prolonging engine life and improving engine efficiency. Three-dimensional measurement of soot structures is currently not undertaken as established techniques are limited to two dimensions. While they give valuable information on the structure and reactivity of soot nanoparticles, it is not easy to correlate this to geometry of primary particles and agglomerates. In this work, we investigate the development and application of 3D-TEM for characterisation of soot agglomerates as a new capability to yield information on the volumetric character of fractal nanoparticles. This investigation looks at the feasibility for volume reconstruction of nanometric soot particles in used engine oil from multiple imaging at different tilt angles. Bright-field TEM was used to capture two-dimensional images of soot. Heptane and diethyl ether washes were used to remove volatile contaminants and allowed for images from −60° to +60° tilt with no sign of carbon build-up to be acquired. Tomographic reconstruction from the aligned tilt-series images based on weighted back-projection algorithm has yielded useful information about complex soot nanoparticle size. Estimation of soot mass in oil by nanoparticle tracking analysis (NTA) can be considerably improved by taking into account the three-dimensional shape of the soot agglomerate including the shape factor in the calculations. 3D-TEM measurements were compared with values calculated by using a single-sphere approach when tracking nanoparticles moving under Brownian motion. A shape factor was calculated, dividing the surface area and volume calculated using spherical geometrical estimates, by the respective values calculated using the 3D models. The spherical model of the particle is found on average to overestimate the surface area by sevenfold, and the volume to the actual soot agglomerate by 23 times. Applying the calculated shape factor as a correction reduces the NTA overestimation by one order of magnitude.

 

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