Publications by authors named "Athanasios Tsolakis"

This work presented the influence of metal oxides as the support for silver-supported catalysts on the catalytic oxidation of diesel particulate matter (DPM). The supports selected to be used in this work were CeO (reducible), ZnO (semiconductor), TiO (reducible and semiconductor), and AlO (acidic). The properties of the synthesized catalysts were investigated using XRD, TEM, H-TPR, and XPS techniques.

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Soot formation models become increasingly important in advanced renewable fuels formulation for soot reduction benefit. This work evaluates performance of machine learning (ML) and deep learning (DL) to predict yield sooting index (YSI) from chemical structure and proposes a tailor-made convolution neural network (CNN)-SDSeries38 for regression problem. In ML, a novel quantitative structure-property relationship (QSPR) is developed for feature extraction and the relationship between molecular structure and YSI is built by ML algorithm.

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The influence of a platinum:palladium (Pt:Pd)-based diesel oxidation catalyst (DOC) on the engine-out particulate matter (PM) emissions morphology and structure from the combustion of alternative fuels (including alcohol-diesel blends and rapeseed oil methyl ester (RME) biodiesel) was studied. PM size distribution was measured using a scanning mobility particulate spectrometer (SMPS), and the PM morphology and microstructure (including size distribution, fractal geometry, and number of primary particles) was obtained using high-resolution transmission electron microscopy (TEM). It is concluded that the DOC does not modify the size or the microstructural parameters of the primary particulates that make up the soot agglomerates.

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