Impact of alcohol–diesel fuel blends on soot primary particle size in a compression ignition engine

The use of alternative fuels, such as bio-alcohols, in advanced propulsion systems could a feasible strategy to address several of the current issues associated to the use of internal combustion engines fuelled by carbonaceous fossil fuels. Particularly, soot particles, are one of the key pollutants emitted from compression ignition engines. Therefore, the development of soot formation prediction models providing new understanding on the impact of alternative fuels combustion in compression ignition engines become essential for soot mitigation purposes. This study proposes a new semi-empirical model that predicts in-cylinder soot primary particle growth from an engine fuelled with alcohol–diesel fuel blends. The model uses macroscopic experimental measurements of engine parameters such as instantaneous in-cylinder pressure. Furthermore, an empirical correlation is presented predicting the mean soot primary particle size as a function of alcohol–diesel fuel blend properties and fuel/air ratio. The experimental measurement of primary soot particle mean size are obtained from High Resolution Transmission Electron Microscope (HT-TEM) micrographs obtained from soot particles collected via thermophoresis. Overall, the research findings presented in this work contributes to propose environmentally friendly fuel candidates for transportation.F.J. Martos expresses thanks (1) the government of Spain for supporting his research stay with reference PRX19/00187 at University of Birmingham and (2) the University of Malaga for supporting through the supercomputing and Bioinnovation Center and in particular to the supercomputer Picasso belonging to the Spanish Supercomputing Network. ESPRC is acknowledged for supporting this work with the project FACE (ESPRC: ref. EP/P03117X/1). // Funding for open access charge: Universidad de Málaga / CBU

Performance of a drop-in biofuel emulsion on a single-cylinder research diesel engine

Current targets in reducing CO2 and other greenhouse gases as well as fossil fuel depletion have promoted the research for alternatives to petroleum-based fuels. Pyrolysis oil (PO) from biomass and waste oil is seen as a method to reduce life-cycle CO2, broaden the energy mix and increase the use of renewable fuels. The abundancy and low prices of feedstock have attracted the attention of biomass pyrolysis in order to obtain energy-dense products. Research has been carried out in optimising the pyrolysis process, finding efficient ways to convert the waste to energy. However, the pyrolysis products have a high content in water, high viscosity and high corrosiveness which makes them unsuitable for engine combustion. Upgrading processes such as gasification, trans-esterification or hydro-deoxynegation are then needed. These processes are normally costly and require high energy input. Thus, emulsification in fossil fuels or alcohols is being used as an alternative. In this research work, the feasibility of using PO-diesel emulsion in a single-cylinder diesel engine has been investigated. In-cylinder pressure, regulated gaseous emissions, particulate matter, fuel consumption and lubricity analysis reported. The tests were carried out of a stable non-corrosive wood pyrolysis product produced by Future Blends Ltd of Milton Park, Oxfordshire, UK. The product is trademarked by FBL, and is a stabilized fraction of raw pyrolysis oil produced in a process for which the patent is pending. The results show an increase in gaseous emissions, fuel consumption and a reduction in soot. The combustion was delayed with the emulsified fuel and a high variability was observed during engine operation

Non-PGM hollow fibre-based after-treatment for emission control under real diesel engine exhaust gas conditions

\ua9 2024. Hollow fibre (HF)-based technologies for emission control, as an alternative to the traditional monolithic technology, offers a promising route to the uptake of non-PGM catalytic systems. In this work, a series of Cu-doped LaCoO3 perovskites were investigated as potential non-PGM Diesel Oxidation Catalysts (DOC). Two HF-based modules, comprising single-channel (i.e., 1CM) and four-channel (i.e., 4CM) HFs respectively, were impregnated with the best catalyst candidate, and their performance was tested under real exhaust gas conditions, using a single-cylinder diesel engine. Compared to the 1CM, the 4CM demonstrated enhanced CO conversion, and reduced performance towards Total Hydrocarbon (THC) conversion. Overall, these findings reveal the influence of HF morphology on catalytic performance, and in turn, will contribute towards the refinement of HF-based technology for emission control, as well as enabling the transition towards non-PGM catalytic systems

Validation of pncA gene sequencing in combination with the mycobacterial growth indicator tube method to test susceptibility of Mycobacterium tuberculosis to pyrazinamide.

Item does not contain fulltextPyrazinamide is important in the treatment of tuberculosis. Unfortunately, the diagnosis of pyrazinamide resistance is hampered by technical difficulties. We hypothesized that mutation analysis combined with the mycobacterial growth indicator tube (MGIT) phenotypic method would be a good predictor of pyrazinamide resistance. We prospectively analyzed 1,650 M. tuberculosis isolates referred to our tuberculosis reference laboratory in 2008 and 2009. In our laboratory, the MGIT 960 system was used for pyrazinamide resistance screening. If a pyrazinamide-resistant strain was detected, we performed a pncA gene mutation analysis. A second MGIT 960 susceptibility assay was performed afterwards to evaluate the accuracy of the pncA mutation analysis to detect true- or false-positive MGIT results. We observed pyrazinamide resistance in 69 samples using the first MGIT 960 analysis. In a second MGIT 960 analysis, 47 of the 69 samples proved susceptible (68% false positivity). Sensitivity of nonsynonymous pncA mutations for detecting resistant isolates was 73% (95% confidence interval [CI], 61% to 73%), and specificity was 100% (95% CI, 95% to 100%). A diagnostic algorithm incorporating phenotypic and molecular methods would have a 100% positive predictive value for detecting pyrazinamide-resistant isolates, indicating that such an algorithm, based on both methods, is a good predictor for pyrazinamide resistance in routine diagnostics.1 februari 201