In the present study, Calcium oxide (CaO) obtained from eggshells has been used as a heterogeneous catalyst for biodiesel production from highly viscous non-edible rubber seed oil (RSO). Characterization of synthesized catalyst was done with the help of scanning electron microscope equipped with Energy dispersive spectrometry (SEM-EDS), X-ray diffraction (XRD) and Fourier transform Infrared spectroscopy (FTIR). Response surface methodology (RSM) with central composite design (CCD) was used to optimize the process parameters and ¹ H-NMR (Nuclear Magnetic Resonance) spectroscopy analysis was performed to find the conversion of RSO to biodiesel. A conversion of 99.7% of RSO to biodiesel was obtained at 12:1 methanol to oil molar ratio, 4 (wt%) of catalyst, and 3 hour reaction time with a quadratic regression model of R ² of value 0.9566 was obtained. The composition of prepared biodiesel is estimated with the help of Gas Chromatogram-Mass Spectroscopy (GC-MS) analysis. Artificial Neural Network (ANN) with Levenberg-Marquardt algorithm was also trained to predict biodiesel conversion and the value of R ² obtained was 0.9976. It was observed that predicted conversion values from ANN were better when compared to prediction using RSM.

Carbon blacks are an extensively used manufactured product. There exist different grades by which the carbon black is classified, based on its purpose and end use. Different properties inherent to the various carbon black types are a result of their production processes. Based on the combustion condition and fuel used, each process results in a carbon black separate from those obtained from other processes. These carbons differ in their aggregate morphology, particle size, and particle nanostructure. Nanostructure is key in determining the material’s behavior in bulk form. A variety of carbon blacks have been analyzed and quantified for their lattice parameters and structure at the nanometer scale, using transmission electron microscopy and custom-developed fringe analysis algorithms, to illustrate differences in nanostructure and their potential relation to observed material properties.

Development of the regeneration process on diesel particulate filters requires a better understanding of soot oxidation phenomena, especially its relation to soot nanostructure. Nitrogen dioxide (NO₂) is known to play an essential role in passive regeneration by oxidizing soot at low temperatures, especially in the presence of oxygen (O₂) in the exhaust. However, change in soot nanostructure due to oxidation by NO₂–O₂ mixtures has not received much attention. This work focuses on nanostructure evolution during passive regeneration of the diesel particulate filter by oxidation of soot at normal exhaust gas temperatures (300°C–400°C). High-resolution transmission electron microscopy of partially oxidized model carbons (R250, M1300, arc-generated soot) and diesel soot under NO₂–O₂ mixtures is used to investigate physical changes in nanostructure correlating with the material’s behavior during oxidation. Microscopy reveals the changing nanostructure of model carbons during oxidation while fringe analysis of the images points to the differences in the structural metrics of fringe length and tortuosity of the resultant structures. The variation in oxidation rates highlights the inter-dependence of the material’s reactivity with its structure. NO₂ preferentially oxidizes edge-site carbon, promotes surface oxidation by altering the particle’s burning mode with increased overall reactivity of NO₂+O₂ resulting in inhibition of internal burning, typically observed by O₂ at exhaust gas temperatures.

Air pollution has become the world’s single biggest environmental health risk of the past decade, causing millions of yearly deaths worldwide. One of the dominant air pollutants is fine particulate matter (PM_2.5), which is a product of combustion. Exposure to PM_2.5 has been associated with decreased lung function, impaired immunity, and exacerbations of lung disease. Accumulating evidence suggests that many of the adverse health effects of PM_2.5 exposure are associated with lung inflammation and oxidative stress. While the physical structure and surface chemistry of PM_2.5 are surrogate measures of particle oxidative potential, little is known about their contributions to negative health effects. In this study, we used functionalized carbon black particles as surrogates for atmospherically aged combustion-formed soot to assess the effects of PM_2.5 surface chemistry in lung cells. We exposed the BEAS-2B lung epithelial cell line to different soot at a range of concentrations and assessed cell viability, inflammation, and oxidative stress. Our results indicate that exposure to soot with varying particle surface composition results in differential cell viability rates, the expression of pro-inflammatory and oxidative stress genes, and protein carbonylation. We conclude that particle surface chemistry, specifically oxygen content, in soot modulates lung cell inflammatory and oxidative stress responses.