Predicting cetane number,kinematic viscosity,density and higher heating value of biodiesel from its fatty acid methyl ester composition

Biodiesel is a renewable bio-fuel derived from natural fats or vegetable oils, and it is considered as a promising alternative to substitute diesel fuels. Cetane number, viscosity, density, and higher heating value are important properties to affect the utilization of biodiesel fuels, because they are involved in the definition of fuel quality and are required as input data for predictive engine combustion models. This work presents the characterization of two biodiesel samples made from beef tallow and soybean oil through their fatty acid methyl esters (FAMEs) profile. Empirical equations were developed to estimate four physical properties of methyl esters; and an average absolute deviation (AAD) of 5.95%, 2.57%, 0.11% and 0.21% for the cetane number, kinematic viscosity, density, and higher heating value were founded. Cetane number, viscosity, and higher heating value increases because of the increase of molecular weight and these physical properties decrease as the number of double bonds increases. Unlike that of above properties, density decreases as molecular weight increases and density increases as the degree of unsaturation increases. Two general mixing rules and five biodiesel samples were used to study the influence of FAMEs over the physical properties of biodiesel. The prediction of the cetane number, kinematic viscosity, density and higher heating value of biodiesel is very close to the experimental values.     

Star-shaped hexaaryltriindoles small molecules: Tuning molecular properties towards solution processed organic light emitting devices

We present a series of differently substituted star-shaped hexaaryltriindoles with tunable light-emitting properties. The deep blue emission is unchanged by donor peripheral substituents while an increasing acceptor character produces a reduction of the optical gap, an increased Stokes shift and eventually leads to the appearance of a new electronic level and to the simultaneous deep blue (413 nm) and green (552 nm) emission in solution. Quenching by concentration increases with the acceptor character but is lower as the tendency of these compounds to aggregate is stronger. Solution processed thin films present optical and morphological qualities adequate for device fabrication and similar electronic structure compared to solutions with an emission range from 423 nm up to 657 nm (red), demonstrating the possibility of tuning the energy levels by chemical functionalization. We have fabricated and characterized single-layer solution processed organic light emitting diodes (OLED) to investigate the influence on transport and emission properties of the substituting species. We analyzed the I–V response using a single-carrier numerical model that includes injection barriers and non-uniform electric-field across the layer. As a result, we obtained the electric field dependence of the mobility for each device. Best results are obtained on the most electron rich derivative functionalized with six donor methoxy groups. This material shows the highest emission efficiency in solid state, due to aggregation-induced enhancement, and better transport properties with the highest mobility and a very low turn-on voltage of 2.8 V. The solution processed OLED devices produce stable deep blue (CIE coordinates (0.16, 0.16)) to white (CIE coordinates (0.33, 0.3)) emission with similar luminous efficiencies.     

Exploiting the relationships among several binary classifiers via data transformation

The structural resemblance among several existing classifiers has motivated us to investigate their underlying relationships. By exploring into the mapping solutions of these classifiers, we found that they can be linked by simple feature data scaling. In other words, the key to these relationships lies upon how the replica of feature data are being scaled. This finding leads us directly to an exploration of novel classifiers beyond existing settings. Based on an extensive empirical evaluation, we show that the proposed formulation facilitates a tuning capability beyond existing settings for classifier generalization.     

Bimodal polypropylene through binary metallocene catalytic systems: comparison between hybrid and mixed heterogeneous catalysts

Polypropylene with wider or bimodal molecular weight distribution is required for numerous applications since low molecular weight chains improve processability and high molecular weight fraction is required to get good mechanical properties. There are several routes to achieve a bimodal resin but the use of a binary catalytic system seems to be the most attractive, particularly with metallocenes combination. From a previous work two metallocenes were selected because they lead to polypropylenes with average molecular weights that differ in one order of magnitude. Two types of binary systems have been investigated, hybrid catalysts (two metallocenes loaded on the same support) and physical mixtures (two independent supported metallocenes that are introduced to the reactor and start the polymerization together), using different ratios, i.e., 25–75, 50–50, 75–25, at three reaction temperatures, i.e., 30, 50 and 70 °C. Most of the binary catalytic systems lead to bimodal molecular weight distributions. Polypropylenes produced by mixed catalysts are greatly influenced by the most active catalyst, while in PP coming from hybrid catalysts, as there is a strong interaction between both metallocenes, each one contributes according to its presence in the hybrid catalyst. Therefore, properties of obtained bimodal polypropylenes are quite influenced by the ratio between both metallocenes.     

Analyzing growth and mortality in a subtropical urban forest ecosystem

Information on urban tree growth, mortality and in-growth is currently being used to estimate urban forest structure changes and ecosystem services such as carbon sequestration. This study reports on tree diameter growth and mortality in 65 plots distributed among four land use categories, which were established in 2005/2006 in Gainesville, Florida, USA and were re-measured in 2009. Models for mortality and in-growth models were developed by grouping species into hardwoods and softwoods. Annual change in tree diameter at breast height growth was analyzed using three tree species groups based on potential height and longevity. Additionally, the four most common tree species in the study area were modeled to explore factors affecting tree growth. The average annual mortality rate in the city was 9.97%. Trees located in Institutional land use/land cover (LULC) had the highest annual mortality rate (19.2%/yr), and commercial had the lowest (3.1%/yr). Overall, growth rates for the study area (0.70 cm/yr) and residential LULC (0.80 cm/yr) were comparable to other studies. Growth rates for trees in forested areas were higher (0.56 cm/yr) than those previously reported. Individual species-level growth rates such as those for Juniperus virginiana (1.24 cm/yr) and Quercus virginiana (1.08 cm/yr) were different than other species values reported in other studies. Maintenance activities, site conditions, soil properties, tree characteristics, and LULC significantly influenced urban tree growth, mortality, and in-growth. Results can be used to better understand urban forest ecosystem structure and services in medium sized, subtropical cities and to make better decisions regarding planting and maintenance strategies.     

Management Levers for Product Platforms

Platforming has become an important means of cost-sharing among industrial products. However, many firms face systemic downward pressure on commonality, with the result that many platforms realize less commonality than intended. Past research has hypothesized that divergence is the result of conflicting tensions between product customization/optimization and cost control. This article investigates the control and incentive levers available to platform managers to shape the behavior of the organization when divergence opportunities arise. Management levers are drawn from a series of 12 industrial case studies, stemming from investigations of the causes of divergences. These management levers are categorized as technical levers, financial levers, and organizational levers. This article illustrates each of the management levers with examples from the case studies.