Population of neutron-rich nuclei around 48ca with deep inelastic collisions

The deep inelastic reaction 48Ca+64Ni at 6 MeV/A has been studied using the CLARA–PRISMA setup. Angular distributions for pure elastic scattering and total cross-sections of the most relevant transfer channels have been measured. The experimental results are compared with predictions from a semiclassical model, showing good agreement for the presently analyzed few neutrons transfer channels. The decay of the most intense reaction products has also been studied, giving indications of the population of states with very short lifetimes.Gadea Raga, Andrés, [email protected]

On the gasification of biomass: Data analysis and regressions

The use of solid wastes as a way to produce energy and chemicals is one of the frontiers in chemistry. One of these methods is the biomass gasification. In this thermal treatment the biomass is heated in a partially oxidizing environment using different process conditions. The variability of both biomass composition and process conditions can lead the thermal treatment to several different results. In order to find a methodology for the classification of all the involved data a dataset containing biomass characterization, gasification process conditions and obtained syngas properties have been gathered from the literature. This dataset has been analysed through multivariate analysis. Principal component analysis (PCA) and a partial least square analysis (PLS) have been performed. Several correlations among different biomass and their gasification products have been found among input parameters, such as biomass properties and process conditions, and output variables like products composition and properties

On the gasification of biomass: Data analysis and regressions

The use of solid wastes as a way to produce energy and chemicals is one of the frontiers in chemistry. One of these methods is the biomass gasification. In this thermal treatment the biomass is heated in a partially oxidizing environment using different process conditions. The variability of both biomass composition and process conditions can lead the thermal treatment to several different results. In order to find a methodology for the classification of all the involved data a dataset containing biomass characterization, gasification process conditions and obtained syngas properties have been gathered from the literature. This dataset has been analysed through multivariate analysis. Principal component analysis (PCA) and a partial least square analysis (PLS) have been performed. Several correlations among different biomass and their gasification products have been found among input parameters, such as biomass properties and process conditions, and output variables like products composition and properties