19 resultados para fast pyrolysis bio-oil components


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Neisseria meningitidis is a gram negative human obligated pathogen, mostly found as a commensal in the oropharyngeal mucosa of healthy individuals. It can invade this epithelium determining rare but devastating and fast progressing outcomes, such as meningococcal meningitidis and septicemia, leading to death (about 135000 per year worldwide). Conjugated vaccines for serogroups A, C, W135, X and Y were developed, while for N. meningitidis serogroup B (MenB) the vaccines were based on Outern Membrane Vesicles (OMV). One of them is the 4C-MenB (Bexsero). The antigens included in this vaccine’s formulation are, in addition to the OMV from New Zeland epidemic strain 98/254, three recombinant proteins: NadA, NHBA and fHbp. While the role of these recombinant components was deeply characterized, the vesicular contribution in 4C-MenB elicited protection is mediated mainly by porin A and other unidentified antigens. To unravel the relative contribution of these different antigens in eliciting protective antibody responses, we isolated human monoclonal antibodies (mAbs) from single-cell sorted plasmablasts of 3 adult vaccinees peripheral blood. mAbs have been screened for binding to 4C-MenB components by Luminex bead-based assay. OMV-specific mAbs were purified and tested for functionality by serum bactericidal assay (SBA) on 18 different MenB strains and characterized in a protein microarray containing a panel of prioritized meningococcal proteins. The bactericidal mAbs identified to recognize the outer membrane proteins PorA and PorB, stating the importance of PorB in cross-strain protection. In addition, RmpM, BamE, Hyp1065 and ComL were found as immunogenic components of the 4C-MenB vaccine.

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Dynamical models of stellar systems represent a powerful tool to study their internal structure and dynamics, to interpret the observed morphological and kinematical fields, and also to support numerical simulations of their evolution. We present a method especially designed to build axisymmetric Jeans models of galaxies, assumed as stationary and collisionless stellar systems. The aim is the development of a rigorous and flexible modelling procedure of multicomponent galaxies, composed of different stellar and dark matter distributions, and a central supermassive black hole. The stellar components, in particular, are intended to represent different galaxy structures, such as discs, bulges, halos, and can then have different structural (density profile, flattening, mass, scale-length), dynamical (rotation, velocity dispersion anisotropy), and population (age, metallicity, initial mass function, mass-to-light ratio) properties. The theoretical framework supporting the modelling procedure is presented, with the introduction of a suitable nomenclature, and its numerical implementation is discussed, with particular reference to the numerical code JASMINE2, developed for this purpose. We propose an approach for efficiently scaling the contributions in mass, luminosity, and rotational support, of the different matter components, allowing for fast and flexible explorations of the model parameter space. We also offer different methods of the computation of the gravitational potentials associated of the density components, especially convenient for their easier numerical tractability. A few galaxy models are studied, showing internal, and projected, structural and dynamical properties of multicomponent galaxies, with a focus on axisymmetric early-type galaxies with complex kinematical morphologies. The application of galaxy models to the study of initial conditions for hydro-dynamical and $N$-body simulations of galaxy evolution is also addressed, allowing in particular to investigate the large number of interesting combinations of the parameters which determine the structure and dynamics of complex multicomponent stellar systems.

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In this study, a novel hybrid thermochemical-biological refinery integrated with power-to-x approach was developed for obtaining biopolymers (namely polyhydroxyalkanoates, PHA). Within this concept, a trilogy process schema comprising of, (i) thermochemical conversion via integrated pyrolysis-gasification technologies, (ii) anaerobic fermentation of the bioavailable products obtained through either thermochemistry or water-electrolysis for volatile fatty acids (VFA) production, (iii) and VFA-to-PHA bioconversion via an original microaerophilic-aerobic process was developed. During the first stage of proposed biorefinery where lignocellulosic (wooden) biomass was converted into, theoretically fermentable products (i.e. bioavailables) which were defined as syngas and water-soluble fraction of pyrolytic liquid (WS); biochar as a biocatalyst material; and a dense-oil as a liquid fuel. Within integrated pyrolysis - gasification process, biomass was efficiently converted into fermentable intermediates representing up to 66% of biomass chemical energy content in chemical oxygen demand (COD) basis. In the secondary stage, namely anaerobic fermentation for obtaining VFA rich streams, three different downstream process were investigated. First fermentation test was acidogenic bioconversion of WS materials obtained through pyrolysis of biomass within an original biochar-packed bioreactor, it was sustained up to 0.6 gCOD/L-day volumetric productivity (VP). Second, C1 rich syngas materials as the gaseous fraction of pyrolysis-gasification stage, was fermented within a novel char-based biofilm sparger reactor (CBSR), where up to 9.8 gCOD/L-day VP was detected. Third was homoacetogenic bioconversion within the innovative power-to-x pathway for obtaining commodities via renewable energy sources. More specifically, water-electrolysis derived H2 and CO2 as a primary greenhouse gas was successfully bio-utilized by anaerobic mixed cultures into VFA within CBSR system (VP: 18.2 gCOD/L-day). In the last stage of the developed biorefinery schema, VFA is converted into biopolymers within a new continuous microaerophilic-aerobic microplant, where up to 60% of PHA containing sludges was obtained.

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The urgent need for alternative solutions mitigating the impacts of human activities on the environment has strongly opened new challenges and opportunities in view of the energy transition. Indeed, the automotive industry is going through a revolutionary moment in its quest to reduce its carbon footprint, with biofuels being one of the viable alternatives. The use of different classes of biofuels as fuel additives/standalone components has attracted the attention of many researchers. Despite their beneficial effects, biofuel’s combustion can also result in the production of undesirable pollutants, requiring complete characterization of the phenomena occurring during their production and consumption. Industrial scale-up of biomass conversion is challenging owing to the complexity of its chemistry and transport phenomena involved in the process. In this view, the role of solid-phase and gas-phase chemistry is paramount. Thus, this study is devoted to detailed analysis of physical-chemical phenomena characterizing biomass pyrolysis and biofuel oxidation. The pyrolysis mechanism has been represented by 20 reactions whereas, the gas-phase kinetic models; manually upgraded model (KiBo_MU) and automated model (KiBo_AG), comprises 141 species and 453 reactions, and 631 species and 28329 reactions, respectively. The accuracy of the kinetic models was tested against experimental data and the models captured experimental trends very well. While the development and validation of detailed kinetic mechanisms is the main deliverable of this project, the realized procedure integrating schematic classifications with methodologies for the identification of common decomposition pathways and intermediates represents an additional source of novelty. Besides, the fundamentally oriented nature of the adopted method allows the identification of most relevant reactions and species under the operating conditions different industrial applications, paving the way for reduced kinetic mechanisms. Ultimately, the resulting detailed mechanisms can be used to integrate with more complex fluid dynamics model to accurately reproduce the behavior of real systems and reactors.