Physical-chemical and mineralogical characterization of fine aggregates from construction and demolition waste recycling plants

Construction and demolition waste (CDW) represents around 31% of all waste produced in the European Union. It is today acknowledged that the consumption of raw materials in the construction industry is a non-sustainable activity. It is thus necessary to reduce this consumption, and the volume of CDW dumped, by using this waste as a source of raw materials for the production of recycled aggregates. One potential use of these aggregates is their incorporation in reinforced concrete as a replacement of natural aggregates. A concrete that incorporates these aggregates and still performs well requires them to be fully characterized so that their behaviour within the concrete can be predicted. Coarse recycled aggregates have been studied quite thoroughly, because they are simpler to reintroduce in the market as a by-product, and so has the performance of concrete made with them. This paper describes the main results of research designed to characterize the physical and chemical properties of fine recycled aggregates for concrete production and their relationship with mineralogical composition and preprocessing. The constraints of the incorporation of fine aggregates in reinforced concrete are discussed. It is shown that, unless a developed processing diagram is used, this application is not feasible. (C) 2013 Elsevier Ltd. All rights reserved.

Projecto de conceito e estrutura de uma aplicação mobile para a marca NIVEA

Trabalho de projecto apresentado à Escola Superior de Comunicação Social como parte dos requisitos para obtenção de grau de mestre em Publicidade e Marketing.

Caracterização laboratorial de misturas betuminosas com incorporação de agregado siderúrgico inerte para construção (ASIC)

Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia Civil na Área de Especialização de Vias de Comunicação e Transportes

In Situ Near-Infrared (NIR) Versus High-Throughput Mid- Infrared (MIR) Spectroscopy to Monitor Biopharmaceutical Production

The development of biopharmaceutical manufacturing processes presents critical constraints, with the major constraint being that living cells synthesize these molecules, presenting inherent behavior variability due to their high sensitivity to small fluctuations in the cultivation environment. To speed up the development process and to control this critical manufacturing step, it is relevant to develop high-throughput and in situ monitoring techniques, respectively. Here, high-throughput mid-infrared (MIR) spectral analysis of dehydrated cell pellets and in situ near-infrared (NIR) spectral analysis of the whole culture broth were compared to monitor plasmid production in recombinant Escherichia coil cultures. Good partial least squares (PLS) regression models were built, either based on MIR or NIR spectral data, yielding high coefficients of determination (R-2) and low predictive errors (root mean square error, or RMSE) to estimate host cell growth, plasmid production, carbon source consumption (glucose and glycerol), and by-product acetate production and consumption. The predictive errors for biomass, plasmid, glucose, glycerol, and acetate based on MIR data were 0.7 g/L, 9 mg/L, 0.3 g/L, 0.4 g/L, and 0.4 g/L, respectively, whereas for NIR data the predictive errors obtained were 0.4 g/L, 8 mg/L, 0.3 g/L, 0.2 g/L, and 0.4 g/L, respectively. The models obtained are robust as they are valid for cultivations conducted with different media compositions and with different cultivation strategies (batch and fed-batch). Besides being conducted in situ with a sterilized fiber optic probe, NIR spectroscopy allows building PLS models for estimating plasmid, glucose, and acetate that are as accurate as those obtained from the high-throughput MIR setup, and better models for estimating biomass and glycerol, yielding a decrease in 57 and 50% of the RMSE, respectively, compared to the MIR setup. However, MIR spectroscopy could be a valid alternative in the case of optimization protocols, due to possible space constraints or high costs associated with the use of multi-fiber optic probes for multi-bioreactors. In this case, MIR could be conducted in a high-throughput manner, analyzing hundreds of culture samples in a rapid and automatic mode.