A solvothermal method was used to prepare zinc ferrite spinel oxide (ZnFe2O4) using ethylene glycol and 1,4 butanediol as solvent diols, and the influence of diols on the physical properties of ZnFe2O4 particles was investigated. The produced particles were characterized by X-ray powder diffraction (XRD), atomic force microscopy (AFM), Fourier transform infrared spectroscopy (FTIR) and nitrogen adsorption isotherms, and the catalytic activity for the organic pollutant decomposition by heterogeneous photo-Fenton reaction was investigated. Both solvents produced particles with cubic spinel structure. Microporous and mesoporous structures were obtained when ethylene glycol and 1,4 butanediol were used as diols, respectively. A higher pore volume and surface area, as well as a higher catalytic activity for the pollutant degradation were found when 1,4 butanediol was used as solvent.
Maize drying is an important process, especially for storage and conservation. For this study, the experimental stage was carried out using a forced convection dryer with air heated at different temperature conditions (306.05–441.85 K) and flow (0.13–0.256 m3/hr), totalizing 15 drying curves. Then the performances of the classic drying kinetics methodology and the approach proposed in this paper, in which the increase in moisture content of the product with time was represented combining exponential models and neural networks based on wavelets, were compared. Good performance was obtained in predictions using the proposed approach. One of the main differentials of the methodology adopted was the obtainment of a model that has a global predictive capacity, within the range of tested operating conditions, which can be used in predicting drying curves for different operating conditions.
Practical applications
The drying process is also one of the most widely used methods for preserving food, and has the advantage of reducing the costs of storage and transport because of the low volume and weight of the end product. During the last years, this topic has attracted a broad industrial interest, resulting in many research studies investigating the drying process. Usually, with regard to the classic approach for modeling of the drying process, the kinetics of drying curves obtained in different operating conditions is affected separately, that is, the parameters are estimated independently, resulting in different regression problems. With the classical approach, in general, it is not possible to obtain a comprehensive prediction model with regards to operating conditions. We have proposed an alternative modeling method. Aiming to obtain a modeling tool with an overall predictive ability, an approach for drying kinetics prediction that combines exponential models and neural networks was proposed. The proposed modeling method was able to predict drying curves for different operating conditions.
The kinetics of the hot‐air drying of soybeans was modeled in order to evaluate the influence of temperature and velocity on the kinetic parameters. A convective dryer with air temperature from 30 to 195C and air flows of 0.75, 1.35, 2.0 and 2.5 m/s was used. Three different mathematical models were applied to simulate the drying process (two empirical equations, exponential and Page's, and Fick's diffusion model) and the diffusivity coefficient increased from 2.5 × 10−11 to 6.69 × 10−10 m2/s for a range of air temperature between 30 and 195C. Both temperature and velocity influenced drying rate. The differential evolution optimization method was used toward parameter estimation. The goodness of fit of the proposed models, evaluated using linear regression coefficient (R2), chi‐squared parameter (χ2) and root mean square error, indicated a satisfactory validation, mainly regarding to the exponential and Page's models.
Practical Applications
Although biological materials are dried to improve shelf life, reduce packaging costs and enhance sensorial aspects, they are highly susceptible to quality deterioration during dehydration if the processing parameters are not well adjusted. The mathematical modeling of food drying provides results about the influence of process parameters on energy efficiency and final product quality in order to help the optimization and upscale application. Given that up to 40% of the agro‐industrial production is lost in developing countries due to the lack of processing and that an energy efficiency improvement of 1% may result in 10% increase in profit, it is important to explore the potential of mathematical tools to properly study drying processes under an energy and qualitative approach.
This study evaluated the operational conditions that maximize the production of biogas from the use of digesters. Experimental tests were conducted using termination phase swine wastes, with total . Regarding the use of nutrients in the anaerobic digestion process, the results showed that there was significant reduction in hydraulic retention time and increased biogas productivity.
Neste trabalho, foi realizado um estudo para avaliar as principais variáveis de processo na produção de uma bebida fermento-destilada a partir do pseudofruto da uva-japão (Hovenia dulcis Thunberg). Foram avaliados os efeitos da temperatura, do tempo de fermentação e da adição de micronutrientes (Mn+2 e K+) sobre a graduação alcoólica, além do pH e dos teores de ésteres presentes nas amostras. A partir dos resultados experimentais obtidos, constatou-se que o pH (pH médio da fração "coração" 5,35) da bebida fermento-destilada a partir da uva-japão não é afetado pelos fatores testados. Para a graduação alcoólica e a concentração de ésteres (2,81 ± 3,13 mg.100mL-1) presentes na fração "coração" da bebida produzida, os fatores mais significativos foram a temperatura e a concentração de Mn+2. A uva-japão se mostrou uma alternativa viável para a produção de uma bebida fermento-destilada ou como matéria-prima para a produção de bioálcool para usos diversos (95 a 100 GL).
Estudo da degradação de compostos fenólicos presente em águas residuárias de postos de combustíveis utilizando fungos filamentosos (Aspergillus Flavus)
ResumoDiversos compostos são sintetizados e produzidos industrialmente, onde, em sua maioria, são dificilmente degradados ou reciclados na forma em que se encontram. Grande parcela do processo de contaminação pode ser atribuída aos compostos fenólicos, encontrados nas mais diversas concentrações em águas residuárias de postos de combustíveis. Neste estudo, buscou-se isolar e identificar fungos filamentosos com capacidade de degradação de compostos fenólicos e avaliar, através da utilização de técnicas de planejamento experimental, os fatores: temperatura e pH no rendimento da degradação dos compostos fenólicos. A linhagem do fungo isolada foi a de Asperillus flavus. Através dos resultados obtidos verificou-se que a linhagem de fungos estudada é pouco afetada por variações no pH e apresentou melhor desempenho na temperatura de 25°C e pH 8, com degradação de 6,7 ppm de fenol.Palavras-chave: Fungos filamentosos, Compostos fenólicos, Tratamento de efluentes, Planejamento experimental..
AbstractSeveral compounds are synthesized and industrially produced, where in most cases, are hardly degraded or recycled in the way they are. A large portion of contamination process can be attributed to phenolic compounds found with different concentrations in wastewater from gas stations. In this study, we attempted to isolate and identify filamentous fungi capable of phenolic compounds degradation and evaluate, using experimental design techniques, the effects of temperature and pH on degradation yield of phenolic compounds. Aspergillus flavus fungi lineage was isolated in this study. Results showed that the fungi lineage was little affected by changes in pH and showed better performance at 25°C and pH 8, when 6.7 ppm of phenol was degraded.
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