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Evaluation of yield-predictive models of biocrude from hydrothermal liquefaction of microalgae

2019; Elsevier BV; Volume: 44; Linguagem: Inglês

10.1016/j.algal.2019.101669

2211-9264

Alejandra Palomino, Luis Carlos Montenegro Ruíz, Rubén Darío Godoy-Silva,

Biodiesel Production and Applications

The prediction capacity of published component additivity and kinetic models was analyzed for calculation of the biocrude yield of hydrothermal liquefaction of microalgae. Their advantages and limitations were identified. Likewise, the effect of reaction temperature and retention time was evaluated on the yield of the biocrude for the kinetic models for four hypothetical biomasses. From the analysis of the component additivity and kinetic models, a new quantitative model was proposed for the calculation of biocrude yield of microalgae. The new model was tested with large numbers of experimental data published over a wide range of temperatures (200–400 °C), retention times (1–120 min) and chemical composition of microalgae (0.0–66% lipids, 9–75% proteins, 5–64% carbohydrates, in dry basis). The predictive capacity of the new model was compared with component additivity and kinetic models. Results show that the model captures better the trend of the experimental data. This model predicted 45% of the biocrude yields published within the standard deviation zone ± 5% and 78% of the total data was within the zone of standard deviation ± 10%. The combined model predicts yields of up to 60% for lipid-rich biomasses and shows a better linear distribution between experimental and predicted yields than any other currently available model.