Current Organizations / Institutes

The organizations/institutes from the scholar's latest article


Sara Pardilhó has a total of 5 co-authors. Here are the top co-authors by number of shared publications:

  • Joana Maia Dias

    LEPABE - Laboratory for Process Engineering, Environment, Biotechnology and Energy, ALiCE - Associate Laboratory in Chemical Engineering, Faculty of Engineering, Department of Mechanical Engineering, University of Porto, Rua Dr. Roberto Frias, 4200-465 Porto, Portugal

    2 shared publications
  • Joana Oliveira

    Department of Chemical Engineering, Faculty of Engineering, Laboratory for Process Engineering, Environment, Biotechnology and Energy (LEPABE), University of Porto, Porto, Portugal

    1 shared publication
  • Joana Oliveira

    LEPABE—Laboratory for Process Engineering, Environment, Biotechnology and Energy, ALiCE—Associate Laboratory in Chemical Engineering, Faculty of Engineering, University of Porto, Rua Dr. Roberto Frias, 4200-465 Porto, Portugal

    1 shared publication
  • José C. Pires

    Department of Chemical Engineering, Faculty of Engineering, Laboratory for Process Engineering, Environment, Biotechnology and Energy (LEPABE), University of Porto, Porto, Portugal

    1 shared publication
  • José Carlos Magalhães Pires

    LEPABE, AliCE, Faculty of Engineering, University of Porto, Rua Dr. Roberto Frias, 4200-465 Porto, Portugal

    1 shared publication

Latest Publications

  • Open Access

    Bioethanol Production from Marine Macroalgae Waste: Optimisation of Thermal acid Hydrolysis

    by Sara Pardilhó, Joana Oliveira, José C. Pires, Joana Maia Dias

    Marine macroalgae waste, resulting from the accumulation of drifted algal biomass along the coastline, might be a relevant complementary raw material aiming sustainable bioethanol production. In the present study, the optimisation of thermal acid hydrolysis was performed using response surface methodology (RSM) considering the effect of three variables, namely, reaction time (10–60 min), acid concentration (0.1–2.5% (v/v) H2SO4) and biomass:acid ratio (5–15% (w/v)) on sugar concentration and yield. Under the best conditions, the resulting hydrolysates were fermented (7 days, 30 °C, 150 rpm, commercial yeast) to produce bioethanol. A statistically valid second-order model was obtained (r2 = 0.9876; Prob > F lower than 0.05), showing that sugar concentration is mostly influenced by the biomass:acid ratio while reaction time was not significant. The maximum predicted sugar concentration was 18.4 g/L, being obtained at 2.5% H2SO4 concentration and 15% (w/v) biomass:acid ratio, corresponding to a sugars yield of 12.5 g/100 g (less 36% than that obtained using 10% (w/v)). At the best conditions, the hydrolysates were fermented to obtain a bioethanol concentration up to 2.4 g/L and a 21 mgbioethanol/gbiomass yield, emphasizing the biomass potential for bioenergy production. Graphical Abstract


  • Open Access

    Microalgae to Bioenergy: Optimization of Aurantiochytrium sp. Saccharification

    by Joana Oliveira, Sara Pardilhó, Joana M. Dias, José C. M. Pires

    Microalgae are a promising feedstock for bioethanol production, essentially due to their high growth rates and absence of lignin. Hydrolysis—where the monosaccharides are released for further fermentation—is considered a critical step, and its optimization is advised for each raw material. The present study focuses on the thermal acid hydrolysis (with sulfuric acid) of Aurantiochytrium sp. through a response surface methodology (RSM), studying the effect of acid concentration, hydrolysis time and biomass/acid ratio on both sugar concentration of the hydrolysate and biomass conversion yield. Preliminary studies allowed to establish the range of the variables to be optimized. The obtained models predicted a maximum sugar concentration (18.05 g/L; R2 = 0.990) after 90 min of hydrolysis, using 15% (w/v) biomass/acid ratio and sulfuric acid at 3.5% (v/v), whereas the maximum conversion yield (12.86 g/100 g; R2 = 0.876) was obtained using 9.3% (w/v) biomass/acid ratio, maintaining the other parameters. Model outputs indicate that the biomass/acid ratio and time are the most influential parameters on the sugar concentration and yield models, respectively. The study allowed to obtain a predictive model that is very well adjusted to the experimental data to find the best saccharification conditions for the Aurantiochytrium sp. microalgae.