Experimental validation off-line a nonlinear controller for removal of chromium using non-living cells of Yarrowia lipolytica.

The removal of hexavalent chromium [Cr (VI)] using non-living cells of Yarrowia lipolytica was investigated. Batch and continuous studies on removal of Cr (VI) achieved 97% and 99% removal from aqueous phase, respectively. The specific uptake values at pH of 2 in batch process were 40.73 ± 1.3 mg/g and 30.09 ± 0.23 mg/g on non-living cells, when 100 and 200 mg/L of metal Cr (VI) concentrations were used. In order to investigate the regulation of Cr (VI) under continuous operation based on reaction volume numerically a new class of feedback controller from structure polynomial was designed. The proposed methodology was used to an experimentally kinetic model for a removal Cr (VI) from Yarrowia lipolytica biomass was showed satisfactory closed-loop performance the proposed controller. Starting from an off-line optimization performed in simulation, we present the controller implementation, focussing on the methodology required to could be suitable for implementation in real time. In our experimental results, we highlight some discrepancies between simulation and reality despite these differences, the controller managed to perform convergence to removal Cr (VI). Finally, the results validated with off-line samples suggest that the proposed control could be suitable for in application in potential scenarios for wastewater treatment.

A novel kinetic model for a cocoa waste fermentation to ethanol reaction and its experimental validation.

A non-segregated kinetic model is proposed to describe a fermentation process of agro-industrial residues derived via cocoa (mucilage juice) by Pichia kudriavzevii. The novel proposed hybrid model is based on a multiple coupling reaction mechanisms (structured) to describe the kinetics of substrate consumption, biomass, carbon dioxide, and ethanol, coupled to an unstructured model for the activity enzyme. The parameters of the kinetic model are estimated by non-linear least-squares curve fitting using the Marquardt-Levenberg algorithm. In addition, numerical simulations were compared with the experimental data via residual graphs. The effectiveness of the model was statistically evaluated using dimensionless efficiency coefficients under different initial conditions. A global sensitivity analysis was applied (Fisher's information matrix). The experimental results of the batch reactor showed a maximum ethanol concentration of 29 g/L, with a yield of 0.48 g-ethanol/g-glucose and a productivity of 0.30 g/L h. The method determined that the cell formation coefficient and the specific substrate consumption rate (θ1 and θ2) directly influence most of the states of our system. The proposed scheme is particularly suitable to assist in the rational design of cell factory properties or fermentation processes because it can represent the complex biochemistry in more detail and under different initial experimental conditions; the above reveals that the generated model is robust and can be considered for control and optimization purposes.

Experimental and kinetic study for lead removal via photosynthetic consortia using genetic algorithms to parameter estimation.

This work presents an experimental-theoretical strategy for a batch process for lead removal by photosynthetic consortium, conformed by algae and bacteria. Photosynthetic consortium, isolated from a treatment plant wastewater of Tecamac (Mexico), was used as inoculum in bubble column photobioreactors. The consortium was used to evaluate the kinetics of lead removal at different initial concentrations of metal (15, 30, 40, 50, and 60 mgL-1), carried out in batch culture with a hydraulic residence time of 14 days using Bold's Basal mineral medium. The photobioreactor was operated under the following conditions: aeration of 0.5 vvm, 80 µmol m-2 s-1 of photon flux density and a photoperiod light/dark 12:12. After determining the best growth kinetics of biomass and metal removal, they were tested under different ratios (30 and 60%) of wastewater-culture medium. Additionally, the biomass growth (X), nitrogen consumption (N), chemical oxygen demand (COD), and metal removal (Pb) were quantified. Achieved lead removal was 97.4% when the initial lead concentration was up to 50 mgL-1 using 60% of wastewater. Additionally, an unstructured-type mathematical model was developed to simulate COD, X, N, and lead removal. Furthermore, a comparison between the Levenberg-Marquardt (L-M) optimization approach and Genetic Algorithms (GA) was carried out for parameter estimation. Also, it was concluded that GA has a slightly better performance and possesses better convergence and computational time than L-M. Hence, the proposed method might be applied for parameter estimation of biological models and be used for the monitoring and control process.