Artificial Neural Network Modeling of Mixing Efficiency in a Split-Cylinder Gas-Lift Bioreactor for <i>Yarrowia lipolytica</i> Suspensions

Drăgoi, Elena Niculina; Curteanu, Silvia; Caşcaval, Dan; Galaction, Anca‐Irina

doi:10.1080/00986445.2016.1206892

Cited by 8 publications

(1 citation statement)

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“…Due to its flexibility, it can be adapted and efficiently used to model and/or optimize other types of processes, being successfully applied for modelling the polycyclic aromatic hydrocarbon formation in grilled meat products, [27] for modelling of aqueous mixtures of poly (ethylene glycol) transport and thermodynamic and thermophysical properties, [28] and for modelling and optimization of the UV/peroxydisulfate process used for acid blue 193 removal. [29] Also, similar strategies combining DE and ANNs were successfully applied for biotechnological processes, [30][31][32] indicating that the combination of these two algorithm is also suitable for these types of systems.…”

Section: Introductionmentioning

confidence: 99%

Application of reactive extraction for the separation of pseudomonic acids: Influencing factors, interfacial mechanism, and process modelling

et al. 2021

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Mupirocin (a mixture of A, B, C, and D pseudomonic acids-four complex, similar structures) is an antibiotic belonging to the monocarboxylic acid class, used to cure infections caused by bacteria (Gram-positive), especially methicillin-resistant Staphylococcus aureus (MRSA). Its biotechnological production and separation need constant attention, as improving antibiotics is important in the pharmaceutical industry. This is the first study regarding pseudomonic acids separation through reactive extraction; the experiments were focused on finding a proper combination of extractant and diluent for optimization of the separation yield. The pH influence (4-9) and extractant (TOA and Amberlite LA-2, 5-20 g/L) concentration dissolved in n-heptane (green solvent) have been analyzed, obtaining the maximum extraction yield (88.78%) at pH 4, 20 g/L extractant, and 10% octanol added to the organic solvent. The addition of the phase modifier, 1-octanol, improved the extraction yield by 2.6 times for Pseudomonic acid A due to interactions of formed complexes with the phase modifier that improves its solubility. The experimental results for determining the mechanism of the interfacial reaction showed that, regardless of the pH value and solvent polarity (modified by the addition of 1-octanol), only one molecule of Pseudomonic acid A and extractant react at the aqueous-organic interface. In addition, the system was modelled and optimized with a methodology combining artificial neural networks (ANN) and differential evolution.

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