Daria Podstawczyk

Application of response surface methodology and artificial neural network methods in modelling and optimization of biosorption process

A review on the application of response surface methodology (RSM) and artificial neural networks (ANN) in biosorption modelling and optimization is presented. The theoretical background of the discussed methods with the application procedure is explained. The paper describes most frequently used experimental designs, concerning their limitations and typical applications. The paper also presents ways to determine the accuracy and the significance of model fitting for both methodologies described herein. Furthermore, recent references on biosorption modelling and optimization with the use of RSM and the ANN approach are shown. Special attention was paid to the selection of factors and responses, as well as to statistical analysis of the modelling results.

Biosorption of malachite green by eggshells: Mechanism identification and process optimization

In the present work, eggshells were used to remove a dye (malachite green) from wastewater. The study was focused on identification and describing the binding mechanism of the dye by eggshells in a biosorption process optimized by Response Surface Methodology based on the Box-Behnken Design. The mechanism of biosorption was determined by characterization of the biosorbent before and after biosorption using scanning electron microscopy, X-ray diffraction analysis, the Brunauer-Emmett-Teller isotherm method, Fourier transform infrared spectroscopy. The second-order polynomial equation and 3D response surface plots were used to quantitatively determine the relationships between dependent and independent variables. The obtained results suggested the mechanism of wastewater treatment that included physical adsorption, alkaline fading phenomenon and microprecipitation. The results of the present study showed that waste eggshells have the potential to be used as an inexpensive but effective biosorbent useful in wastewater treatment.

Modelling and optimization of chromiumIII biosorption on soybean meal

In this investigation a waste biological material, soybean meal, was applied as a biosorbent for heavy metal ions (CrIII). The diffusive Webber-Morris model and the pseudo-II-order model suitably described the kinetics of CrIII ions binding on soybean meal. The Langmuir-Freundlich equation was valid for the description of the isotherm. Inductively coupled plasma optical emission spectroscopy (ICP-OES), FTIR and scanning electron microscopy with an energy dispersive X-ray analytical system (SEM-EDX) were used in order to identify the mechanism of the metal ions binding. The analysis of the composition of the enriched soybean meal confirmed the contribution of ion exchange in the biosorption process. Three-variable-three-level Box-Behnken design was used to determine the optimal conditions for biosorption of CrIII on soybean meal. The optimal conditions for predicted maximum Cr3+ uptake (61.07 mg g−1) by soybean meal were estimated by Matlab and established as temperature of 38.04°C, initial metal concentration 500 mg L−1 and biosorbent dosage 1 g L−1.Graphical abstract

Enrichment of soybean meal with microelements during the process of biosorption in a fixed-bed column.

The aim of the present investigation was to enrich the mineral content of soybean meal with essential chromium and copper metal ions by a biosorption technique in a fixed-bed column. The values of column parameters were determined at various process conditions: pH, temperature, flow rate, and concentration of the feed solution; mass and size of the particles of the bed to determine the breakthrough curves. Biosorption efficiency at optimal conditions (pH 5.0, temperature = 20 °C, Cr(3+) concentration = 200 mg/L, flow rate = 10 mL/min, and sorbent mass = 40 g) was 71.4%. Maximum uptake for Cr(III) and Cu(II) obtained in column was around 15.3 and 12.3 mg/g, respectively. The model constants obtained in this study can be used for design pilot plant systems. Soybean enriched with microelements by biosorption can be considered as biological carrier of microelements and therefore used as the component of livestock feed.

Concentration of natural aroma compounds from fruit juice hydrolates by pervaporation in laboratory and semi-technical scale. Part 1. Base study

The first article of a two-article series presents pervaporation (PV) of volatile aroma compounds from fruit juice hydrolates (plum, apple, blackcurrant and cherry). The purpose of this research was to evaluate the effectiveness of fruit juice hydrolates separation on a laboratory scale (inert gas flow pervaporation system) and semi-technical (vacuum pervaporation system) by means of pervaporation. To create precise matrices for hydrolates before and after pervaporation for each of the separated systems, solid phase microextraction (SPME) technique and the gas chromatography-mass spectrometry (GC-MS) was applied. Sensory analysis confirmed improvement of aroma note of concentrated permeates as compared to feed hydrolates solutions. The results indicated that pervaporation may be applied in condensing aromatic water or fruit juice hydrolate, which may significantly enhance product quality and lengthen shelf life.