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RISS 인기검색어
- 검색키워드
- 저자 : Gabriela Buema (검색결과 3 건)
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Removal of cadmium(II) from aqueous solution by adsorption onto modified algae and ash
Maria Harja,Gabriela Buema,Laura Bulgariu,Dumitru Bulgariu,Daniel-Mircea Sutiman,Gabriela Ciobanu 한국화학공학회 2015 Korean Journal of Chemical Engineering Vol.32 No.9
Pollution with cadmium ions has serious negative consequences on human health and environment. Adsorption of low-cost materials represents a viable option for the removal of cadmium ions from aqueous media. In this study are comparatively discussed the adsorption behaviour of cadmium(II) on two low-cost materials, one of biologic nature (marine algae) and other of inorganic nature (ash), after their treatment with alkaline solution. The influence of contact time and initial cadmium ions concentration was studied in batch system, for each type of adsorbent. In optimum experimental conditions (solution pH of 5.0; adsorbent dose of 8 g L−1) and an initial cadmium concentration of 360mg L−1, the obtained uptake capacities reach to 34.15mg g−1 for the modified algae and to 43.12mg g−1 for the modified ash, respectively. The uptake data were analyzed using two isotherm models (Langmuir and Freundlich) and the models’ parameters were evaluated. The results indicate that t heLangmuir model provides the best correlation of experimental data for both adsorbents, and the maximum adsorption capacities were 41.8mg g−1 for modified algae and 48.0 mg g−1 for modified ash, respectively. The kinetics of the cadmium uptake was modelled using the pseudofirst order, pseudo-second order and intra-particle diffusion model equations. It was shown that the pseudo-second order kinetic equation could best describe the adsorption kinetics of cadmium ions, whatever the nature of adsorbent.
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Low cost adsorbents obtained from ash for copper removal
Maria Harja,Gabriela Buema,Daniel-Mircea Sutiman,Corneliu Munteanu,Daniel Bucur 한국화학공학회 2012 Korean Journal of Chemical Engineering Vol.29 No.12
We investigated the utilization of ash and modified ash as a low-cost adsorbent to remove copper ions from aqueous solutions such as wastewater. Batch experiments were conducted to determine the factors affecting adsorption of copper. The influence of pH, adsorbent dose, initial Cu2+ concentration, type of adsorbent and contact time on the adsorption capacity of Cu2+ from aqueous solution by the batch adsorption technique using ash and modified ash as a low-cost adsorbent were investigated. The optimum pH required for maximum adsorption was found to be 5. The results from the sorption process showed that the maximum adsorption rate was obtained at 300 mg/L when a different dosage of fly ash was added into the solution, and it can be concluded that decreasing the initial concentration of copper ion is beneficial to the adsorption capacity of the adsorbent. With the increase of pH value, the removal rate increased. When the pH was 5, the removal rate reached the maximum of over 99%. When initial copper content was 300 mg/L and the pH value was 5, the adsorption capacity of the zeolite Z 4 sample reached 27.904 mg/g. The main removal mechanisms were assumed to be the adsorption at the surface of the fly ash together with the precipitation from the solution. The adsorption equilibrium was achieved at pH 5 between 1 and 4 hours in function of type of adsorbent. A dose of 1 : 25 g/mL of adsorbent was sufficient for the optimum removal of copper ions. For all synthesized adsorbents the predominant mechanism can be described by pseudo-second order kinetics.
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Neuro-evolutionary optimization methodology applied to the synthesis process of ash based adsorbents
Silvia Curteanu,Maria Harja,Gabriela Buema,Ciprian George Piuleac,Daniel-Mircea Sutiman 한국공업화학회 2014 Journal of Industrial and Engineering Chemistry Vol.20 No.2
Ash and modified ash were investigated as alternative adsorbents for copper ions. Our aim was toestablish optimal working conditions for obtaining the new adsorbents, using a neuro-evolutionaryoptimization methodology. The materials were characterized by SEM, FT-IR, EDAX, XRD, and by theremoval percentage. Three multilayer perceptron neural networks were developed and aggregated into astack to form the model of the process. The neural model was integrated into an optimization proceduresolved with a genetic algorithm to obtain the optimum values for the percentage of adsorption. The newadsorbents provide two benefits: environmental protection and energy recovery.
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