Prediction of adsorption efficiencies of Ni (II) in aqueous solutions with perlite via artificial neural networks

Abstract

One of the major problems occurring in wastewater is the extensive amount of pollution. These waters are formed by the leakage of snow and moisture in waste materials held in storage sites. High need for oxygen and heavy metal content of the wastewater cause the quality of the receiving environment to deteriorate in the long term. These problems lead to toxic and anaerobic conditions in the receiving environment, fi sh death or exposition to pollution, and deterioration in water quality when the receiving environment is used as a water supply. Therefore, wastewater must be collected before it reaches underground and surface water resources, and should be treated appropriately. The main chemical methods used for treating wastewater are coagulation-fl occulation, chemical deposition and chemical--electrochemical oxidation. Vivek et al. (2014) investigated the physical, chemical and biological methods that exist for the treatment of wastewater. It is generally diffi cult to ensure satisfactory treatment effi ciency and a high quality outfl ow of water by using only a single method. Nadaroglu et al. (2014) studied the removal of copper from aqueous solutions by using micritic limestone. They found that the maximum adsorption capacity was 237.05 mg/g for 1 hour and 1 g dosage. The experimental investigation results show that powdered micritic limestone has a high level of adsorption capacity in terms of copper ions. Adsorption data was correlated with the Langmuir and Freundlich isotherm models. It was found that the Langmuir and Freundlich isotherms fi tted well with the data. Consequently, it was determined that powdered micritic limestone can be used successfully for removing copper ions from aqueous solutions.Moradi et al. studied the adsorption of ammonium ions onto pumice as a natural and low-cost adsorbent. They found the optimum conditions for maximum removal of NH 4 + (70.3%) were found to be 100 g, 20 mg/L, 300 rpm and 180 min, for pumice dosage, initial NH 4 + ion concentration, mixing rate and contact time.For this, a combination of physical, chemical and biological methods is most commonly used. Garcia et al. (2014) explained that the most common physical methods used for the treatment of wastewater are precipitation, refi ning with air conditioning, adsorption and membrane fi ltration. In wastewaters containing heavy metals, refi ning is performed by using many different adsorbent materials. Malkoc et al. (2006) suggested that one such material is tea waste from the fi xed bed column used for removing Nickel (II) from an aqueous solution. Different initial nickel concentrations are input concentrations used in this study. The result obtained show that the adsorbent material obtained from tea factory waste is effi cient, and it is not an expensive material with regard to Nickel (II) removal. In addition, Erdogan et al. Abstract: This study investigates the estimated adsorption effi ciency of artifi cial Nickel (II) ions with perlite in an aqueous solution using artifi cial neural networks, based on 14...

Simultaneous dry-sorption of heavy metals by porous adsorbents during sludge composting

“…Previous studies reported that the most important adsorption phenomena in natural adsorbents such as zeolite and perlite particles are cation exchange, adsorption on the surfaces, and chemisorption of cations on the edge surfaces [10]. The zeolite layer edges are with negatively charged Si and Al oxides and have a strong affinity to complexation with metal cations from the solution [11]. The noted decrease of heavy metal concentration in the final compost samples in the present study (Table 3) suggests that composting moisture and pH profile pro-vided sufficient metal mobility and migration for binding exchangeable and reducible metal fractions onto the tested natural adsorbents [12].…”

“…Natural adsorbents made from zeolite and perlite contains many characteristics conducive to the retention of heavy metals [10]. The structure zeolites consist of Si 4+ and AL 3+ that produce a net negative charge that will be balanced by certain exchangeable cations such as cadmium, copper, lead, and zinc [11]. Likewise, expanded perlite has a large external and internal surface area with micro and nanoscale pores and a certain amount of adsorption capacity to heavy metals [10].…”

Simulation of Ammonia Nitrogen Removal from Simulated Wastewater by Sorption onto Waste Foundry Sand Using Artificial Neural Network

“…Artificial neural networks (ANNs) have been used to investigate the nature of relationship related between the input and output variables. This can be achieved through extracting the controlling features from input database [35] [38] [26]. Accordingly, the feasibility of using WFS in the treatment of water contaminated with ammonia nitrogen depended on batch experimental results and ANN model is the focal point of the present study.…”