• 한국세라믹학회지
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• 제53권3호
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• pp.362-366
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• 2016

In this study, humidity control ceramics with good adsorption/desorption capabilities and high strength were fabricated from drinking-water treatment sludge (DWTS) and Onggi soil. The DWTS powder heat-treated at $800^{\circ}C$ and Onggi soil were mixed at weight ratios of 40:60, 50:50, 60:40, and 70:30 and fired at $800-1000^{\circ}C$. With increasing DWTS content, density and flexural strength increased. For the sample with a DWTS:Onggi soil weight ratio of 70:30, porosity and specific surface area decreased with increasing firing temperature, attributed to densification and grain growth at high firing temperatures. From the results obtained, a firing temperature of $800^{\circ}C$ is the optimum condition for fabricating humidity control ceramics with good adsorption/desorption capabilities and strength. The maximum adsorbed amount for the sample fired at $800^{\circ}C$ was $439g/m^2$.

• Membrane and Water Treatment
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• 제9권5호
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• pp.363-371
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• 2018

In this work, it was investigated the usability of artificial bee colony (ABC) and genetic algorithm (GA) in modeling adsorption of Co(II) onto drinking water treatment sludge (DWTS). DWTS, obtained as inevitable byproduct at the end of drinking water treatment stages, was used as an adsorbent without any physical or chemical pre-treatment in the adsorption experiments. Firstly, DWTS was characterized employing various analytical procedures such as elemental, FT-IR, SEM-EDS, XRD, XRF and TGA/DTA analysis. Then, adsorption experiments were carried out in a batch system and DWTS's Co(II) removal potential was modelled via ABC and GA methods considering the effects of certain experimental parameters (initial pH, contact time, initial Co(II) concentration, DWTS dosage) called as the input parameters. The accuracy of ABC and GA method was determined and these methods were applied to four different functions: quadratic, exponential, linear and power. Some statistical indices (sum square error, root mean square error, mean absolute error, average relative error, and determination coefficient) were used to evaluate the performance of these models. The ABC and GA method with quadratic forms obtained better prediction. As a result, it was shown ABC and GA can be used optimization of the regression function coefficients in modeling adsorption experiments.