Alternative Composite Nanosorbents Based on Turkish Perlite for the Removal of Cr(VI) from Aqueous Solution

New nanocomposite sorbents were synthesized and used for Cr(VI) removal from aqueous solution by modifying Turkish perlite with α-MnO2 (PAM) and γ-Fe2O3 (PGI) nanoparticles. Nanocomposite sorbents were characterized using scanning electron microscopy (SEM) and FTIR. The effects of several parameters such as contact time, amount of sorbent, pH, and concentration were investigated and it was found that the sorption capacity for Cr(VI) was found to be highly pH dependent. Also the experimental data were evaluated in terms of different isotherm models. The data of PGI were well fit to DR isotherm model whereas PAM data were well described with Temkin isotherm model. The sorption capacities were found to be 8.64 and 7.6 mg g−1 for PGI and PAM, respectively. This confirms that these nanocomposites retain the constituent nanoparticle properties while being macroscopic particles suitable for chromium removal in water treatment

‟YEŞİL SENTEZ” YÖNTEMİYLE ÜRETİLMİŞ GÜMÜŞ NANOTANECİK YÜKLÜ AKTİF KARBONUN KROM(VI) GİDERİMİNDEKİ PERFORMANSININ DEĞERLENDİRİLMESİ

ÖZET: Bu çalışma, sulu çözeltilerden krom(VI) iyonunun uzaklaştırılmasında gümüş (Ag) nanotanecik yüklü aktif karbonun (AgNP-AK) adsorban olarak kullanımının değerlendirilmesini amaçlamaktadır. pH etkisi, adsorban miktarı, temas süresi ve başlangıç metal konsatrasyonu gibi parametrelerin incelenmesi ile gerekli optimizasyon şartları belirlendikten sonra farklı izoterm modelleri üzerinde çalışılmıştır. Adsorpsiyon öncesi ve sonrası çözeltideki metal iyon değişimleri UV–vis spektrofotometresi ile tayin edilmiştir. Elde edilen denge eğrisi, Langmuir izoterm modeline daha çok uygunluk göstermiş ve maksimum adsorplama kapasitesi 71,4 mg olarak hesaplanmıştır. Bu çalışma ile elde edilen veriler ışığında çevreci bir yöntemle elde edilen AgNP-AK adsorbanının krom(VI) iyonunun uzaklaştırılmasında umut vaadeden yeni bir alternatif olabileceği sonucuna varılmıştır

Advanced Sorption Process Applications

At the beginning of the twenty-firstst century, separation processes presented a comprehensive application of the major operations performed by various industries, such as chemical, food, environmental, and biotechnology. Sorption, one of the preferred separation processes because of its effectiveness at different interfaces, has caught the attention of many scientists. This book is aimed at gaining a general knowledge of sorption and a number of extremely important applications, as well as recognizing its functions and paramount importance in chemical and biochemical plants, including environmental treatment. Moreover, progress in the phenomenon is highlighted in this book. To help provide instruction in the important sorption processes, we have chosen authors who have extensive industrial and academic experience in closing the gap between theory and practice. Crucial progress in the theoretical information section of sorption has been achieved, mainly through the development of new techniques that examine the usage of various sorbents, including nanomaterials for the removal of various pollutants. We have subdivided the book into several sections, one of which is focused on applications of the sorption process, which presents real results of the recent studies and gives a source of up-to-date literature. The relationship between the sorption process and isotherm and kinetics modeling is analyzed in another chapter. This book will be a reference book for those who are interested in sorption techniques from various industries

Modeling of Trivalent Chromium Sorption onto Commercial Resins by Artificial Neural Network

In this research, artificial neural network (ANN) model having three layers was developed for precise estimation of Cr(III) sorption rate varying from 17% to 99% by commercial resins as a result of obtaining 38 experimental data. ANN was trained by using the data of sorption process obtained at different pH (2–7) values with Amberjet 1200H and Diaion CR11 amount (0.01–0.1 g) dosage, initial metal concentration (4.6–31.7 ppm), contact time (5–240 min), and a temperature of 25°C. A feed-forward back propagation network type with one hidden layer, different algorithm (transcg, trainlm, traingdm, traincgp, and trainrp), different transfer function (logsig, tansig, and purelin) for hidden layer and purelin transfer function for output layer were used, respectively. Each model trained for cross-validation was compared with the data that were not used. The trainlm algorithm and purelin transfer functions with five neurons were well fitted to training data and cross-validation. After the best suitable coefficient of determination and mean squared error values were found in the current network, optimal result was searched by changing the number of neurons range from 1 to 20 in the current network hidden layer

An Artificial Neural Network Model for Wastewater Treatment Plant of Konya

In this study, modelling of Konya wastewater treatment plant was studied by using artificial neural network with different architectures in Matlab software. All data were obtained from wastewater treatment plant of Konya during daily records over four month. Treatment efficiency of the plant was determined by taking into account of input values of pH, temperature, COD, TSS and BOD with output values TSS. Performance of the model was compared via the parameters of Mean Squared Error (MSE), and correlation coefficient (R). The suitable architecture of the neural network model is determined after several trial and error steps. According to the modelling study, the ANN can predict the plant performance with correlation coefficient (R) between the observed and predicted output variable reached up to 0.96

Safety assessment of the innovative functional food ingredient from Cannabis sativa L. wastes

Xylooligosaccharides (XOS) are the oligomers of β-1,4 linked xylose monomers and they have health promoting effect by modulating the beneficial microorganisms in intestine. In this study, hydrolysate obtained from hemp (Cannabis sativa) shives was investigated in terms of its in vitro toxicological impacts at cellular and genetic levels and antioxidant activity. The hydrolysate was found to contain 0.264 mg mL-1 of xylose, 0.789 mg mL-1 of xylobiose and 0.171 mg mL-1 of xylotriose in addition to hydroxymethlyfurfural (HMF) and furfural (F) at concentrations of 0.545 mg mL-1 and 0.107 mg mL-1, respectively. The cells, colon epithelial cells (CoN) and colon cancer cells (Caco-2), exposed to 5.00 mg mL-1 or lower XOS hydrolysate showed very similar growth profiles to the untreated control cells. At the genetic level, the oxidative responses of the cell types to XOS hydrolysate were different as measured by NFE2L2 (Nuclear factor, erythroid-derived 2-like 2) gene expression. Regarding antioxidant activity, the amount of XOS hydrolysate (IC50) that cleared 50 % of the 2,2-diphenyl-l-picrylhydrazyl (DPPH) in the medium was calculated as 0.12 mg mL-1. To conclude, based on in vitro studies, XOS hydrolysate obtained from lignocellulosic hemp shives emerges as an innovative, alternative and safe functional food candidate