TY  - JOUR
AU  - Vasiljevic, T
AU  - Spasojević, J.
AU  - Bacic, M
AU  - Onjia, Antonije E.
AU  - Laušević, Mila D.
PY  - 2006
UR  - https://vinar.vin.bg.ac.rs/handle/123456789/3016
AB  - In this work the effect of the activated carbon cloth surface acidity and pH of the solution on phenols adsorption has been studied. Two phenols, widely different in the terms of their pKa values (phenol and 2,4-dinitrophenol), have been chosen as the model compounds. It has been shown that phenol adsorption was favored by low pH values of solution and high point of zero charge values of activated carbon cloths. The adsorption of 2,4-dinitrophenol was promoted at very low pH values of solution and it was less influenced by activated carbon cloth surface acidity.
T2  - Separation Science and Technology
T1  - Adsorption of phenol and 2,4-dinitrophenol on activated carbon cloth: The influence of sorbent surface acidity and pH
VL  - 41
IS  - 6
SP  - 1061
EP  - 1075
DO  - 10.1080/01496390600588853
ER  - 

@article{
author = "Vasiljevic, T and Spasojević, J. and Bacic, M and Onjia, Antonije E. and Laušević, Mila D.",
year = "2006",
abstract = "In this work the effect of the activated carbon cloth surface acidity and pH of the solution on phenols adsorption has been studied. Two phenols, widely different in the terms of their pKa values (phenol and 2,4-dinitrophenol), have been chosen as the model compounds. It has been shown that phenol adsorption was favored by low pH values of solution and high point of zero charge values of activated carbon cloths. The adsorption of 2,4-dinitrophenol was promoted at very low pH values of solution and it was less influenced by activated carbon cloth surface acidity.",
journal = "Separation Science and Technology",
title = "Adsorption of phenol and 2,4-dinitrophenol on activated carbon cloth: The influence of sorbent surface acidity and pH",
volume = "41",
number = "6",
pages = "1061-1075",
doi = "10.1080/01496390600588853"
}

Vasiljevic, T., Spasojević, J., Bacic, M., Onjia, A. E.,& Laušević, M. D.. (2006). Adsorption of phenol and 2,4-dinitrophenol on activated carbon cloth: The influence of sorbent surface acidity and pH. in Separation Science and Technology, 41(6), 1061-1075.
https://doi.org/10.1080/01496390600588853

Vasiljevic T, Spasojević J, Bacic M, Onjia AE, Laušević MD. Adsorption of phenol and 2,4-dinitrophenol on activated carbon cloth: The influence of sorbent surface acidity and pH. in Separation Science and Technology. 2006;41(6):1061-1075.
doi:10.1080/01496390600588853 .

Vasiljevic, T, Spasojević, J., Bacic, M, Onjia, Antonije E., Laušević, Mila D., "Adsorption of phenol and 2,4-dinitrophenol on activated carbon cloth: The influence of sorbent surface acidity and pH" in Separation Science and Technology, 41, no. 6 (2006):1061-1075,
https://doi.org/10.1080/01496390600588853 . .

TY  - JOUR
AU  - Vasiljevic, T
AU  - Bacic, M
AU  - Laušević, Mila D.
AU  - Onjia, Antonije E.
PY  - 2004
UR  - https://vinar.vin.bg.ac.rs/handle/123456789/6423
AB  - The aim of this work is to gain a better fundamental understanding of the nature Of Surface oxide sites present on activated carbon cloth (ACC) surface, and their role in the adsorption process. BET surface area of ACC was measured by means of benzene adsorption isotherms. The amount and the type of surface oxygen groups were determined by thermogravimetric analysis and titration following Boehms method. Batch adsorption tests were conducted to evaluate equilibrium adsorption isotherms of phenol on ACC. It was shown that both surface area and surface groups composition had quite an impact on adsorption properties of ACC against phenol.
T2  - Materials Science Forum
T1  - Surface composition and adsorption properties of activated carbon cloth
VL  - 453-454
SP  - 163
EP  - 168
DO  - 10.4028/www.scientific.net/MSF.453-454.163
ER  - 

@article{
author = "Vasiljevic, T and Bacic, M and Laušević, Mila D. and Onjia, Antonije E.",
year = "2004",
abstract = "The aim of this work is to gain a better fundamental understanding of the nature Of Surface oxide sites present on activated carbon cloth (ACC) surface, and their role in the adsorption process. BET surface area of ACC was measured by means of benzene adsorption isotherms. The amount and the type of surface oxygen groups were determined by thermogravimetric analysis and titration following Boehms method. Batch adsorption tests were conducted to evaluate equilibrium adsorption isotherms of phenol on ACC. It was shown that both surface area and surface groups composition had quite an impact on adsorption properties of ACC against phenol.",
journal = "Materials Science Forum",
title = "Surface composition and adsorption properties of activated carbon cloth",
volume = "453-454",
pages = "163-168",
doi = "10.4028/www.scientific.net/MSF.453-454.163"
}

Vasiljevic, T., Bacic, M., Laušević, M. D.,& Onjia, A. E.. (2004). Surface composition and adsorption properties of activated carbon cloth. in Materials Science Forum, 453-454, 163-168.
https://doi.org/10.4028/www.scientific.net/MSF.453-454.163

Vasiljevic T, Bacic M, Laušević MD, Onjia AE. Surface composition and adsorption properties of activated carbon cloth. in Materials Science Forum. 2004;453-454:163-168.
doi:10.4028/www.scientific.net/MSF.453-454.163 .

Vasiljevic, T, Bacic, M, Laušević, Mila D., Onjia, Antonije E., "Surface composition and adsorption properties of activated carbon cloth" in Materials Science Forum, 453-454 (2004):163-168,
https://doi.org/10.4028/www.scientific.net/MSF.453-454.163 . .

TY  - JOUR
AU  - Vasiljevic, T
AU  - Onjia, Antonije E.
AU  - Čokeša, Đuro
AU  - Laušević, Mila D.
PY  - 2004
UR  - https://vinar.vin.bg.ac.rs/handle/123456789/2812
AB  - An artificial neural network (ANN) model for the prediction of retention times in high-performance liquid chromatography (HPLC) was developed and optimized. A three-layer feed-forward ANN has been used to model retention behavior of nine phenols as a function of mobile phase composition (methanol-acetic acid mobile phase). The number of hidden layer nodes, number of iteration steps and the number of experimental data points used for training set were optimized. By using a relatively small amount of experimental data (25 experimental data points in the training set), a very accurate prediction of the retention (percentage normalized differences between the predicted and the experimental data less than 0.6%) was obtained. It was shown that the prediction ability of ANN model linearly decreased with the reduction of number of experiments for the training data set. The results obtained demonstrate that ANN offers a straightforward way for retention modeling in isocratic HPLC separation of a complex mixture of compounds widely different in pK(a) and log K-ow values. (C) 2004 Elsevier B.V. All rights reserved.
T2  - Talanta
T1  - Optimization of artificial neural network for retention modeling in high-performance liquid chromatography
VL  - 64
IS  - 3
SP  - 785
EP  - 790
DO  - 10.1016/j.talanta.2004.03.032
ER  - 

@article{
author = "Vasiljevic, T and Onjia, Antonije E. and Čokeša, Đuro and Laušević, Mila D.",
year = "2004",
abstract = "An artificial neural network (ANN) model for the prediction of retention times in high-performance liquid chromatography (HPLC) was developed and optimized. A three-layer feed-forward ANN has been used to model retention behavior of nine phenols as a function of mobile phase composition (methanol-acetic acid mobile phase). The number of hidden layer nodes, number of iteration steps and the number of experimental data points used for training set were optimized. By using a relatively small amount of experimental data (25 experimental data points in the training set), a very accurate prediction of the retention (percentage normalized differences between the predicted and the experimental data less than 0.6%) was obtained. It was shown that the prediction ability of ANN model linearly decreased with the reduction of number of experiments for the training data set. The results obtained demonstrate that ANN offers a straightforward way for retention modeling in isocratic HPLC separation of a complex mixture of compounds widely different in pK(a) and log K-ow values. (C) 2004 Elsevier B.V. All rights reserved.",
journal = "Talanta",
title = "Optimization of artificial neural network for retention modeling in high-performance liquid chromatography",
volume = "64",
number = "3",
pages = "785-790",
doi = "10.1016/j.talanta.2004.03.032"
}

Vasiljevic, T., Onjia, A. E., Čokeša, Đ.,& Laušević, M. D.. (2004). Optimization of artificial neural network for retention modeling in high-performance liquid chromatography. in Talanta, 64(3), 785-790.
https://doi.org/10.1016/j.talanta.2004.03.032

Vasiljevic T, Onjia AE, Čokeša Đ, Laušević MD. Optimization of artificial neural network for retention modeling in high-performance liquid chromatography. in Talanta. 2004;64(3):785-790.
doi:10.1016/j.talanta.2004.03.032 .

Vasiljevic, T, Onjia, Antonije E., Čokeša, Đuro, Laušević, Mila D., "Optimization of artificial neural network for retention modeling in high-performance liquid chromatography" in Talanta, 64, no. 3 (2004):785-790,
https://doi.org/10.1016/j.talanta.2004.03.032 . .

TY  - JOUR
AU  - Onjia, Antonije E.
AU  - Vasiljevic, T
AU  - Čokeša, Đuro
AU  - Laušević, Mila D.
PY  - 2002
UR  - https://vinar.vin.bg.ac.rs/handle/123456789/2593
AB  - A multifactor optimization strategy was utilized to predict the isocratic HPLC separation of nine phenols. The retention behavior was studied as a function of changing eluent (methanol - acetic acid) composition. The predicted and measured retentions; are in rather good agreement. To locate the optimum in the factor space, the normalized resolution product criterion was applied. In virtually every case, the resolution is limited by the separation of the 2-chlorophenol and 2,4-dinitrophenol pair.
T2  - Journal of the Serbian Chemical Society
T1  - Factorial design in isocratic high-performance liquid chromatography of phenolic compounds
VL  - 67
IS  - 11
SP  - 745
EP  - 751
DO  - 10.2298/JSC0211745O
ER  - 

@article{
author = "Onjia, Antonije E. and Vasiljevic, T and Čokeša, Đuro and Laušević, Mila D.",
year = "2002",
abstract = "A multifactor optimization strategy was utilized to predict the isocratic HPLC separation of nine phenols. The retention behavior was studied as a function of changing eluent (methanol - acetic acid) composition. The predicted and measured retentions; are in rather good agreement. To locate the optimum in the factor space, the normalized resolution product criterion was applied. In virtually every case, the resolution is limited by the separation of the 2-chlorophenol and 2,4-dinitrophenol pair.",
journal = "Journal of the Serbian Chemical Society",
title = "Factorial design in isocratic high-performance liquid chromatography of phenolic compounds",
volume = "67",
number = "11",
pages = "745-751",
doi = "10.2298/JSC0211745O"
}

Onjia, A. E., Vasiljevic, T., Čokeša, Đ.,& Laušević, M. D.. (2002). Factorial design in isocratic high-performance liquid chromatography of phenolic compounds. in Journal of the Serbian Chemical Society, 67(11), 745-751.
https://doi.org/10.2298/JSC0211745O

Onjia AE, Vasiljevic T, Čokeša Đ, Laušević MD. Factorial design in isocratic high-performance liquid chromatography of phenolic compounds. in Journal of the Serbian Chemical Society. 2002;67(11):745-751.
doi:10.2298/JSC0211745O .

Onjia, Antonije E., Vasiljevic, T, Čokeša, Đuro, Laušević, Mila D., "Factorial design in isocratic high-performance liquid chromatography of phenolic compounds" in Journal of the Serbian Chemical Society, 67, no. 11 (2002):745-751,
https://doi.org/10.2298/JSC0211745O . .