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Frontiers of Environmental Science & Engineering

ISSN 2095-2201

ISSN 2095-221X(Online)

CN 10-1013/X

Postal Subscription Code 80-973

2018 Impact Factor: 3.883

Front. Environ. Sci. Eng.    2021, Vol. 15 Issue (5) : 109    https://doi.org/10.1007/s11783-021-1397-3
RESEARCH ARTICLE
Experimental and DFT insights into nitrogen and sulfur co-doped carbon nanotubes for effective desulfurization of liquid phases: Equilibrium & kinetic study
Seyyed Salar Meshkat1(), Ebrahim Ghasemy2, Alimorad Rashidi3(), Omid Tavakoli4, Mehdi Esrafili5
1. Faculty of Chemical Engineering, Urmia University of Technology, Urmia 57166-419, Iran
2. Nanotechnology Departments, School of New Technologies, Iran University of Science and Technology, Tehran 16846-13114, Iran
3. Nanotechnology Research Center, Research Institute of Petroleum Industry (RIPI), Tehran 14856-13111, Iran
4. School of Chemical Engineering, College of Engineering, University of Tehran, Tehran 14155-6619, Iran
5. Department of Chemistry, Faculty of Basis Sciences, University of Maragheh, Maragheh 55136-553, Iran
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Abstract

• Synthesis of NS-CNTS is used in a high desulfurization performance.

• Synthesizing NS-CNT is considered as a novel adsorbent from low-cost precursors.

• A high sulfur removal capacity for NS-CNT is attained compared with recent works.

Herein, nitrogen and sulfur co-doped carbon nanotubes (NS-CNT) adsorbents were synthesized via the chemical vapor deposition technique at 1000°C by employing the camphor, urea and sulfur trioxide pyridine. In this study, desulfurization of two types of mercaptans (dibenzothiophene (DBT) and tertiary butyl mercaptan (TBM) as nonlinear and linear forms of mercaptan) was studied. In this regard, a maximum capacity of NS-CNT was obtained as 106.9 and 79.4 mg/g and also the removal efficiencies of 98.6% and 88.3% were achieved after 4 h at 298K and 0.9 g of NS-CNT for DBT and TBM, respectively. Characterization of the NS-CNTs was carried out through exploiting scanning electron microscopy (SEM), X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), and elemental analysis (CHN). The isotherm equilibrium data could be ascribed to the Freundlich nonlinear regression form and the kinetic data was fitted by nonlinear form of the pseudo second order model. The negative values of ΔS0, ΔH0 and ΔG0 specify that the adsorption of both types of mercaptans was a natural exothermic process with a reduced entropy. Maintenance of more than 96% of the adsorption capacity even after nine cycles suggest the NS-CNT as a superior adsorbent for mercaptans removal in the industry. Density functional theory (DFT) calculations were also performed to peruse the effects of S/N co-doping and carbon monovacancy defects in CNTs toward the adsorption of DBT and TBM.

Keywords Dibenzothiophene (DBT)      Tertiary methyl mercaptan      Adsorption      Carbon nano tube (CNT)      Desulfurization      Doping     
Corresponding Author(s): Seyyed Salar Meshkat,Alimorad Rashidi   
Issue Date: 03 February 2021
 Cite this article:   
Seyyed Salar Meshkat,Ebrahim Ghasemy,Alimorad Rashidi, et al. Experimental and DFT insights into nitrogen and sulfur co-doped carbon nanotubes for effective desulfurization of liquid phases: Equilibrium & kinetic study[J]. Front. Environ. Sci. Eng., 2021, 15(5): 109.
 URL:  
https://academic.hep.com.cn/fese/EN/10.1007/s11783-021-1397-3
https://academic.hep.com.cn/fese/EN/Y2021/V15/I5/109
Fig.1  The schematic illustration of the experimental setup.
Fig.2  FTIR spectra of the synthesized NS-CNT and CNT.
Fig.3  FE-SEM images of synthesized (a) CNT and (b) NS-CNT.
Fig.4  XRD pattern of synthesized the NS-CNT, N-CNT, and pristine CNT.
Sample Nitrogen loading (wt.%) Sulfur loading (wt.%)
CNT 0 0
N-CNT 0.91 0
NS-CNT1 1.02 0.91
NS-CNT2 1.03 0.62
NS-CNT3 1.44 1.06
Tab.1  Elemental analysis of the synthesized adsorbent
Fig.5  TGA weight loss curve of the synthesized NS-CNT.
Fig.6  The FE-SEM image of the adsorbent after adsorption process.
Fig.7  TGA curve of the adsorbent before and after adsorption process.
Fig.8  Removal efficiency of TBM & DBT vs. mass loaded.
Fig.9  Removal efficiency of DBT adsorption on the different synthesized adsorbents.
Models Linear/ Nonlinear Parameters Error (R2)
qmax (mg/g) kad (1/min)
Pseudo first order Linear 104.7 0.0024 0.849
Nonlinear 107.9 0.0045 0.886
Pseudo second order Linear 107.1 0.0013 0.971
Nonlinear 106.8 0.0014 0.986
Tab.2  Kinetic model parameters for the adsorption of DBT onto NS-CNT
Fig.10  (a) Linear form of pseudo first order model; (b) Linear pseudo second order model; (c) Experimental and nonlinear forms of kinetic models.
Linear/ Nonlinear Langmuir Freundlich
qmax (mg/g) b(L/mg) R2 kf n R2
Linear 125.15 0.023 0.84 2.57 1.41 0.95
Nonlinear 134.1 0.017 0.87 2.64 1.48 0.99
Tab.3  Results of the DBT adsorption equilibrium analysis
Fig.11  (a) Langmuir linear form; (b) Freundlich linear form; (c) nonlinear fittings of Langmuir and Freundlich model for DBT adsorption
Mercaptan ΔH0 (kJ/mol) ΔS0(J/K/mol) ΔG0 (kJ/mol)
298K 313K 323K
DBT –86.4 –170.4 –36.8 –29.7 –18.6
TBM –59.7 –199.1 –23.6 –17.2 –8.9
Tab.4  Thermodynamic parameters for DBT and TBM adsorption
Fig.12  Regeneration of NS-CNT for DBT and TBM adsorption.
Element Weight (%)
N 1.44
S 1.06
C 92.5
O 4.2
H >0.8
Tab.5  Elemental analysis of the NS-CNT (weight %)
Adsorbent Capacity (mg/g) Reference
MCM-41 0.81 Erses et al., 2005
MSN 4.6 Erses et al., 2005
SBA-16 29.56 Anbia and Karami, 2015
OMC 50.32 Anbia and Karami, 2015
N-CNT4 63.3 Meshkat et al., 2018a
N-G 73.4 Meshkat et al., 2018b
NS-CNT 106.8 This work
Tab.6  The comparison of the DBT removal by different adsorbents
CNT DBT TBM
R Eads qCT R Eads qCT
pristine 4.70 -7.4 0.02 4.32 -5.2 0.01
M1 4.18 -12.8 0.04 3.85 -9.4 0.03
M2 3.51 -18.5 0.07 3.46 -15.7 0.05
M3 3.74 -16.9 0.06 3.71 -13.2 0.04
M4 4.08 -12.3 0.05 3.62 -12.5 0.04
M5 3.97 -22.8 0.09 3.64 -16.4 0.07
M6 3.95 -21.0 0.08 3.52 -15.1 0.06
Tab.7  The optimized binding distances (R, Å), adsorption energies (Eads, kJ/mol) and charge-transferred values due to the adsorption of DBT or TBM molecules over different models of CNTs
Fig.13  Optimized models of NS-CNTs used in the DFT calculations.
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