| Literature DB >> 35558585 |
Zhihua Xu1, Tianqi Zhang1, Zhihang Yuan1, Daofang Zhang1, Zhenhua Sun1, YuanXing Huang1, Weifang Chen1, Danqi Tian1, Haixuan Deng1, Yuwei Zhou1.
Abstract
Cotton textile waste-based magnetic activated carbon was prepared via simultaneous activation-pyrolysis using FeCl3 as a novel activating agent. The response surface methodology based on the Box-Behnken design method was applied to optimize the preparation parameters and predict the specific surface area of the samples. The optimal activated carbon was obtained at a mass ratio of FeCl3/CTW, activation time and activation temperature of 1.62 : 1, 1 h and 700 °C, respectively. The experimental maximum yield and iodine adsorptive value (32.66% and 714.55 mg g-1) of the resultant carbon were close to that of the predicated response values (34.85% and 783.75 mg g-1), respectively. SEM, N2 adsorption-desorption isotherms, XRD, PPMS, FTIR and pHpzc measurements were conducted to analyze the physicochemical characteristics of the optimal sample. The results showed that the carbon matrix had a high specific surface area of 837.39 m2 g-1 with abundant micropores and acidic surface functional groups, and the saturation magnetization (Ms) was 5.2 emu g-1 due to the formation of Fe3O4. The maximum adsorption of Cr(vi) by the carbon reached 212.77 mg g-1. Furthermore, the addition of FeCl3 lowered the pyrolytic carbonization temperature and inhibited the generation of volatiles in the activation-pyrolysis process. Meanwhile, the formation of Fe2O3 and Fe3O4 derived from FeCl3 was beneficial for the development of vast micropores. This journal is © The Royal Society of Chemistry.Entities:
Year: 2018 PMID: 35558585 PMCID: PMC9089844 DOI: 10.1039/c8ra06253f
Source DB: PubMed Journal: RSC Adv ISSN: 2046-2069 Impact factor: 4.036
Levels and code schedule of the experiments
| Parameters | Factors | Levels | ||
|---|---|---|---|---|
| −1 | 0 | 1 | ||
| Mass ratio |
| 1 : 1 | 2 : 1 | 3 : 1 |
| Activation time (h) |
| 1 | 2 | 3 |
| Activation temperature (°C) |
| 400 | 550 | 700 |
Design matrix and responses
| Numbers | Variable | Response | |||||
|---|---|---|---|---|---|---|---|
|
|
|
|
|
| |||
| Actual | Predicted | Actual | Predicted | ||||
| 1 | 1 | 0 | −1 | 38.15 | 38.55 | 339.74 | 311.96 |
| 2 | 0 | 1 | −1 | 35.98 | 35.44 | 304.34 | 344.4 |
| 3 | −1 | −1 | 0 | 38.76 | 39.3 | 329.72 | 289.67 |
| 4 | −1 | 1 | 0 | 35.28 | 34.88 | 339.09 | 366.87 |
| 5 | 0 | −1 | 1 | 39.76 | 38.47 | 432.36 | 470.32 |
| 6 | 0 | 0 | 0 | 37.34 | 36.98 | 306.52 | 276.65 |
| 7 | 0 | −1 | −1 | 34.58 | 34.94 | 594.46 | 624.33 |
| 8 | 1 | −1 | 0 | 27.60 | 28.89 | 965.6 | 927.64 |
| 9 | −1 | 0 | 1 | 38.80 | 39.7 | 311.66 | 301.48 |
| 10 | 0 | 1 | 1 | 39.40 | 40.15 | 421.39 | 423.48 |
| 11 | 1 | 0 | 1 | 35.00 | 34.25 | 827.99 | 825.9 |
| 12 | 0 | 0 | 0 | 34.88 | 33.98 | 693.88 | 704.06 |
| 13 | 0 | 0 | 0 | 36.00 | 35.57 | 357.38 | 401.1 |
| 14 | 0 | 0 | 0 | 34.90 | 35.57 | 439.67 | 401.1 |
| 15 | −1 | 0 | −1 | 35.90 | 35.57 | 399.4 | 401.1 |
| 16 | 1 | 1 | 0 | 35.72 | 35.57 | 402.28 | 401.1 |
| 17 | 0 | 0 | 0 | 35.34 | 35.57 | 406.76 | 401.1 |
Analysis of variance table
| Source |
|
| ||
|---|---|---|---|---|
|
|
|
|
| |
| Model | 11.24 | 0.0021 | 35.08 | <0.0001 |
|
| 24.58 | 0.0016 | 3.22 | 0.1159 |
|
| 0.017 | 0.9014 | 8.20 × 10−6 | 0.9978 |
|
| 58.62 | 0.0001 | 173.53 | <0.0001 |
|
| 0.37 | 0.5609 | 0.27 | 0.6204 |
|
| 4.51 | 0.0712 | 33.07 | 0.0007 |
|
| 0.11 | 0.7471 | 7.96 | 0.0257 |
|
| 0.49 | 0.508 | 2.16 | 0.1853 |
|
| 12.31 | 0.0099 | 3.97 | 0.0867 |
|
| 0.55 | 0.4831 | 94.37 | <0.0001 |
|
| 0.9504 | 0.8520 | ||
|
| 0.7352 | 0.0592 | ||
Analysis of variance table after simplification
| Source |
|
| ||
|---|---|---|---|---|
|
|
|
|
| |
| Model | 31.42 | <0.0001 | 54.16 | <0.0001 |
|
| 24.38 | 0.0003 | — | — |
|
| 58.14 | <0.0001 | 122.94 | <0.0001 |
|
| — | — | 23.43 | 0.0004 |
|
| — | — | 5.64 | 0.0351 |
|
| 11.73 | 0.0045 | — | — |
|
| — | — | 64.62 | <0.0001 |
|
| 0.8508 | 0.9300 | ||
|
| 0.7389 | 0.8629 | ||
Fig. 13D surface response (a) and the contour (b) for the desirability function for the simultaneous optimization of the yield and iodine adsorption value.
Fig. 2SEM images of CTW (a) and OAC (b).
Fig. 3N2 adsorption/desorption isotherm (a) and pore size distributions (b) of OAC.
Specific surface area and pore volume parameters of OAC
| Sample |
|
|
|
|
|
|---|---|---|---|---|---|
| OAC | 837.39 | 423.55 | 50.58 | 0.69 | 2.89 |
Specific surface area of activated carbons prepared from various precursors by different activating agents
| Precursor | Activating agent | Mass ratio | Activation time (h) | Activation temperature (°C) | Surface area (m2 g−1) | Reference |
|---|---|---|---|---|---|---|
| Cotton textile waste | FeCl3 | 1.62 : 1 | 1 | 700 | 837.39 | This study |
| Carbonized coconut shells | FeCl3 | 2 : 1 | 1.5 | 700 | 337 |
|
| Date pits | FeCl3 | 1.5 : 1 | 1 | 700 | 780.06 |
|
| Textile cotton waste | ZnCl2 | — | 1 | 700 | 292 |
|
| Cotton woven waste | H3PO4 | — | 0.5 | 800 | 789 |
|
Fig. 4XRD pattern of OAC.
Fig. 5Magnetization loop of OAC.
Magnetic properties of OAC
|
|
|
|
|
|---|---|---|---|
| 5.20 | 0.30 | 63.84 | 0.06 |
Fig. 6FTIR spectrum of OAC.
Fig. 7Linear fitting plots of Cr(vi) adsorption by OAC, WAC and CAC for the Langmuir isotherms (a) and Freundlich isotherms (b).
Isotherm model parameters of Cr(vi) adsorption
| Adsorbent |
| Langmuir model | Freundlich model | ||||
|---|---|---|---|---|---|---|---|
|
|
|
|
|
|
| ||
| OAC | 298 | 212.77 | 0.0118 | 0.96 | 40.6069 | 4.2265 | 0.95 |
| WAC | 298 | 104.17 | 0.0025 | 0.97 | 1.7061 | 1.7973 | 0.97 |
| CAC | 298 | 232.56 | 0.0196 | 0.98 | 47.2825 | 4.2230 | 0.98 |
Fig. 8TG-DTG-DSC image of CTW, FeCl3 and CTW–FeCl3.