Pyrolysis of Low Density Polyethylene: Kinetic Study Using TGA Data and ANN Prediction
Abstract
1. Introduction
2. Materials and Methods
2.1. Materials
2.2. Thermal Decomposition of LDPE
2.3. Kinetic Theory
2.4. Topology of ANNs
3. Results and Discussion
3.1. TG-DTG Analysis of LDPE
3.2. Model-Free Kinetics Calculation
3.3. Model-Fitting Kinetics Calculation
3.4. Pyrolysis Prediction by ANN Model
4. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
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Reference | Activation Energy (kJ mol−1) |
---|---|
Diaz Silvarrey and Phan [2] | 267.61 ± 3.23 |
Lyon [8] | 130–200 |
Saha and Ghoshal [9] | 190 |
Aboulkas et al. [10] | 215 |
Aboulkas et al. [11] | 215–221 |
Aguado et al. [12] | 261 ± 21 |
Sorum et al. [13] | 340 |
Wu et al. [14] | 194–206 |
Manufacturer | Ipoh SY Recycle Plastic, Perak, Malaysia |
---|---|
Polymer Type | Recycled LDPE |
Appearance (at 25 °C) | Solid |
Physical State | Pellets |
Colour | Black |
Density (Kg/m3) | 910–940 |
Melting Temperature (°C) | 115 ± 10 |
Method | Equation | Integral (I) or Differential (D) | Plot | |
---|---|---|---|---|
Friedman | (6) | D | ||
Flynn-Wall-Qzawa (FWO) | (7) | I | ||
Kissinger-Akahira-Sunose (KAS) | (8) | I |
Method | Equation | Plot | |
---|---|---|---|
Arrhenius | (9) | ||
Coats-Redfern | n ≠ 1 | (10) | |
n = 1 | (11) |
Heating Rate (K/min) | On-Set (K) | End-Set (K) | Peak (K) |
---|---|---|---|
5 | 665 | 750 | 741 |
10 | 668 | 755 | 744 |
20 | 688 | 782 | 765 |
40 | 700 | 794 | 785 |
Conversion | Friedman | FWO | KAS | ||||||
---|---|---|---|---|---|---|---|---|---|
E (kJ/mol) | A (min−1) | R2 | E (kJ/mol) | A (min−1) | R2 | E (kJ/mol) | A (min−1) | R2 | |
0.1 | 197 | 2.63 × 1013 | 0.9772 | 193 | 8.14 × 1012 | 0.9532 | 191 | 5.51 × 1012 | 0.9474 |
0.2 | 185 | 4.85 × 1012 | 0.9265 | 198 | 2.17 × 1013 | 0.9575 | 196 | 1.49 × 1013 | 0.9523 |
0.3 | 186 | 6.68 × 1012 | 0.9288 | 198 | 2.46 × 1013 | 0.9629 | 196 | 1.65 × 1013 | 0.9582 |
0.4 | 206 | 1.97 × 1014 | 0.9387 | 195 | 1.70 × 1013 | 0.9498 | 193 | 1.09 × 1013 | 0.9435 |
0.5 | 198 | 5.20 × 1013 | 0.9793 | 194 | 1.55 × 1013 | 0.9527 | 191 | 9.74 × 1012 | 0.9467 |
0.6 | 194 | 3.06 × 1013 | 0.9844 | 194 | 1.97 × 1013 | 0.9567 | 192 | 1.23 × 1013 | 0.9511 |
0.7 | 188 | 1.17 × 1013 | 0.9674 | 196 | 3.07 × 1013 | 0.9612 | 194 | 1.94 × 1013 | 0.9562 |
0.8 | 196 | 4.31 × 1013 | 0.9345 | 197 | 4.15 × 1013 | 0.9665 | 195 | 2.62 × 1013 | 0.9621 |
0.9 | 198 | 4.50 × 1013 | 0.9559 | 192 | 2.16 × 1013 | 0.9720 | 190 | 1.28 × 1013 | 0.9681 |
Average | 194 | 4.63 × 1013 | 0.9547 | 195 | 2.23 × 1013 | 0.9592 | 193 | 1.43 × 1013 | 0.9540 |
Heating Rate (K/min) | Arrhenius Method | Coats-Redfern Method | ||||
---|---|---|---|---|---|---|
E (kJ/mol) | A (min−1) | R2 | E (kJ/mol) | A (min−1) | R2 | |
5 | 207 | 1.42 × 1014 | 0.9673 | 193 | 4.22 × 1010 | 0.9295 |
10 | 200 | 2.29 × 1013 | 0.985 | 193 | 6.75 × 1010 | 0.9436 |
20 | 213 | 9.13 × 1013 | 0.9724 | 197 | 8.66 × 1010 | 0.9413 |
40 | 187 | 1.11 × 1012 | 0.9649 | 201 | 1.61 × 1011 | 0.9459 |
Average | 202 | 6.43 × 1013 | 0.9724 | 196 | 8.92 × 1010 | 0.9401 |
Model | Network Topology | 1st Transfer Function | 2nd Transfer Function | R |
---|---|---|---|---|
ANN1 | NN-2-10-1 | TANSIG | - | 0.99943 |
ANN2 | NN-2-15-1 | TANSIG | - | 0.99981 |
ANN3 | NN-2-5-1 | TANSIG | - | 0.99724 |
ANN4 | NN-2-10-1 | LOGSIG | - | 0.99865 |
ANN5 | NN-2-15-1 | LOGSIG | - | 0.98047 |
ANN6 | NN-2-5-1 | LOGSIG | - | 0.99544 |
ANN7 | NN-2-15-15-1 | TANSIG | TANSIG | 0.99978 |
ANN8 | NN-2-15-15-1 | LOGSIG | TANSIG | 0.99961 |
ANN9 | NN-2-15-15-1 | TANSIG | LOGSIG | 0.99989 |
ANN10 | NN-2-10-15-1 | TANSIG | LOGSIG | 0.99990 |
ANN11 | NN-2-10-10-1 | TANSIG | LOGSIG | 0.99993 |
ANN12 | NN-2-10-10-1 | LOGSIG | LOGSIG | 1.00000 |
ANN13 | NN-2-15-15-1 | LOGSIG | LOGSIG | 0.99998 |
ANN14 | NN-2-10-15-1 | LOGSIG | LOGSIG | 0.99997 |
ANN15 | NN-2-15-10-1 | LOGSIG | LOGSIG | 0.99996 |
Set | Statistical Parameters | |||
---|---|---|---|---|
R | RMSE | MAE | MBE | |
Training | 0.99999 | 0.09786 | 0.04177 | 0.00583 |
Validation | 0.99999 | 0.04578 | 0.03291 | −0.01063 |
Test | 0.99999 | 0.05197 | 0.03713 | 0.002655 |
All | 0.99999 | 0.08621 | 0.03975 | 0.002897 |
No. | Input Data | Predicted-Output Data | |
---|---|---|---|
Heating Rate (K min−1) | Temperature (K) | Weight Left (%) | |
1 | 5 | 528.036 | 99.87579 |
2 | 5 | 578.09 | 99.6904 |
3 | 5 | 628.072 | 99.328 |
4 | 5 | 678.062 | 96.50681 |
5 | 5 | 728.025 | 49.30348 |
6 | 5 | 778.043 | 0.048376 |
7 | 5 | 828.05 | −0.01156 |
8 | 10 | 528.014 | 100.0249 |
9 | 10 | 578.026 | 99.66833 |
10 | 10 | 628.017 | 98.99761 |
11 | 10 | 678 | 96.5807 |
12 | 10 | 728.002 | 64.78094 |
13 | 10 | 778 | 0.450783 |
14 | 10 | 828.018 | 0.344112 |
15 | 20 | 528.148 | 99.97255 |
16 | 20 | 578.205 | 99.85724 |
17 | 20 | 628.006 | 99.64173 |
18 | 20 | 678.273 | 98.72066 |
19 | 20 | 728.203 | 88.68082 |
20 | 20 | 778.291 | 0.577601 |
21 | 20 | 828.075 | −0.04285 |
22 | 40 | 528.194 | 99.98355 |
23 | 40 | 578.397 | 99.8972 |
24 | 40 | 628.452 | 99.74232 |
25 | 40 | 678.12 | 99.26672 |
26 | 40 | 728.501 | 94.30099 |
27 | 40 | 778.047 | 30.7278 |
28 | 40 | 828.38 | 0.264529 |
Set | Statistical Parameters | |||
---|---|---|---|---|
R | RMSE | MAE | MBE | |
simulated | 0.99998 | 0.17017 | 0.07941 | 0.04903 |
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Dubdub, I.; Al-Yaari, M. Pyrolysis of Low Density Polyethylene: Kinetic Study Using TGA Data and ANN Prediction. Polymers 2020, 12, 891. https://doi.org/10.3390/polym12040891
Dubdub I, Al-Yaari M. Pyrolysis of Low Density Polyethylene: Kinetic Study Using TGA Data and ANN Prediction. Polymers. 2020; 12(4):891. https://doi.org/10.3390/polym12040891
Chicago/Turabian StyleDubdub, Ibrahim, and Mohammed Al-Yaari. 2020. "Pyrolysis of Low Density Polyethylene: Kinetic Study Using TGA Data and ANN Prediction" Polymers 12, no. 4: 891. https://doi.org/10.3390/polym12040891
APA StyleDubdub, I., & Al-Yaari, M. (2020). Pyrolysis of Low Density Polyethylene: Kinetic Study Using TGA Data and ANN Prediction. Polymers, 12(4), 891. https://doi.org/10.3390/polym12040891