Bio-Based Composites for Light Automotive Parts: Statistical Analysis of Mechanical Properties; Effect of Matrix and Alkali Treatment in Sisal Fibers
Abstract
:1. Introduction
2. Materials and Methods
2.1. Materials
2.2. Alkali Treatment of Sisal and Bio-Based Composites Processing
2.3. Characterization
2.3.1. Fourier Transform Infrared Spectroscopy (FTIR)
2.3.2. X-ray Diffraction (XRD)
2.3.3. Water Absorption
2.3.4. Density Measurements
2.3.5. Shore-D Hardness
2.3.6. Izod Impact Test
2.3.7. Statistical Analysis
3. Results and Discussion
3.1. Fourier Transform Infrared Spectroscopy (FTIR)
3.2. X-ray Diffraction (XRD)
3.3. Water Absorption
3.4. Density, Hardness and Impact Strenght
3.5. Statistical Analysis
4. Summary and Conclusions
- The FTIR analysis indicated that the alkali treatment removed most of the amorphous materials, such as hemicellulose, and lignin from the surface of the sisal fibers.
- X-ray diffraction analysis of the sisal showed that the alkali treatment promoted a significant increase in its crystallinity, in which the crystallinity index increased from 44.76% to 73.18%, corroborating the FTIR analyses.
- The density of the materials ranged from 0.89 to 0.95 g·cm−3, showing the possibility of using these bio-based composites in light automotive parts.
- The rPP and rPP composites had lower hardness than those of virgin PP.
- Water absorption tests revealed that the composites with the rPP matrix showed higher liquid absorption, due to the lack of sisal–matrix interaction and the hydrophilic character of the fiber, besides the presence of the fibers that had hydrophilic behavior. All groups except PP presented the highest liquid absorption in the 168 h test.
- The composites with the PP matrix displayed higher-impact strength values than the composites with the rPP matrix, corroborating the results of water absorption and hardness.
- Statistical analysis revealed that the type of bio-based composite matrix was the most significant variable. The regression model and the Pareto diagrams showed that the alkali treatment was a significant factor for the hardness of rPP and PP composites, and that the addition of a sisal layer was relevant to improve the impact resistance of the composites. For the fabrication of internal components of automobiles, the matrix of virgin PP and the alkali treatment of the fiber are indicated.
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Absorption Band (cm−1) | Functional Group | Fiber Component |
---|---|---|
3296 | O - H stretching | Cellulose |
2914 | C - H stretching | Cellulose |
2796 | C - H stretching | Hemicellulose and Lignin |
2357 | C = C stretching | Wax |
1737 | C = O stretching | Hemicellulose and Lignin |
1642 | OH bending | Lignin |
1346 | C = O stretching | Hemicellulose |
1028 | C - OH stretching | Lignin and Cellulose |
Increase in wt. (%) | ||||
---|---|---|---|---|
Sample | Immersion Time | |||
2 h | 24 h | 168 h | 336 h | |
PP | 0.531 ± 0.008 | 0.227 ± 0.008 | 0.152 ± 0.009 | 0.152 ± 0.008 |
rPP | 0.592 ± 0.017 | 0.723 ± 0.017 | 1.183 ± 0.018 | 1.249 ± 0.018 |
PP/Sisal | 2.297 ± 0.031 | 2.935 ± 0.028 | 4.339 ± 0.025 | 4.914 ± 0.028 |
rPP/Sisal | 1.958 ± 0.031 | 4.214 ± 0.031 | 7.477 ± 0.032 | 7.914 ± 0.031 |
PP/Sisal NaOH | 0.847 ± 0.017 | 1.885 ± 0.019 | 3.966 ± 0.017 | 4.156 ± 0.019 |
rPP/Sisal NaOH | 1.329 ± 0.050 | 3.797 ± 0.057 | 8.101 ± 0.060 | 9.051 ± 0.057 |
Sample | Density (g·cm−3) | Shore D Hardness | Izod Impact Strength (MPa) |
---|---|---|---|
PP | 0.89 ± 0.02 | 63.00 ± 0.00 | 21.49 ± 0.25 |
rPP | 0.92 ± 0.01 | 58.00 ± 0.58 | 8.48 ± 0.08 |
PP/Sisal | 0.93 ± 0.02 | 63.33 ± 1.00 | 9.22 ± 0.02 |
rPP/Sisal | 0.95 ± 0.01 | 59.33 ± 1.00 | 6.82 ± 0.06 |
PP/Sisal NaOH | 0.90 ± 0.02 | 63.33 ± 1.00 | 9.14 ± 0.07 |
rPP/Sisal NaOH | 0.93 ± 0.01 | 57.00 ± 1.00 | 5.63 ± 0.05 |
Experiment | M | AT | SS | H | I | D |
---|---|---|---|---|---|---|
1 | 1 | 0 | 0 | 63 | 0.893 | 18.614 |
2 | 1 | 0 | 0 | 63 | 0.875 | 17.853 |
3 | 1 | 0 | 0 | 63 | 0.907 | 28.025 |
4 | 1 | 0 | 1 | 63 | 0.955 | 9.641 |
5 | 1 | 0 | 1 | 64 | 0.911 | 8.788 |
6 | 1 | 0 | 1 | 63 | 0.934 | 9.226 |
7 | 1 | 15 | 1 | 63 | 0.891 | 7.911 |
8 | 1 | 15 | 1 | 63 | 0.921 | 8.557 |
9 | 1 | 15 | 1 | 64 | 0.891 | 10.956 |
10 | 2 | 0 | 0 | 58 | 0.932 | 10.426 |
11 | 2 | 0 | 0 | 58 | 0.921 | 6.620 |
12 | 2 | 0 | 0 | 58 | 0.923 | 8.396 |
13 | 2 | 0 | 1 | 60 | 0.956 | 8.004 |
14 | 2 | 0 | 1 | 59 | 0.957 | 5.305 |
15 | 2 | 0 | 1 | 59 | 0.950 | 7.150 |
16 | 2 | 15 | 1 | 58 | 0.931 | 6.389 |
17 | 2 | 15 | 1 | 57 | 0.918 | 6.228 |
18 | 2 | 15 | 1 | 56 | 0.932 | 4.267 |
Source of Variation | Degree of Freedom (D.F) | Sum of Squares (SQ) | Means Squares (MQ) | F | Significance of F |
---|---|---|---|---|---|
Regression | 3 | 0.0076 | 0.0025 | 14.6094 | |
Residue | 14 | 0.0024 | 0.0002 | ||
Total | 17 | 0.0100 | |||
Term | Coefficients | Stand. Error | Stat t | Value-p | |
intercept | 0.8682 | 0.0107 | 80.7936 | ||
M | 0.0269 | 0.0062 | 4.3342 | ||
AT | −0.0020 | 0.0005 | −3.9264 | ||
SS | 0.0353 | 0.0076 | 4.6502 | ||
S = 0.0132 | |||||
R-sq = 75.79% | |||||
R-sq (adj) = 70.60% |
Source of Variation | Degree of Freedom (D.F) | Sum of Squares (SQ) | Means Squares (MQ) | F | Significance of F |
---|---|---|---|---|---|
Regression | 6 | 126 | 21 | 75.6 | |
Residue | 12 | 4 | 0.3333 | ||
Total | 18 | 130 | |||
Term | Coefficients | Stand. Error | Stat t | Value-p | |
Intercept | 68 | 0.7454 | 91.2316 | ||
M | −5 | 0.4714 | −10.6066 | ||
AT | 0.1556 | 0.0703 | 2.2136 | 0.0469 | |
SS | −0.6667 | 1.0541 | −0.6325 | 0.5389 | |
M-AT | −0.1556 | 0.0444 | −3.5 | 0.0044 | |
M-SS | 1 | 0.6667 | 1.5 | 0.1595 | |
S = 0.5775 | |||||
R-sq = 96.92% | |||||
R-sq (adj) = 87.31% |
Source of Variation | Degree of Freedom (D.F) | Sum of Squares (SQ) | Means Squares (MQ) | F | Significance of F |
---|---|---|---|---|---|
Regression | 6 | 494.8954 | 82.4826 | 14.2137 | 0.00013 |
Residue | 12 | 83.5634 | 6,9636 | ||
Total | 18 | 578,4588 | |||
Term | Coefficients | Stand. Error | Stat t | Value-p | |
intercept | 34.5137 | 3.4068 | 10.1309 | ||
M | −13.0166 | 2.1546 | −6.0413 | ||
AT | 0.0692 | 0.3212 | 0.2154 | 0.8330 | |
SS | −22.8964 | 4.8179 | −4.7524 | 0.0005 | |
M-AT | −0.0743 | 0.2031 | −0.3659 | 0.7208 | |
M-SS | 10.6178 | 3.0471 | 3.4846 | 0.0045 | |
S = 2.6388 | |||||
R-sq = 85.55% | |||||
R-sq (adj) = 71.20% |
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Fernandes, R.A.P.; da Silveira, P.H.P.M.; Bastos, B.C.; da Costa Pereira, P.S.; de Melo, V.A.; Monteiro, S.N.; Tapanes, N.d.L.C.O.; Bastos, D.C. Bio-Based Composites for Light Automotive Parts: Statistical Analysis of Mechanical Properties; Effect of Matrix and Alkali Treatment in Sisal Fibers. Polymers 2022, 14, 3566. https://doi.org/10.3390/polym14173566
Fernandes RAP, da Silveira PHPM, Bastos BC, da Costa Pereira PS, de Melo VA, Monteiro SN, Tapanes NdLCO, Bastos DC. Bio-Based Composites for Light Automotive Parts: Statistical Analysis of Mechanical Properties; Effect of Matrix and Alkali Treatment in Sisal Fibers. Polymers. 2022; 14(17):3566. https://doi.org/10.3390/polym14173566
Chicago/Turabian StyleFernandes, Roberta Anastacia Palermo, Pedro Henrique Poubel Mendonça da Silveira, Beatriz Cruz Bastos, Patricia Soares da Costa Pereira, Valdir Agustinho de Melo, Sergio Neves Monteiro, Neyda de La Caridad Om Tapanes, and Daniele Cruz Bastos. 2022. "Bio-Based Composites for Light Automotive Parts: Statistical Analysis of Mechanical Properties; Effect of Matrix and Alkali Treatment in Sisal Fibers" Polymers 14, no. 17: 3566. https://doi.org/10.3390/polym14173566