Sustainable Composites from Sugarcane Bagasse Fibers and Bio-Based Epoxy with Insights into Wear Performance, Thermal Stability, and Machine Learning Predictive Modeling
Abstract
:1. Introduction
1.1. Sugarcane Bagasse Fiber
1.2. Bio-Based Epoxy
1.3. Synergistic Potential of Sugarcane Bagasse Fibers and Bio-Based Epoxy
2. Materials and Methods
2.1. Chemical Treatment of Bagasse Fibers
2.1.1. Potassium Permanganate (KMnO4) Treatment
2.1.2. Benzene Sulfonyl Chloride (C6H5SO2Cl) Treatment
2.1.3. Ethylene Dichloride Treatment
2.2. Material Characterization
3. Results and Discussion
3.1. FTIR Analysis
3.2. XRD Analysis
3.3. SEM Analysis
3.4. Thermogravimetric Analysis (TGA)
3.5. Experimental Design and Analysis of Wear Testing Using Taguchi Method
3.6. Machine Learning Insights into Wear Performance and Predictive Modeling
4. Conclusions
4.1. Wear Resistance
- Fiber treatment emerged as the most influential factor in determining wear resistance, contributing 90.86% to the variation, as confirmed by the ANOVA results. Among the treatments, ethylene dichloride-treated fibers exhibited the lowest wear rate (0.245 mg/m), which was attributed to their optimized surface modification that enhanced fiber–matrix bonding.
- The raw fibers demonstrated the highest wear rate (0.382 mg/m), underscoring the impact of poor interfacial adhesion and untreated surfaces.
- Lubrication type is ranked as the second most significant factor, with hybrid and grease lubricants effectively reducing wear through protective barriers.
4.2. Thermal Stability
- TGA analysis revealed improved thermal stability across treated fibers, with ethylene dichloride-treated fibers exhibiting the highest thermal onset temperature (T20% at 260 °C) and moderate char yield (1.3 mg). This balance reflects the removal of amorphous components and enhanced hydrophobicity, which correlates with superior wear performance.
- KMnO4-treated fibers demonstrated moderate stability (T20% at 250 °C, char yield of 1.2 mg), while benzene sulfonyl chloride treatments (10% and 20%) optimized hydrophobicity and matrix compatibility but showed reduced thermal stability at higher concentrations.
4.3. Crystallinity Index
- The XRD results demonstrated that alkali pre-treatment led to the highest crystallinity index (62%), promoting interfacial bonding. However, the reduced crystallinity in the KMnO3 and ethylene dichloride treatments (50.5% and 40.6%, respectively) was counterbalanced by the improved surface reactivity and chemical modifications, resulting in enhanced wear resistance.
4.4. Machine Learning Insights
- The Random Forest model effectively predicted wear rates with high accuracy, confirming that fiber treatment was the dominant variable influencing wear. Minimal deviations at higher wear rates suggest areas for model refinement, such as feature interactions and dataset expansion.
4.5. Practical Implications
- The synergy between sugarcane bagasse fibers and bio-based epoxy produced composites with superior thermal stability, mechanical performance, and wear resistance. The environmental benefits, including reduced CO2 emissions (50%) and weight reduction (35% in automotive applications), further validate their potential for sustainable industrial use.
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Sample | Crystallinity Index |
---|---|
Raw untreated fiber | 59% |
Pre-treated fiber | 62% |
KMnO4-Soaked fiber | 50.5% |
KMnO4-refluxed fiber | 46% |
10% Benzene sulphonyl chloride treated | 48.5% |
20% Benzene sulphonyl chloride treated | 42.5% |
Ethylene dichloride-treated fiber | 40.6% |
Parameter | FormuLITE |
---|---|
Calculated bio-content | 36.6 |
Mix ratio by weight | 100:30 |
Mix ratio by volume | 100:36 |
Mix viscosity at 25 °C (cPs) | 700 |
Mix viscosity at 40 °C (cPs) | 242 |
Pot life at 25 °C (min) | 105 |
Pot life at 40 °C (min) | 57 |
Tg (°C) | 92 |
Tensile strength (MPa) | 62 |
Tensile modulus (MPa) | 2615 |
Elongation at Fmax (%)/Elongation at break (%) | 4.8/6.4 |
Flexural strength (MPa) | 92 |
Flexural modulus (MPa) | 2262 |
Fibers | T20% (°C) | T(max) (°C) | Sample Weight at 800 °C (mg) | Yc (Char Yield, mg) |
---|---|---|---|---|
Raw Fiber | 210 | 400 | 4.2 | 0.5 |
Pre-Treated Fiber | 235 | 510 | 3.8 | 0.7 |
KMnO4-Soaked Fiber | 250 | 480 | 3.5 | 0.75 |
KMnO4-Refluxed Fiber | 245 | 460 | 5.7 | 1.2 |
10% C6H5SO2Cl-Treated Fiber | 155 | 490 | 5.4 | 1.1 |
20% C6H5SO2Cl-Treated Fiber | 140 | 470 | 4.6 | 1.25 |
Ethylene Dichloride-Treated Fiber | 260 | 430 | 5.2 | 1.3 |
Load (N) | Sliding Speed (m/s) | Fiber Treatment | Lubrication Type | Sliding Distance (m) | Wear Rate (mg/m) | Friction Coefficient (µ) |
---|---|---|---|---|---|---|
10 | 0.5 | Raw | Dry | 100 | 0.055 | 0.6 |
10 | 1 | Pre | Water | 200 | 0.05 | 0.55 |
10 | 1.5 | KMn | Oil | 300 | 0.045 | 0.5 |
10 | 2 | Benz | Grease | 400 | 0.04 | 0.45 |
10 | 2.5 | Ethy | Hybrid | 500 | 0.035 | 0.4 |
20 | 0.5 | Pre | Oil | 400 | 0.05 | 0.55 |
20 | 1 | KMn | Grease | 500 | 0.045 | 0.5 |
20 | 1.5 | Benz | Hybrid | 100 | 0.04 | 0.45 |
20 | 2 | Ethy | Dry | 200 | 0.035 | 0.4 |
20 | 2.5 | Raw | Water | 300 | 0.06 | 0.65 |
30 | 0.5 | KMn | Hybrid | 200 | 0.045 | 0.5 |
30 | 1 | Benz | Dry | 300 | 0.04 | 0.45 |
30 | 1.5 | Ethy | Water | 400 | 0.035 | 0.4 |
30 | 2 | Raw | Oil | 500 | 0.065 | 0.7 |
30 | 2.5 | Pre | Grease | 100 | 0.05 | 0.55 |
40 | 0.5 | Benz | Water | 500 | 0.04 | 0.45 |
40 | 1 | Ethy | Oil | 100 | 0.035 | 0.4 |
40 | 1.5 | Raw | Grease | 200 | 0.07 | 0.75 |
40 | 2 | Pre | Hybrid | 300 | 0.055 | 0.6 |
40 | 2.5 | KMn | Dry | 400 | 0.045 | 0.5 |
50 | 0.5 | Ethy | Grease | 300 | 0.035 | 0.4 |
50 | 1 | Raw | Hybrid | 400 | 0.075 | 0.8 |
50 | 1.5 | Pre | Dry | 500 | 0.05 | 0.55 |
50 | 2 | KMn | Water | 100 | 0.045 | 0.5 |
50 | 2.5 | Benz | Oil | 200 | 0.04 | 0.45 |
Level | Load (N) | Sliding Speed (m/s) | Fiber Treatment | Lubrication Type | Sliding Distance (m) |
---|---|---|---|---|---|
1 | −1.446 | −1.446 | −1.462 | −1.446 | −1.446 |
2 | −1.444 | −1.439 | −1.486 | −1.440 | −1.440 |
3 | −1.442 | −1.440 | −1.443 | −1.436 | −1.441 |
4 | −1.438 | −1.439 | −1.424 | −1.442 | −1.439 |
5 | −1.439 | −1.444 | −1.394 | −1.444 | −1.442 |
Delta | 0.008 | 0.007 | 0.093 | 0.010 | 0.007 |
Rank | 3 | 4.5 | 1 | 2 | 4.5 |
Level | Load (N) | Sliding Speed (m/s) | Fiber Treatment | Lubrication Type | Sliding Distance (m) |
---|---|---|---|---|---|
1 | 0.2725 | 0.2725 | 0.2450 | 0.2725 | 0.2725 |
2 | 0.2780 | 0.2945 | 0.2175 | 0.2890 | 0.2890 |
3 | 0.2835 | 0.2890 | 0.2725 | 0.3000 | 0.2835 |
4 | 0.2945 | 0.2890 | 0.3055 | 0.2835 | 0.2945 |
5 | 0.2945 | 0.2780 | 0.3825 | 0.2780 | 0.2835 |
Delta | 0.0220 | 0.0220 | 0.1650 | 0.0275 | 0.0220 |
Rank | 4 | 4 | 1 | 2 | 4 |
Source | DF | Seq SS | Contribution | Adj SS | Adj MS | F-Value | p-Value |
---|---|---|---|---|---|---|---|
Fiber Treatment | 4 | 0.002684 | 90.86% | 0.002684 | 0.000671 | 54.78 | 0.000 |
Lubrication Type | 4 | 0.000074 | 2.51% | 0.000074 | 0.000019 | 1.51 | 0.246 |
Error | 16 | 0.000196 | 6.64% | 0.000196 | 0.000012 | ||
Total | 24 | 0.002954 | 100.00% |
Term | Coef | SE Coef | 95% CI | T-Value | p-Value | VIF |
---|---|---|---|---|---|---|
Constant | 0.047200 | 0.000700 | (0.045716, 0.048684) | 67.43 | 0.000 | |
Fiber Treatment | ||||||
Benz | −0.00720 | 0.00140 | (−0.01017, −0.00423) | −5.14 | 0.000 | 1.60 |
Ethy | −0.01220 | 0.00140 | (−0.01517, −0.00923) | −8.71 | 0.000 | 1.60 |
KMn | −0.00220 | 0.00140 | (−0.00517, 0.00077) | −1.57 | 0.136 | 1.60 |
Pre | 0.00380 | 0.00140 | (0.00083, 0.00677) | 2.71 | 0.015 | 1.60 |
Lubrication Type | ||||||
Dry | −0.00220 | 0.00140 | (−0.00517, 0.00077) | −1.57 | 0.136 | 1.60 |
Grease | 0.00080 | 0.00140 | (−0.00217, 0.00377) | 0.57 | 0.576 | 1.60 |
Hybrid | 0.00280 | 0.00140 | (−0.00017, 0.00577) | 2.00 | 0.063 | 1.60 |
Oil | −0.00020 | 0.00140 | (−0.00317, 0.00277) | −0.14 | 0.888 | 1.60 |
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Samanth, M.; Hiremath, P.; Deepak, G.D.; Naik, N.; H S, A.; Heckadka, S.S.; Shivamurthy, R.C. Sustainable Composites from Sugarcane Bagasse Fibers and Bio-Based Epoxy with Insights into Wear Performance, Thermal Stability, and Machine Learning Predictive Modeling. J. Compos. Sci. 2025, 9, 124. https://doi.org/10.3390/jcs9030124
Samanth M, Hiremath P, Deepak GD, Naik N, H S A, Heckadka SS, Shivamurthy RC. Sustainable Composites from Sugarcane Bagasse Fibers and Bio-Based Epoxy with Insights into Wear Performance, Thermal Stability, and Machine Learning Predictive Modeling. Journal of Composites Science. 2025; 9(3):124. https://doi.org/10.3390/jcs9030124
Chicago/Turabian StyleSamanth, Mahima, Pavan Hiremath, G. Divya Deepak, Nithesh Naik, Arunkumar H S, Srinivas Shenoy Heckadka, and R. C. Shivamurthy. 2025. "Sustainable Composites from Sugarcane Bagasse Fibers and Bio-Based Epoxy with Insights into Wear Performance, Thermal Stability, and Machine Learning Predictive Modeling" Journal of Composites Science 9, no. 3: 124. https://doi.org/10.3390/jcs9030124
APA StyleSamanth, M., Hiremath, P., Deepak, G. D., Naik, N., H S, A., Heckadka, S. S., & Shivamurthy, R. C. (2025). Sustainable Composites from Sugarcane Bagasse Fibers and Bio-Based Epoxy with Insights into Wear Performance, Thermal Stability, and Machine Learning Predictive Modeling. Journal of Composites Science, 9(3), 124. https://doi.org/10.3390/jcs9030124