Enhancement of Additively Manufactured Bagasse Fiber-Reinforced Composite Material Properties Utilizing a Novel Fiber Extraction Process Used for 3D SLA Printing
Bibliographic record
Abstract
The growing interest in sustainable and biodegradable materials has prompted significant attention towards natural fiber-reinforced composites (FRC) due to their lower environmental impacts. In a similar sustainable vein, this study fabricated composite materials utilizing bagasse fibers with the 3D SLA (Stereolithography) printing method. To start with, a novel fiber extraction process was adopted for extracting fiber from the bagasse stem in three distinct methods (Process-1, Process-2, and Process-3). The fiber extraction process includes washing, sun-drying, manual collection of rind fibers, immersion of rind fibers in NaOH at specific concentrations for specific durations, combing, and drying. In Process-1, the rind fibers were immersed in 5% NaOH for 15 h, while in Process-2 and Process-3, the rind fibers were immersed in 1% NaOH, but the soaking time varied: 25 h for Process-2 and 18 h for Process-3.for 25 h, and in Process-3, the rind fibers were immersed in 1% NaOH for 18 h. The resulting bagasse fibers underwent comprehensive property assessment with a focus on functional group analysis, diameter measurement, and tensile strength assessment. Subsequently, these fibers were used to fabricate composite materials via the 3D SLA printing technique after being treated in a NaOH solution. The Fourier Transform Infrared (FTIR) Spectroscopy results clearly showed that a fraction of hemicellulose and lignin was removed by NaOH, resulting in improved tensile strength of the bagasse fibers. Three-dimensional-printed composites reinforced with bagasse fibers extracted through the P1 method showed the highest improvement in tensile strength (approximately 70%) compared to specimens made from pure resin. The lack of pores in the composite and the observable fiber fracture phenomena clearly indicate that 3D printing technology effectively enhances the quality of the interface between the fiber and the matrix interfacial bonding, consequently resulting in improved tensile properties of the composites. The 3D-printed composites reinforced with bagasse fiber showcased impressive tensile properties and provided solutions to the limitations of traditional composite manufacturing methods. This sets the stage for developing innovative composite materials that combine natural fibers with cutting-edge fabrication techniques, offering a promising path to tackle present and future economic and ecological challenges.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".