High stiffness 3D-printed continuous pitch carbon fiber reinforced polymer composites
Bibliographic record
Abstract
This study presents a method for 3D printing very high stiffness pitch-based carbon fiber (CF) reinforced polylactic acid (PLA) composites using a modified open-source 3D printer. The fused filament fabrication (FFF) technique was used to fabricate the samples with alternating layers of PLA and PLA-coated pitch CF. The tensile Young’s modulus of the 3D-printed composite samples was measured to characterize the effect of different grades and volume fractions of pitch CF on the behaviour of the printed composites. Three grades of pitch CF which have different Young’s modulus were used with volume fractions ranging from 2.4 to 8.4%. Tensile tests showed that the K1392U CF reinforced composite with a 7.3% volume fraction demonstrated the highest improvement in Young’s modulus of 850% compared to neat 3D-printed PLA. This improvement is notably higher than any previous 3D-printed carbon-based composites at a relatively low volume fraction of CF. Statistical analysis showed increased Young’s modulus in all of 3D-printed composite samples tested. The experimental values were compared to the Halpin-Tsai model and suggest that some degree of fibre breakage occurred during the 3D printing process owing to the relative stiffness of the pitch-based fibers. Future directions and suggestions for process improvements are discussed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".