3D printing high interfacial bonding polyether ether ketone components via pyrolysis reactions
Bibliographic record
Abstract
Recently, 3D-printed polyether-ether-ketone (PEEK) components have been shown to offer many applications in state-of-the-art electronics, 5G wireless communications , medical implantations, and aerospace components. Nevertheless, a critical barrier that limits the application of 3D printed PEEK components is their weak interfacial bonding strength . Herein, we propose a novel method to improve this unsatisfied situation via the interface plasticizing effect of benzene derivatives obtained from the thermal pyrolysis of trisilanolphenyl polyhedral oligomeric silsequioxane (POSS). Based on this method, the bonding strength of the filaments and interlayers of 3D-printed POSS/PEEK components can reach 82.9 MPa and 59.8 MPa, respectively. Moreover, the enhancing mechanism of the pyrolysis products derived from the POSS is characterized using pyrolysis-gas chromatography/mass spectrometry (Py-GC/MS), Fourier transform infrared spectroscopy (FTIR), and X-ray computed tomography (X-CT). Our proposed strategy broadens the novel design space for developing additional 3D-printed materials with satisfactory interfacial bonding strength.
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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".