Crack propagation in adhesive bonded 3D printed polyamide: Surface versus bulk patterning of the adherends
Bibliographic record
Abstract
The confined build space of 3D printers often necessitates breaking down larger objects into sub-components for efficient printing. Addressing this challenge, related existing research emphasizes the growing adoption of structural adhesives as a key method for joining 3D printed components. In this context, the present study combines finite element modeling, design exploration, and additive manufacturing, to ascertain the role of the adherends’ architecture on the mechanics of crack growth in adhesive bonded 3D printed materials. Finite element simulations and experiments are carried out using Double Cantilever Beam (DCB) specimens comprising epoxy-bonded selective laser sintered polyamide (PA). In particular, the study includes adherends that feature either sub-surface hollow channels of various shapes (bulk patterns) or sinusoidal interfaces with different aspect ratios (surface patterns). The objective is to demonstrate how the proposed patterning strategies not only promote crack shielding and delayed growth but also unlock energy-absorbing processes, such as interfacial void growth and buckling, that are absent in the control joint (i.e., no patterns). Therefore, customizing the architecture of the adjoined layers ultimately results in toughening and enhanced damage tolerance in adhesive joints that comprise 3D printed materials.
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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 | 0.000 | 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) | 0.000 | 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".