Characterization of Post-Sintering Shrinkage of Ceramic-Based Lattice Structures Printed Using LCD Resin Printer
Bibliographic record
Abstract
Unlike polymers and metals, additive manufacturing (AM) of ceramic parts has only recently become an increasingly important technology, thanks to ceramic’s exceptional thermal and chemical properties. Most of the AM-processed ceramic parts must undergo a sintering process that adds additional challenges. Managing post-sintering shrinkage remains a critical challenge that impacts the dimensional accuracy and integrity of the final printed components. This is particularly important for intricate designs if the part has triply periodic minimal surface lattice structures. This study systematically analyzes the effect of lattice parameters, namely cell sizes along the X, Y, and Z axes, lattice type, and wall thickness on the post-sintering shrinkage. A number of samples with different lattice parameters were designed and printed with an LCD 3D resin printer using commercially available aluminosilicate resin. Later, the specimens were subjected to the same sintering process, and the dimensions of the green bodies and sintered parts were studied to measure volumetric and linear shrinkages.
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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 | 0.001 |
| 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".