3‐Dimensional Printing of Hydrogel‐Based Nanocomposites: A Comprehensive Review on the Technology Description, Properties, and Applications
Bibliographic record
Abstract
Increasing demand for customized implants and tissue scaffolds requires advanced biomaterials and fabricating processes for fabricating three‐dimensional (3D) structures that resemble the complexity of the extracellular matrix (ECM). Lately, biofabrication approaches such as cell‐laden (soft) hydrogel 3D printing (3DP) have been of increasing interest in the development of 3D functional environments similar to natural tissues and organs. Hydrogels that resemble biological ECMs can provide mechanical support and signaling cues to cells to control their behavior. Although the capability of hydrogels to produce artificial ECMs can regulate cellular behavior, one of the major drawbacks of working with hydrogels is their inferior mechanical properties. Therefore, keeping and enhancing the mechanical integrity of fabricated scaffolds has become an essential matter for 3D hydrogel structures. Herein, 3D‐printed hydrogel‐based nanocomposites (NCs) are evaluated systematically in terms of introducing novel techniques for 3DP of hydrogel‐based materials, properties, and biomedical applications.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".