Low-temperature solvent-based 3D printing of PLGA: a parametric printability study
Bibliographic record
Abstract
In this paper, a novel low-temperature 3 D printing technique is introduced and characterized through a parametric printability study to fabricate poly-lactic-co-glycolic acid (PLGA) constructs using methyl ethyl ketone (MEK) as a solvent. The effects of varying concentrations of PLGA in MEK solvent, lactic to glycolic ratio of PLGA, the molecular weight of PLGA, and the scaling of PLGA constructs on the printability are investigated. PLGA concentrations of higher than 80% w/v, lactic to glycolic ratio more than 75%, molecular weight more than 100 kDa, and printing through nozzles smaller than 0.96 mm internal diameter are recommended for 3 D printing of PLGA constructs with high shape fidelity. Ultimately, a vacuum drying solvent removal process is implemented, and Proton Nuclear Magnetic Resonance (1H-NMR) spectroscopy is used to confirm complete removal of the solvent from PLGA constructs. The results of this study can be used for the development of drug-eluting implants.
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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".