UV-Assisted Direct-Write Assembly of Scaffold-Templated Nanoclay Composites via Biotin-Streptavidin Interactions
Bibliographic record
Abstract
Three-dimensional epoxy scaffolds with abundant active epoxy groups on surfaces were fabricated through UV-assisted direct-write manufacturing process. The prepared scaffolds composed of cylindrical filaments (diameter ∼100 μm) were aminated by reacting the epoxy groups with 1, 3-diaminopropane. The resulting aminated scaffolds were subsequently biotinylated and then successfully applied to immobilize biotinylated nanoclay conjugates via a specific, strong and rapid binding of biotin and streptavidin. In another approach, the same amount of nanoclays was properly dispersed in epoxy by three-roll mill machine inducing high shear mixing. The nanoclay-epoxy filaments were then deposited by a computerized-control robot in a 3D micro structure scaffold form. Tensile mechanical tests were performed with a dynamic mechanical analysis (DMA) using a film tension clamp on three microstructures: nanoclay-epoxy scaffolds, aminated-biotinylated nanoclays coated on unloaded epoxy scaffolds and finally unloaded epoxy scaffolds (used as a reference). DMA tensile measurements indicated a slight improvement in modulus (by ∼5%), but significant increase in strength (by ∼24%), fracture strain (by ∼21%) and fracture energy (by ∼38%) by introducing biotin-streptavidin strong bonds among epoxy scaffolds and nanoclays in comparison with those of mixed nanoclay-epoxy scaffolds. These mechanical improvements are attributed to the strong biotin and streptavidin bonds between the epoxy scaffolds and nanoclays.
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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".