Dispersion Strategy improves the mechanical properties of 3D-Printed biopolymer nanocomposite
Bibliographic record
Abstract
Homogenous dispersion of nanoparticles in polymer matrices is a technical challenge that if overcome can lead to improved mechanical properties of the resulting nanocomposites. In this work, we successfully refined commercially-available nanoscale, calcium deficient, and poorly crystalline hydroxyapatite (nHA) particles and composited them with acrylate and methacrylate functionalized soybean oil (mAESO) and triethylene glycol dimethacrylate (TEGDMA) producing inks for masked stereolithography (mSLA) -based 3D printing. First, we used shear mixing and ultrasonication on nHA/ethanol mixtures to break down agglomerates and then separated the finest nanoparticles from the remaining agglomerates using centrifugation. The refined nanoparticles (termed fine) were then mixed with the resins and UV-initiator to produce inks for 3D printing. Similarly, we prepared one ink using as-purchased nHA particles (termed raw) and another ink using leftover agglomerates after refinement (termed coarse). We compared the rheological properties of the nHA-resin inks. We used mSLA to fabricate nanocomposite specimens and tested them using flexural, and Mode-I fracture toughness testing following ASTM standards. The dispersion of nanoparticles in the polymer matrix was studied by analyzing backscattered mode scanning electron microscopy images. The nHA particle refinement improved the nanoparticle dispersion in the resin matrix while also increasing the viscosity and shear yield strength of the nanocomposite ink. The flexural fracture strength, flexural modulus, and Mode-I fracture toughness of refined nHA-based nanocomposites were increased by 11 %, 71 %, and 12 %, respectively compared to the raw nHA-based nanocomposites. However, the flexural fracture strain of refined nHA-based nanocomposites was lower by 40 % compared to the raw nHA-based nanocomposites. The nanocomposites became stiffer with the incorporation of refined nanoscale nHA. The separation of nanoscale nHA particles, excellent dispersion of these nanoparticles in polymer matrix, and improved flexural strength and modulus opens a new avenue towards the 3D printing of high-performance nHA-based nanocomposites.
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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".