Bibliographic record
Abstract
This thesis outlines the integration of 3D printing and Atomic Layer Deposition (ALD) to create advanced 3D printed architectures.Polymer nanocomposite materials have been synthesized using common polymer materials to alter physical properties however these nanocomposites are synthesized prior to use.In this thesis, Atomic Layer Deposition (ALD) was used in combination with common and inexpensive polymer materials post model creation (using 3D printing) to create nanoscale hybrid materials.3D printed Acrylonitrile Butadiene Styrene (ABS) and Polyvinyl Alcohol (PVA) polymer structures were coated and infiltrated with alumina (Al2O3) using the trimethylaluminum(III) (TMA) and water ALD process.Coating studies on ABS were carried out at 80 ˚C, which resulted in a 203 nm thin film with a 1.35 Å growth per cycle (GPC).The thin film was a welladhered protective overcoating on ABS which prevented the reaction with acetone vapors in a solvent resistance experiment.Scratch and more aggressive tape tests were not able to remove the overcoating completely from the polymer surface which provided a 50 % and 32 % increase in acetone vapour resistance before initial deformation and complete structure collapse respectively.Infiltration studies on ABS and PVA structures were preformed at 130 ˚C and 80 ˚C respectively, to alter their physical properties.Differential Scanning Calorimetry (DSC) was used to determine the Glass Transition Temperature (Tg) of the polymers pre-and post-deposition after varying the number of ALD cycles, resulting in a change of ~ 9 ˚C and ~ 27 ˚C for ABS and PVA, respectively.After one heat cycle the post-deposition Tg reverted back to its pre-disposition point indicating reversibility of the deposition effects are possible.Optimal growing patterns, polymer composition, and inhibiting surface coatings were examined by Energy Dispersive X-ray Spectroscopy (EDS) mappings which effected the amount of infiltration possible within the polymer substrate and in turn Tg.These results achieved provides guidelines to creating nanoscale hybrid materials using 3D printing and ALD via coating and infiltration and in tern altering the physical and thermal properties of 3D printed polymer architectures with significant impact in the development of advanced 3D printed architectures leading to a wide array of applications in polymer and material chemistry.
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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 | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".