Développement de verres phosphates à basse température de transition vitreuse pour l'impression 3D et ses applications
Bibliographic record
Abstract
Additive manufacturing, also known as 3D printing, refers to a set of manufacturing techniques by adding matter, as opposed to the more 'traditional' subtractive methods, such as machining. There are a lot of very different additive manufacturing processes, as well as a diversity of printable materials, including metals, ceramics and polymers. However, very few solutions have been developed so far for the printing of glass. The main obstacles are the very high processing temperatures required.The main objective of this thesis is to enable the additive manufacturing of phosphate glasses. These glasses are advantageous for their lower working temperatures and are also known for their applications in optics and biomaterials. To that purpose, convenient phosphate glass compositions with low glass transition temperatures were developed. The first system studied was (50 - x) P2O5 – 25 Na2O – 25 K2O – x M2O3 (%mol), with M = Al ou Ga and x between 0 and 10 %mol. The most ideal composition studied in the system was then successfully printed following a fused deposition modeling process, using a modified commercial polymer 3D printer. To obtain printed glass objects that are transparent, printing parameters were finely tuned to avoid potential defects. The residual porosity of printed glass objects is estimated to be lower than 0.02 %. Being able to print phosphate glasses with this process enables the fabrication of optical parts with complex geometries and unique properties.Transparent hydrated phosphate glasses were also studied. These materials exhibit a glass transition temperature below 100 °C and could be synthetized at temperatures as low as 300 °C. The structure of these new materials was then investigated, using Raman, infrared and NMR spectroscopies. -OH groups were found within the phosphate network, where they act as network modifiers, causing the modification of the glass' properties. By adding zinc oxide to the glass composition, it is possible to make the hydrated phosphate glasses more resistant to dissolution while keeping their transparency and their low glass transition temperature. These materials enable new functionalization possibilities, some of which were studied. For instance, glass-polymer composite fibers were made, and tungsten trioxide functional nanoparticles were integrated in a hydrated phosphate glass matrix.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".