Nanoscale Chemical Surface Analyses of Recycled Powder for Direct Metal Powder Bed Fusion Ti-6Al-4V Root Analog Dental Implant: An X-ray Photoelectron Spectroscopy Study
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Over the past couple of decades, additive manufacturing and the use of root-analogue-printed titanium dental implants have been developed. Not all powder particles are sintered into the final product during the additive manufacturing process. Reuse of the remaining powder could reduce the overall implant manufacturing cost. However, Ti-6Al-4V powder particles are affected by heat, mechanical factors, and oxidization during the powder bed fusion manufacturing process. Degradation of the powder may harm the final surface composition and decrease the biocompatibility and survival of the implant. The uncertainty of the recycled powder properties prevents implant fabrication facilities from reusing the powder. This study investigates the chemical composition of controlled, clean, and recycled titanium alloy powder and root-analogue implants (RAI) manufactured from these powders at three different depths. The change in titanium’s quantity, oxidization state, and chemical composition in powder and RAI implants have been demonstrated and analyzed. While not identical, the surface chemical composition of the recycled powder implant and the implant manufactured from unused powder are similar. The results also indicate the presence of TiO2 on all surfaces. Many studies confirmed that titanium dioxide on the implant’s surface correlates with better osteointegration, reduced bacterial infection, and increased corrosion resistance. Considering economic and environmental aspects, surface chemical composition comparison of clean and reused powder is crucial for the future manufacturing of cost-effective and biocompatible implants.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 it