Tribocorrosion of additively manufactured and wrought Ti6Al4V in a saline environment
Bibliographic record
Abstract
Laser powder bed fusion (LPBF) and wrought Ti6Al4V were compared from a tribocorrosion perspective in 0.9% NaCl, distinguishing between mechanical and chemical (oxidative) wear through potential-controlled measurements. The aim was to elucidate the manufacturing- and potential-dependent tribocorrosion mechanisms in a saline environment. While both manufacturing methods resulted in excellent corrosion resistance, the LPBF titanium alloy exhibited a finer, distinct microstructure, higher microhardness, and greater tribocorrosion resistance under applied cathodic and anodic potentials in saline than the wrought alloy. More available slip systems, lower grain boundary density, easier crack formation and propagation at the oxide-subsurface interface, and more oxidized third-body particles were responsible for the higher mechanical and chemical volume loss of wrought samples. These features were related to the microstructural differences; the wrought titanium alloy consisted of a β phase, along with α phase, and a lower grain boundary density, whereas the LPBF alloy possessed α/α′ phases and a higher grain boundary density. • Chemical and mechanical wear distinguished through applied potential control. • Laser powder bed fusion (LPBF) and wrought Ti6Al4V alloys compared. • No β phase in LPBF Ti6Al4V resulted in higher microhardness and fewer cracks. • Higher tribocorrosion resistance of LPBF than wrought Ti6Al4V in saline.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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".