Deformation, mechanical properties, and fracture of titanium hydrides
Bibliographic record
Abstract
This study investigates the deformation behavior and cracking mechanisms in titanium δ-hydrides through in-situ scanning electron microscopy (SEM) and in-situ electron backscatter diffraction (EBSD) tensile experiments. Two commercially pure titanium specimens were hydrided and then homogenized to have both intergranular and intragranular δ-hydrides, before being deformed to ∼14 % macroscopic tensile strain . Pre-deformation grain orientations and shapes were measured by EBSD and subsequently imported into a crystal plasticity finite element model to simulate the evolution of localized deformation fields and the formation of microcracks within hydrides. In addition, indentation experiments were performed to extract plastic properties of hydrides. Pre-deformation numerical and experimental results indicated that the formation of δ-hydrides, in the absence of external mechanical loads, induces lattice rotations up to 2° near hydride tips as well as at the intersection of intergranular and intragranular hydrides. With applying external mechanical loads, ̅ ̅ ̅ { 11 2 ̅ 2 } < 11 2 ̅ 3 ̅ > compression twins form in the titanium matrix, followed by the formation of secondary ̅ ̅ ̅ { 10 1 ̅ 2 } < 10 1 ̅ 1 ̅ > extension twins within compression twins. The interaction of hydrides with compression twins increase local rotations within hydrides up to 6°. Microcracks were detected in both intragranular and intergranular δ-hydrides, with a higher propensity measured within the former. These microcracks were observed to form at the intersections of compression twins and hydrides, on the crystallographic planes of hydrides. Numerical results confirm that the presence of twins affect the formation of microcracks.
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 | 0.000 |
| 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".