Effect of bicarbonate concentration on corrosion of high strength steel
Bibliographic record
Abstract
This research evaluates the passivation process, in relation to the anodic and cathodic reactions, in deoxygenated solutions of different bicarbonate concentrations. Two types of API-X100 steel microstructures were examined. They are similar to near fusion heat affected zones (HAZs) which were produced by special thermal cycles. By monitoring the open circuit potentials, the passivation process exhibited electrochemical signs that it forms faster with higher bicarbonate concentration. During cyclic voltammetry, bicarbonate in concentrations less than 0·1M impedes the passivation, by catalysing the anodic dissolution. In higher concentrations, bicarbonate seemed more protective in facilitating the development of thicker passive films, from an electrochemical perspective that encourages corresponding physicochemical investigations in the future. The transpassivation seemed to depend more on the chemistry of the passive film than on the formation of FeCO3. Cooling down the HAZs at high rates could make them more corrosion resistant, but probably of less protective corrosion products.
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 | 0.002 |
| 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 | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".