Electrochemical corrosion behavior of X80 pipeline steel in a near‐neutral pH solution
Bibliographic record
Abstract
Abstract In this work, the electrochemical corrosion behavior of X80 pipeline steel was investigated in a near‐neutral pH solution using electrochemical impedance spectroscopy (EIC) and photo‐electrochemical (PEC) measurements as well as X‐ray photo‐electron spectroscopy (XPS) technique. The effects of hydrogen‐charging and stress were considered. The results show that the steel is in an active dissolution state, and a layer of corrosion product is formed and deposited on the electrode surface, which is subjected to further oxidation to form ferric oxide and hydroxide. Photo‐illumination enhances anodic dissolution of the steel when it is under anodic polarization due to destroying of the corrosion product film. When the steel is under cathodic polarization, the cathodic current density decreases upon laser illumination due to the photo‐oxidation of hydrogen atoms generated during cathodic reactions, which behaves as an anodic reaction to offset the cathodic current density. Hydrogen‐charging and stress decrease the corrosion resistance of the steel and enhance the dissolution rate of the steel.
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".