Pitting Corrosion of X65 Pipeline Steel in CO2-Saturated Chloride Solutions: Effects of Acetic and Formic Acids with Pit Chemistry Insights from Pure Iron Experiments
Bibliographic record
Abstract
The influence of acetic acid (HAc) and formic acid (HFr) on the pitting corrosion behavior of X65 pipeline steel in CO2-saturated 1 wt% NaCl solution was investigated using potentiodynamic polarization, long-term immersion, and pit morphology analysis. To mechanistically evaluate the role of organic acids on pit chemistry, a pure-iron lead-in pencil electrode technique was used, allowing controlled, one-dimensional pit growth and quantification of key chemical parameters inside the pit environment. Both HAc and HFr shifted the corrosion potential to more noble values and enhanced cathodic kinetics by buffering local pH, thereby accelerating overall corrosion rates. Immersion testing and scanning electron microscopy revealed that the presence of organic acids resulted in fewer but deeper and more aggressive pits than those formed in acid-free chloride solutions. Mechanistic analysis revealed that HAc and HFr exert a dual effect, increasing the pit propagation rate while also altering the local chemistry to delay the termination of pit growth by raising the required concentration of metal cations. These findings indicate that although acetic and formic acids do not increase the number of corrosion pits, they substantially increase pit severity, representing a critical risk factor for pipeline integrity in CO2-rich, chloride-containing environments common to oil and gas operations.
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How this classification was reachedexpand
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) | 0.000 | 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".