Bicarbonate, Temperature, and pH Influences on the Passivation of API-X100 Pipeline Steel in Simulated Groundwater Solutions
Bibliographic record
Abstract
The influence of bicarbonate ion (HCO3−) concentration and related environmental parameters such as pH and temperature on the passivation of API-X100 pipeline steel is the focus of this investigation. NS4 solution simulating groundwater trapped under disbonded coatings at regions where near-neutral stress corrosion cracking (SCC) occurs was used as a reference. Bicarbonate content in the solutions was increased steadily and the critical HCO3− concentration at which passivation becomes evident is found using potentiodynamic polarization sweeps. Multi-step dissolution is observed especially in higher pH solutions, owing to the involvement of hydroxide ions (OH−) in the adsorption of hydrous Fe(OH)2. Dynamic electrochemical impedance spectroscopy (DEIS) is used to study and compare interfacial processes in active, pre-passive, passive, and trans-passive regions. The results of the potentiodynamic and DEIS tests achieve good agreement. The protective properties of the passive film formed at three different HCO3− concentrations (critical passivation and two higher concentrations) and temperatures (25, 50, and 75 °C) are studied. The combined effect of HCO3− and temperature resulted in a pH range from ∼6.7 to 9.3 for the nine conditions in the corresponding test matrix. Passive films were formed at a suitable anodic potential and then studied with electrochemical impedance spectroscopy (EIS), Mott-Schottky, and cyclic voltammetry (CV) tests. Evidence of adsorption and diffusion, in addition to significant resistance from the passive film, is observed and accounted for in the equivalent circuit, which achieved good correspondence when fitted with the experimental data. The protective properties of the overall passive film are enhanced with increased bicarbonate and decreased temperature. Positive slopes in the Mott-Schottky plots reveal the n-type semi-conductive behavior of the passive films in all conditions and the CV results highlight the proposed reaction sequences occurring in different potential scan regions. CV measurements also confirm the enhanced protective properties of passive films with increased bicarbonate and lower temperatures observed in the EIS analysis.
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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".