Corrosion and Fouling of Chromium and Nickel Alloys in Petrochemical Environments
Bibliographic record
Abstract
Abstract Corrosion and fouling is encountered in various locations and environments in operating petrochemical plants despite the fact that process streams are primarily composed of hydrocarbons. An electrochemical high temperature and high pressure facility is used to study the corrosion and fouling behaviour of low-alloy, stainless and exotic alloy steels in several petrochemical environments. Electrochemical techniques including cyclic voltammetry, open circuit potential and electrochemical impedance spectroscopy are used to study the effect of temperature, water concentration, chromium and nickel concentration on the initiation of corrosion/fouling on various alloyed steels in several petrochemical solutions (i.e. naphtha, raw pyrolysis gasoline and quench tower bottoms). Experiments are conducted using a quasi-reference Ag metal electrode. Previous results on carbon and low alloy steels suggest that corrosion rates vary with conductivity, which are controlled, by varying the concentration of water. Scanning electron microscopy and energy dispersive X-ray analysis (SEM/EDX) is used to look at the nature of the deposit formed after applying the aforementioned electrochemical techniques.
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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) | 0.000 | 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 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".