Bibliographic record
Abstract
Abstract Although petrochemical process streams are primarily composed of hydrocarbons, corrosion and fouling is observed in various locations and environments in operating plants. An electrochemical high temperature and high pressure facility is used to study the corrosion behaviour of carbon, low alloy and stainless steels in several petrochemical environments. The electrochemical techniques such as cyclic voltammetry and open circuit potential measurements are used to study the effect of metallurgy and surface roughness on the initiation of corrosion/fouling on carbon and stainless steels in several solutions (i.e. naphtha, raw pyrolysis gasoline and quench tower bottoms). The experiments are conducted using a quasi reference Ag metal electrode. Initial results suggest that corrosion/fouling rates vary with surface roughness and 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. Electrochemical impedance spectroscopy (EIS) is used to determine the solution resistance of naphtha and quench tower bottoms. A number of fouling characteristics including the time for initial surface coverage, the rate of film formation and the properties of the surface film have been studied using cyclic voltammetry and open circuit potential.
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) | 0.000 | 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".