Natural alkaloid as a non‐toxic, environmentally friendly corrosion inhibitor
Bibliographic record
Abstract
Abstract Acid treatments are commonly used in various oilfield treatments in order to remove inorganic scale or to stimulate formations. When applied in high temperature wells, these acids become very corrosive and can cause severe damage to tubulars as well as downhole equipment. Therefore, corrosion inhibitors are a necessary additive in these stimulation treatments. Commercial corrosion inhibitors used in the oil and gas industry are damaging to the environment and harmful to human health. Therefore, it is necessary to find a corrosion inhibitor that is both environmentally friendly and non‐toxic. An alkaloid was tested with N‐80 and S13Cr coupons and exposed to HCl solutions ranging from 15–28 wt.% at temperatures between 25–121°C for 6 h. In addition, a control solution containing no corrosion inhibitor was used to establish a corrosion rate for a base case at each temperature. For both N‐80 and S13Cr metals, the alkaloid performed well, with corrosion rates significantly lower than the industry standards. The concentration of alkaloid used was at 2 wt.% for most tests and was shown to be effective even at concentrations as low as 0.2 wt.%. Furthermore, the corrosion inhibitor was found to be stable in the presence of emulsified acid and was able to provide sufficient corrosion resistance. This shows that this naturally occurring, non‐toxic alkaloid is a suitable corrosion inhibitor for oilfield steels as an alternative to existing commercial corrosion inhibitors.
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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) | 0.001 | 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 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".