STUDY OF THE RHEOLOGICAL PROPERTIES OF COMPOSITE POLYMER STABILIZERS FOR DRILLING FLUIDS
Bibliographic record
Abstract
This article presents the results of experimental data on the preparation of a composite heatresistant reagent for drilling fluids, including a modified copolymer based on polyacrylonitrile (by hydrolysis in the absence of a mixture of sodium hydroxide) and vinylsulfonic acid. A thermally stable composite reagent to polyvalent cations has been obtained, which reduces filtration and improves the anti-wear properties of clay suspensions. The values of the optimal reaction time and temperature were determined, the viscosity of the sampled polymer solutions was determined. The ratio of monomers and modification conditions are selected, this ensures a high conversion of monomers, and also increases the yield of the final product. The synthesized polymer of acrylonitrile and in the presence of fatty acids of gossypol resin and sulfuric acid in the pH = 3.5-5.5, with subsequent modification. The synthesized water-soluble polymer has a diphilic structure throughout the structure, the macromolecules of which contain a hydrophobic group and a hydrophilic part. They are able to adsorb and lower the interfacial free energy, which allows them to be classified as high-molecular surfactants.
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 | 0.001 |
| 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".