Rheology of Hydrophobically Modified Polyacrylamide-<i>co</i>-poly(acrylic acid) on Addition of Surfactant and Variation of Solution pH
Bibliographic record
Abstract
Constant shear and shear dependent viscosity measurements are reported in aqueous systems of co- and terpolymers of acrylamide (AM), N-n-alkylacrylamide (C10, C12, and C14 alkyl groups), and acrylic acid (AA) with added anionic surfactant sodium dodecyl sulfate (SDS). The results are presented as three-dimensional plots of viscosity vs surfactant concentration and pH at constant shear rate or viscosity vs shear rate and surfactant concentration at constant pH. For terpolymers incorporating AA, a strong viscosity maximum is observed at intermediate pH values (pH 4-6) where the AA groups are partially ionized and at SDS concentrations close to the critical micelle concentration. At high pH, all AA incorporating terpolymer solutions with SDS are strongly shear thinning, but at pH 3-4 the systems of terpolymers with SDS are strongly shear thickening at low shear, followed by a shear-thinning region at high shear. These results are explained in terms of surfactant-mediated network formation with polymer coil expansion and hydrogen bonding between partially ionized AA groups as additional factors.
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) | 0.001 | 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 | 0.001 |
| 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".