Development of poly(aspartic acid-<i>co</i>-malic acid) composites for calcium carbonate and sulphate scale inhibition
Bibliographic record
Abstract
Polyaspartic acid (PSI) is suitable for the inhibition of inorganic scale deposition. To enhance its scale inhibition efficiency, PSI was modified by reacting aspartic acid with malic acid (MA) using thermal polycondensation polymerization. This reaction resulted in poly(aspartic acid-co-malic acid) (PSI-co-MA) dual polymer. The structural, chemical and thermal properties of the dual polymers were analysed by using scanning electron microscopy, Fourier transform infrared spectroscopy, X-ray diffraction, differential scanning calorimetry and gel permeation chromatography. The effectiveness of six different molar ratios of PSI-co-MA dual polymer for calcium carbonate and calcium sulphate scale inhibition at laboratory scale batch experiments was evaluated with synthetic brine solution at selected doses of polymer at 65-70°C by the static scale test method. The performance of PSI-co-MA dual polymer for the inhibition of calcium carbonate and calcium sulphate precipitation was compared with that of a PSI single polymer. The PSI-co-MA exhibited excellent ability to control inorganic minerals, with approximately 85.36% calcium carbonate inhibition and 100% calcium sulphate inhibition at a level of 10 mg/L PSI-co-MA, respectively. Therefore, it may be reasonably concluded that PSI-co-MA is a highly effective scale inhibitor for cooling water treatment applications.
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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) | 0.001 | 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 | 0.000 |
| 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".