Effects of polycarboxylate superplasticizers with different functional groups on the adsorption behavior and rheology of cement paste containing montmorillonite
Bibliographic record
Abstract
The dispersing effectiveness of polycarboxylate superplasticizer (PCE) in cement paste is dramatically reduced as a result of the sorption of PCE by montmorillonite (MMT) clay. To improve the dispersing effectiveness of PCE in MMT-containing cement paste, three PCEswere synthesized by copolymerizing isopentenyl polyoxyethylene ether (TPEG) with trans-2-butenedioic acid (FA) (FA-TPEG), FA and methacryloxyethyltrimethyl ammonium chloride (FA-DMC-TPEG), FA and sodium p-styrene sulfonate (FA-SSS-TPEG), respectively. Their molecular structures were characterized by gel permeation chromatography, specific charge density , Fourier transform infrared spectrum, and 1H nuclear magnetic resonance spectroscopy. X-ray diffraction and adsorption analysis were used to reveal the interactions between PCEs and MMT, and their dispersing performance in cement-MMT paste was evaluated using mini-cone and rheology measurements.. Results indicate that the difference in flowability caused by PCEs is primarily attributed to their different affinity for MMT in cement paste. Among them,, FA-SSS-TPEG showed excellent flowability due to its high affinity for cement particles and strong steric hindrance effect.
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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) | 0.000 | 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".