Effect of geopolymer cement on microstructure, compressive strength and sulphuric acid resistance of concrete
Bibliographic record
Abstract
The effect of geopolymer cement on the compressive strength and resistance to sulphuric acid of concrete made with type 10 and type 50E cements was studied. Hydration products and microstructure of various concrete mixtures incorporating geopolymer cement were investigated using X-ray diffraction (XRD), scanning electron microscopy (SEM) and transmitted light microscopy in order to identify the mechanisms underlying the effects of the geopolymer cement on concrete properties. Experimental results indicate that using geopolymer cement as partial replacement for ordinary Portland cement (OPC) effectively improved both the compressive strength and resistance to sulphuric acid. Replacement of 50% OPC by geopolymer cement increased the 28-day compressive strength by about 50% and reduced the mass loss of concrete specimens subjected to eight weeks of immersion in sulphuric acid solutions with pH of 0·3 and 0·6 by 42% and 30%, respectively. The effect of geopolymer cement on the compressive strength and sulphuric acid resistance of concrete made with type 50E cement was less significant than that for concrete made with type 10 cement. Results of XRD, SEM and light microscopy indicate that improvements in compressive strength and sulphuric acid resistance of the geopolymer modified concrete can be mainly attributed to the formation of new hydration products such as calcium–magnesium–aluminium-oxide silicates. A direct relationship between the ability of geopolymer modified concrete specimens to resist sulphuric acid and their normal 28-day compressive strength was found, but varied with the binder used.
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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 | 0.001 |
| 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".