The importance of using silica fume and pumice powder in cement-based fiber composites, with a focus on microstructural and mechanical assessments
Why this work is in the frame
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Bibliographic record
Abstract
This study aims to evaluate the combined effect of pumice powder and silica fume, used as a binary supplementary cementitious material (SCM) blend, on the microstructural, mechanical, and pull-out properties of steel fiber-reinforced cementitious composites. Concrete cylinders and prisms were prepared with varying steel fiber contents (0.5–1.5 %) and binary SCMs (10 % silica fume combined with 10 % or 20 % pumice powder). Experimental tests were conducted to determine compressive strength, tensile strength, flexural strength, modulus of elasticity, Poisson’s ratio, and bond behavior through steel rebar pull-out tests. Microstructural analyses included FTIR, XRD, TG/DTG, and field emission scanning electron microscopy (FESEM). The results demonstrated that the optimal mixture, containing 20 % pumice powder and 10 % silica fume, significantly enhanced the compressive strength by up to 120 %, the modulus of elasticity by 17 %, the flexural strength by up to 68 %, and the pull-out resistance by up to 73 % compared to the control sample. Additionally, this blend improved the pore-filling effect, promoted the consumption of portlandite, and facilitated the formation of C-S-H/C-A-S-H phases, thereby confirming the positive effect of pumice powder and silica fume on the performance of steel fiber-reinforced cementitious composites.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 it