Microstructural characterization of high-performance steel fiber reinforced geopolymer concrete
Bibliographic record
Abstract
Due to growing environmental and economic concerns associated with conventional building materials, research interest gravitates towards the development of novel environmentally friendly materials as alternatives to conventional Portland cement concrete. Geopolymer concrete is a class of novel advanced and sustainable structural materials that hold promise for the future of infrastructure. Its synthesis comprises industrial by-products (fly ash and slag among others) in the role of binder and thus reduces the demand in Portland cement leading to a significant carbon footprint reduction. In the present study a High-Performance Fiber Reinforced Geopolymer Concrete (HPFRGC) is synthesized from first principles and is subsequently characterized, with particular emphasis on its microstructural and mineralogical properties. The study explores the linkage between the microstructure and mineralogy of the precursors, and the properties of the final product. Both fresh and hardened HPFRGC are studied. Experimental results illustrate the correlation between microstructure, mineralogy and final mechanical properties can be used as an indicator of suitability of industrial by-products for geopolymer precursors. The effect of these choices on stability and physical properties of the material is also explored in the study.
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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 | 0.001 | 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".