Study and Comparison of the Thermomechanical Response of Geopolymeric and Conventional Concretes
Bibliographic record
Abstract
Geopolymers are a class of inorganic synthetic materials that in recent years have received extensive interest of the scientific community, mainly due to the variety of applications in which they can be used.The synthesis of these materials is based on a chemical process called geopolymerization, which consists of the alkaline activation of amorphous alumina and silica oxides present in many natural raw materials and industrial solid waste.Therefore, the present work proposes the use of inorganic mining residues (mine tailings) from gold mining in the southern region of Peru, for the manufacture of geopolymeric concrete.The first part of the research focused on the physical, structural and microstructural characterization of the raw material (fine sand and mining tailings), then the volumetric matrix of mixtures for five types of geopolymer concrete was determined.Cylindrical samples of 20 mm diameter and 40 mm high geopolymeric concrete were manufactured, at the same time conventional Portland cement concrete was manufactured for comparison purposes.All materials were mechanically characterized by uniaxial compression tests at variable temperatures (from room temperature to 600 ºC), and they were also microstructurally characterized before and after mechanical tests.The main microstructural mechanisms responsible for the fracture and plastic deformation of geopolymeric and conventional Portland cement concretes have been determined.
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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) | 0.002 | 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".