Chemical, thermal and mineralogical characteristics of concretes in stabilized soil with sugar cane molasses
Bibliographic record
Abstract
Abstract This paper scrutinizes MEDDRX, TGA, IR, DTA’s analyses performed on stabilized soil concrete with sugar cane molasses. It is important to underline that the soil remains the principal material in house construction in the Republic of the Congo. The use of sugar cane molasses as a stabilizing to bricks and soil roads appears as an alternative solution to valorise this agro-industrial by-product; moreover, sugar cane molasses has led to obtain soil-made materials with highly enhanced mechanical properties. Therefore, this study has enabled to determine the evolution of induced structure by the presence of molasses within the soil matrix. As a consequence, the final results clearly indicate that the molasses brings no alteration to kaolinite’s structure. However, molasses spreads on basal and lateral surface of clay, and sugar groupings establish physical interactions with silanol and aluminol groupings of clay’s external surface. Thereby, the interaction between molasses and clay of soil is essentially physical. Molasses’ presence within stabilized soil matrix is ascertained by the appearance of thermal peaks attributed to sucrose pyrolysis, whereas the appearance of absorption bands is attributed to aromatic compounds responsible of the colouring. The thermal decomposition of stabilized soil with molasses takes place following four thermal peaks: 150-200 °C, 300 °C, 480-500 °C, and 700 °C.
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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".