Physico-Chemical and Mineralogical Characterizations of Two Togolese Clays for Geopolymer Synthesis
Bibliographic record
Abstract
Geopolymers are an alternative to Portland cement, well known for their contribution to greenhouse gas emissions. Finding materials that can validly replace Portland cement is a challenge. It is in this logic that this work was undertaken with the objective of characterizing two local clay resources of Togo as raw materials for geopolymers. The physico-chemical properties of these clays were determined by characterization using X-ray diffraction (XRD), Fourier transform infrared (FTIR), thermogravimetric (TGA) and elemental analysis (ICP-OES). The results show that these clays contain kaolinite and therefore can be used in the formulation of geopolymers. The characterized clays underwent heat treatments transforming the crystalline phases into more reactive amorphous phases and then were activated by an alkaline solution in order to formulate the geopolymer materials. These elaborated materials were analyzed by Fourier transform infrared to identify the types of bonds formed. The results of these analyses show that these two local clays are well suited to be used in synthesizing geopolymers. Our future work will focus on the constraints of consolidation as well as the mechanical properties of these geopolymer materials.
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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".