Exploration of mechanical performance, porous structure, and self-cleaning behavior for hydrothermally cured sustainable cementitious composites containing de-aluminated metakaolin waste and TiO2 nanoparticles
Bibliographic record
Abstract
The main goal behind this research is to produce antimicrobial cementitious composites with acceptable mechanical characteristics based on de-aluminated metakaolin waste (DAK) and commercial titania. Two cementitious blends have been prepared: OPC containing 50%DAK and OPC containing 45%DAK +5% TiO2 NPs. Regarding curing time and cost, these blends were treated under two different curing regimes: normal curing under tap water for up to 28-days at room temperature and hydrothermal curing at various steam pressures of up to 12 bars. Compared with the reference paste (OPC/28days), compressive strength test, phases identification, morphology, textural characteristics, and microbial resistivity test were conducted. It was found that the normal cured cementitious composite containing titania NPs possessed the highest strength (88MPa) compared with the reference (80MPa) and OPC+50%DAK (58MPa). On the other hand, the strength value for cementitious composite modified with TiO2 NPs reached 96 MPa under autoclave curing at 4bars for 8 hrs. and became 61.6 MPa for OPC+50%DAK. XRD and TGA/DTG techniques confirmed the formation of binding hydrates (C-S-Hs, C-A-S-Hs and C-A-Hs) under different curing conditions. SEM/EDX indicated stacked plates, fibers, and rods of C-S-Hs under hydrothermal treatment. N2-adsorption/desorption technique revealed that autoclaving conditions significantly reduced the pore diameter of the prepared blends. Two fungi strains (Mucor-circinelloide and Aspergillus-terreus) and two bacteria strains (Gram Positive-Bacillus subtilis-ATCC6633, Gram negative-K. pneumonia-ATCC13883) were used to conduct a self-cleaning test. According to the agar diffusion test, high inhibition zones were observed for normally cured OPC-50%DAK and OPC-45%DAK-5%TiO2 pastes.
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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) | 0.000 | 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 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".