Bibliographic record
Abstract
The use of different nanoparticles as seeding agents for geopolymeric binders was studied to determine the relations between the type of seeds and the geopolymers setting time, structural reorganization, compressive strength and durability. The hypothesis that seeds can act as templates for the reorganization of metakaoline based geopolymers was tested using zeolites with different crystal structures and chemistry, silica and alumina. The strain induced by high energy ball milling on the nanoparticles was determined by X-ray diffraction and by spectroscopic techniques. The effects of microstrains in the seeds on the geopolymeric reaction kinetics and products were investigated. FTIR and X-ray diffraction provided the short order and long order information needed to characterize the structural reorganization of the geopolymer. SEM imaging was adopted to study the effect of the seeds on the microstructure, in particular the nature of the geopolymer product (dense particulates or homogeneous gel). The fresh and hardened properties of the geopolymers were studied and correlated with the structure and microstructure of the geopolymers. The properties of the seeded geopolymers are explained in terms of the possible interactions between the seeds surface sites and the forming geopolymer matrix. The seeds had no effects during the first hours of reaction, but they affected the properties of the geopolymer at longer time. The zeolites seeds showed the most pronounced effects on the structural reorganization and compressive strength of the geopolymers.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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".