State-of-the-art report on use of nano-materials in concrete
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Nanotechnology application to concrete presents an innovative approach to improve concrete properties based on the ability to manipulate the cementitious material at an atomic scale. This paper presents a review of the nano-materials that have been used in concrete. The literature survey revealed that four nano-materials are most often used to modify concrete properties; these include nano-silica (nano-SiO2), nano-titanium dioxide (nano-TiO2), carbon nano-tubes (CNTs) and carbon nano-fibres (CNFs). All of these four nano-materials have shown improvement in many concrete properties. Both nano-TiO2 and nano-SiO2 reduce bleeding and segregation, and improve mechanical and transport properties. CNFs and CNTs tend to adversely affect the fresh properties due to agglomerations, which are overcome when a surfactant or ultrasonic mixer is used. However, both CNFs and CNTs significantly improve the mechanical properties of concrete. This paper also discusses how concrete durability is improved when nano-materials are added to concrete. In addition, this paper identifies several research needs based on the gaps in the current state of knowledge on using nano-materials in concrete.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 it