Properties and Hydration Mechanism of Autoclaved Aerated Concrete Containing Coal Gangue and Fly Ash
Bibliographic record
Abstract
The coal gangue (CG) that occupies 15%-20% of coal outputs per year is produced from mining and washing in China at an annual increasing rate of 1.5-2.0t.The existence of CG not only occupies land, but also brings about hidden dangers to the surrounding safety and environment.However, CG is rich in clay minerals and carbon, which can be used for mine filling, construction material preparation, thermal power plant generation, etc. [1-6].The main phases of CG are composed of minerals such as feldspar and quartz, exhibiting weak gelling properties.When its Si-O and Al-O bonds acquire external energy (through calcination or spontaneous combustion), a lattice distortion occurs, so that the original crystal structure is destroyed, and Si-O bond and Al-O bond are broken, thus exciting the gelling activity of CG.Fly ash (FA) refers to the dust and furnace bottom slag collected from the flue gas of coal-fired (CG, slime) boilers.China is one of the few countries in the world using the coal as its main energy source.In the past decade, with China's power industry developing rapidly, the total number of coal-fired generating units has continued to expand, and more than half of the coal resources in China have been consumed, resulting in the increase of FA year by year.During the 13th Five-Year Plan period, China's comprehensive utilization rate of FA
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 | 0.001 | 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".