Bibliographic record
Abstract
Sustainability awareness in the building industry has increased in recent years, and several initiatives have been developed. One of the areas gaining attention recently is the application of phase change materials (PCMs) in concrete. PCMs are materials capable of storing and releasing energy based on the temperature of the environment in which they are situated. This capability makes them provide heat during cold times, and absorb heat when the temperature is higher. As concrete is the most used building material in the world, the use of PCMs in concrete will be a great way to widen the application of PCMs. However, as the composition of concrete determines its properties; hence, the use of PCM in concrete can be detrimental to the properties of concrete. Some of the negative effects on the properties of concrete include reduced mechanical properties and corrosion of reinforcements. In addition, PCMs suitable for concrete are not readily available in the market, and extremely expensive when available. Also, lack of long-term data on the effect of PCM on concrete's durability has discouraged stakeholders to accept the use of PCMs in concrete. This paper explored the current challenges faced by the application of PCMs in concrete which, and possible opportunities that will open more pathway for extensive research and applications of PCM in concrete. It was concluded that the use of right type and proportion of PCM in concrete can result in similar strength to those of control samples. Also, certain methods of incorporating PCMs into the concrete were found to be more effective. Therefore, it is imperative that building engineers carry out initial tests to determine the most appropriate incorporation method to be used. Finally, huge energy savings can be achieved through the use of PCM in concrete without any significant reduction in mechanical strength.
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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.006 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".