Bibliographic record
Abstract
The feasibility of using carbon dioxide as feedstock in precast concrete production is studied. Carbon dioxide reacts with calcium compounds in concrete, producing solid calcium carbonates in binding matrix. Two typical precast products are examined for their capacity to store carbon dioxide during the production. They are concrete blocks and fiber-cement panels. The two products are currently mass produced and cured by steam. Carbon dioxide can be used to replace steam in curing process to accelerate early strength, improve the long-term durability and reduce energy and emission. For a reaction within a 24-hour process window, the theoretical maximum possible carbon uptake in concrete is found to be 29% based on cement mass in the product. To reach the maximum uptake, a special process is developed to promote the reaction efficiency to 60-80% in 4-hour carbon dioxide curing and improve the resistance to freeze-thaw cycling and sulfate ion attack. The process is also optimized to meet the project target of $10/tCO2 in carbon utilization. By the use of self-concentrating absorption technology, high purity CO2 can be produced at a price below $40/t. With low cost CO2 capture and utilization technologies, it is feasible to establish a network for carbon capture and utilization at the vicinity of carbon sources. If all block produces and panel producers in United States could adopt carbon dioxide process in their production in place of steam, carbon utilization in these two markets alone could consume more than 2 Mt CO2/year. This capture and utilization process can be extended to more precast products and will continue for years to come.
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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 | 0.001 | 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".