Surfactant Assisted Synthesis of Homogeneous Calcium Based CO2 Sorbent at Room Temperature
Bibliographic record
Abstract
Calcium oxide (CaO) sorbents have been recently used for removal of CO2 gases in fossil fuel-fired power plant. However, there are some limitations of CaO in CO2 capturing such as rapid loss of activity during the capture cycles, which is a result of sintering, attrition, and consequent elutriation. Therefore, this paper has demonstrated a novel synthesis method to produce CaO at room temperature to avoid abovementioned drawbacks. In addition, introduction of ionic surfactant of sodium dodecyl sulfate to the CaO formation solution has shown a positive result of formation of homogeneous spherical particle with a mean Z-average diameter of 345.2 nm and polydispersion index (PDI) of 0.335 by dynamical light scattering measurement. Subjected to a high calcination temperature of 1200oC, developed CaO is able to maintain a CO2 uptake capacity of 0.1025 gCO2/gsorbent under 30 minutes of carbonation time. Despite its lower CO2 uptake capacity compared to maximum theoretical limit of 0.78 gCO2/gsorbent, CaO particles is able to withstand a high calcination temperature of 1200oC and reported a particle size distribution ranged from 0.4 - 1.2 µm after calcination which is just slightly larger than fresh developed CaO. Given that such small narrow distributed size of CaO, developed CaO at room temperature is good for packed-bed reactor in calcium looping processes and more studies are required to find a suitable support for fluidized bed reactor type. This successful synthesis story of CaO particle at room temperature has unraveled the possibility to develop nanosized CaO at room temperature in order to achieve high CO2 uptake capacity while enjoying its superior thermal stability over multiple carbonation/calcination cycles.
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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 | 0.000 | 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".