Preparation of Ca(<scp>OH</scp>)<sub>2</sub> nanoparticles by impinging stream reaction precipitation method
Bibliographic record
Abstract
Abstract In this paper, Ca(OH)2 nanoparticles are prepared by impinging stream co‐precipitation method. The process of preparing nanoparticles by impinging stream is optimized. The influence of process variable, such as dispersant type, dispersant dosage, circulating flow rate, reactant concentration ratio of OH− and Ca2+, reaction temperature and circulation time, on the particle size of Ca(OH)2 nanoparticle are investigated. The results show that the concentration ratio of reactants has a significant effect on the size of Ca(OH)2 nanoparticles. The optimal process conditions are obtained by single factor experiment, PEG6000, 3.3% dispersant dosage, Q = 1000 L · h−1, C = 1.88, T = 46.68°C and t = 60 min. The average particle size of Ca(OH)2 nanoparticles prepared under these conditions is 107.67 nm. According to the microstructure analysis, the prepared Ca(OH)2 nanoparticles samples have high purity and a good crystal structure. The powder dispersed with a marked hexagonal crystal shape and good thermal decomposition.
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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".