Preparation of ferric oxide powders by ultrasonic‐assisted impinging stream reaction
Bibliographic record
Abstract
Abstract In this paper, Fe 3 O 4 powder was prepared by the chemical precipitation method using impinging stream technology. The influences of feed flow rate, L / D , reactant concentration, ratio of iron ion concentration, reaction temperature, and impact time on the size and distribution of particles were investigated by the orthogonal experiment method. The microstructure and morphology of Fe 3 O 4 powders were characterized by scanning electron microscopy, X‐ray diffractometer, and granulometer. The results showed that when ratio of iron ion concentration c (Fe 2+ ): c (Fe 3+ ) = 0.75, reactant concentration c (Fe 3+ ) = 0.4 mol · L −1 , feed flow rate Q = 800 L · h −1 , L / D = 3, reaction temperature T = 20°C, impact time t = 50 min, the prepared Fe 3 O 4 had an average particle size of 1.815 μm and the most uniform distribution. The influence of ultrasonic enhancement on the mixing process and powder preparation in an impinging stream reactor was investigated. The size and distribution of the powders were significantly affected by ultrasonic enhancement. With the increase in ultrasonic power, the particle size of the powders decreased and the distribution became narrower. The particle size was reduced by 68.78%, and the particle distribution range was narrowed by 84.34% under ultrasound enhancement. This study promised the effective utilization of ultrasonic cavitation in the optimization of experimental equipment and the preparation of ultrafine powder, which provides a basis for process optimization of powder preparation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".