Preparation of high quality Microgranulate CrO<sub>3</sub> based on green process design
Bibliographic record
Abstract
Abstract A mild crystallization process was proposed to prepare chromium trioxide (CrO3) by reaction between K2Cr2O7 and HNO3 aqueous solutions. Through ICP, XRPD, SEM, and EDS analysis, key factors and mechanisms that influenced the preparation of CrO3 were studied. Large spherical particles of CrO3 (d50 ≥ 300 µm) with high purity (CrO3 ≥ 0.99 g/g, K ≤ 2 mg/g) were prepared when the initial concentration of K2Cr2O7 was kept at 80 g/100 mL HNO3, the acid feeding rate and the cooling rate were set at 1 mL · min−1 and 0.1 °C · min−1, respectively, and the direct recovery of Cr6+ was up to more than 95 %. Kinetic analysis indicated that low nucleation rate and high growth rate would favour the increase of CrO3 particle size in this process. As a high‐valued byproduct, Cr(VI)‐free KNO3 was further prepared with the designed crystallization steps. Additionally, green characteristics of the process were also discussed.
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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".