Esterquat EQ-90 as a green novel collector for effective desilication in magnesite flotation: Adsorption mechanisms and selectivity
Why this work is in the frame
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Bibliographic record
Abstract
This study investigates the selective adsorption behavior and flotation efficacy of the eco-friendly esterquat EQ-90 on quartz and magnesite, leveraging an array of advanced analytical techniques, including micro-flotation tests, Zeta potential analysis, contact angle measurement, FTIR, SEM-EDS, XPS, and TOF-SIMS. Micro-flotation tests demonstrated that EQ-90 achieved a 93.15 % recovery for quartz, while maintaining the magnesite recovery at only 5.26 %. Zeta potential and contact angle analyses confirmed the robust adsorption of EQ-90 on quartz, rendering it hydrophobic, while magnesite exhibited negligible interaction. FTIR, SEM-EDS, and XPS analyses revealed substantial increases in C and N content and significant shifts in binding energies on quartz surfaces post EQ-90 treatment, corroborating the selective adsorption mechanism. TOF-SIMS imagery further validated these findings, showing pronounced EQ-90 concentrations on quartz. This comprehensive analysis underscores EQ-90′s efficacy in selectively adsorbing onto quartz, thereby optimizing its flotation efficiency. The study offers significant insights and a robust foundation for employing EQ-90 in the selective separation of quartz from magnesite, advancing flotation processes in mineral processing.
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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 | 0.001 |
| 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 it