Chromium(III) Isolation from Acid Extract of Tannery Sludge
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Bibliographic record
Abstract
High concentrations of Al, Fe, Ca, Mg, and Zn in the tanning agent are detrimental to the properties of tanned leather. To facilitate removal of chromium from the tannery sludge and recycle to the tanning agent, these five metals must first be removed as much as possible from the acid extract of tannery sludge. This work proposes a three-step process for the separation of Cr(III) from these interfering element metals present in the acid extract (leachate) of tannery sludge. In step 1, the leachate was appropriately diluted, and the Al was efficiently removed by precipitation in the form of hydroxide at 21°C and adjusting the pH between 4.6 and 4.8. The optimum dilution ratio for the tannery sludge leachate at a solids concentration 80 (g/L) was 6.3. Under the above operating conditions, 50–80% of Al, 30–40% of Fe, and 22–40% of Cr were removed, and the discrimination ratio between Al and Cr was between 2.0 and 2.2, depending on the pH. In step 2, the Al and Fe that remained in the filtrate after step 1 were further reduced at 21°C by reacting with an organic agent cupferron (Y). The precipitation reactions of cupferron with all of metals were completed in 10 min. The optimum pH for the removal of Al, Fe, and Zn was between 3 and 4.83. The optimum molar ratio of cupferron to the sum of Al, Fe, and Zn was between 2.78 and 4. Under these operating conditions, about 90% of Fe, 80% of Al, 70% of Zn, and 7% of Cr were precipitated. During step 2, most of Fe, Al, and Zn originally present in the tannery leachate were separated from Cr(III), Ca, and Mg. In step 3, the Ca and Mg left in the filtrate after step 2 were separated from Cr(III) by adjusting the pH of the filtrate to 7.0 with the solution of sodium hydroxide at 21°C. The removal efficiency of Cr(III), Ca, and Mg were 99.6, 13.7, and 4.9%. After step 3, the molar percentages of Al, Ca, Cr, Fe, Mg, and Zn in the precipitate formed at pH 7.0 and 21°C in a typical case were 2.94, 0.055, 95.649, 0.302, 1.013, and 0.041, respectively. The overall removal efficiencies of the targeted metals in a typical case were as follows: Al, 77%; Fe, 84.4%; Ca, 99.2%; Mg, 98.5%; and Zn, 61%. About 42% of Cr(III) in total (step 1 + step 2) was removed as precipitates with other metals. The hydroxide precipitates of Cr(III) (from step 1) can be recovered efficiently by the conventional oxidation method. The spent cupferrons as cupferrates can be recovered and recycled. The separation process was simple since it does not involve the oxidation of Cr(III) and the use of ionic exchange resin.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 it