Physical Solubility of Total Reduced Sulfurs in Fe-Chelate Aqueous Solutions
Bibliographic record
Abstract
Total reduced sulfurs (TRS) include hydrogen sulfide (H 2 S), methyl mercaptan (methanethiol, CH 3 SH), dimethyl sulfide (CH 3 SCH 3 ) and dimethyl disulfide (CH 3 S 2 CH 3 ) and are referred to as noncondensible gases. They are part of a well-known environmental problem afflicting pulp mills exploiting the Kraft pulp mill process. These sulfur compounds are formed in the Kraft pulping process and come in contact with different waters and liquors, contributing to the odor problems of Kraft mills. Because of their toxic and corrosive characters, they must be removed down to very low concentration levels. The olfactory threshold of TRS for human beings is four orders of magnitudes below the regulated emission level which is approximately 5-10 ppm in Canada and the US, giving rise to strict regulations in order to reduce their emissions from specific sulfate pulp process equipments. Among several approaches proposed to remove or at least reduce these airborne pollutants, the utilization of ferric chelate complex of trans-1,2-cyclohexane diaminetetraacetic acid (CDTA) for the oxidative scrubbing of hydrogen sulfide and methyl mercaptan in Kraft mill streams is beneficial from the standpoints of iron protection against precipitation and oxygen-mediated regenerative oxidation of the ferrous chelate CDTA. The remaining (unreactive) two sulfur-bearing compounds, dimethyl sulfide and dimethyl disulfide undergo only physical absorption in such solutions. The physical solubility of these four compounds in aqueous CDTA-Fe(III) alkaline solutions is therefore a crucial parameter for designing the complete scrubbing-absorption process. The aim of this review is to highlight several aspects related to the solubility of TRS compounds in Fe-chelate aqueous solutions (experimental methods, solubility dependence on temperature, chelate concentration, and solution pH).
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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 | 0.002 | 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".