Decontamination of water co-polluted by copper, toluene and tetrahydrofuran using lauric acid
Bibliographic record
Abstract
Abstract Co-contamination by organic solvents (e.g., toluene and tetrahydrofuran) and metal ions (e.g., Cu2+) is common in industrial wastewater and in industrial sites. This manuscript describes the separation of THF from water in the absence of copper ions, as well as the treatment of water co-polluted with either THF and copper, or toluene and copper. Tetrahydrofuran (THF) and water are freely miscible in the absence of lauric acid. Lauric acid separates the two solvents, as demonstrated by proton nuclear magnetic resonance (1H NMR) and Attenuated Total Reflection-Fourier Transform Infrared Spectroscopy (ATR-FTIR). The purity of the water phase separated from 3:7 (v/v) THF:water mixtures using 1 M lauric acid is ≈87%v/v. Synchrotron small angle X-Ray scattering (SAXS) indicates that lauric acid forms reverse micelles in THF, which swell in the presence of water (to host water in their interior) and ultimately lead to two free phases: 1) THF-rich and 2) water-rich. Deprotonated lauric acid (laurate ions) also induces the migration of Cu2+ ions in either THF (following separation from water) or in toluene (immiscible in water), enabling their removal from water. Laurate ions and copper ions likely interact through physical interactions (e.g., electrostatic interactions) rather than chemical bonds, as shown by ATR-FTIR. Inductively coupled plasma—optical emission spectrometry (ICP-OES) demonstrates up to 60% removal of Cu2+ ions from water co-polluted by CuSO4 or CuCl2 and toluene. While lauric acid emulsifies water and toluene in the absence of copper ions, copper salts destabilize emulsions. This is beneficial, to avoid that copper ions are re-entrained in the water phase alongside with toluene, following their migration in the toluene phase. The effect of copper ions on emulsion stability is explained based on the decreased interfacial activity and compressional rigidity of interfacial films, probed using a Langmuir trough. In wastewater treatment, lauric acid (a powder) can be mixed directly in the polluted water. In the context of groundwater remediation, lauric acid can be solubilized in canola oil to enable its injection to treat aquifers co-polluted by organic solvents and Cu2+. In this application, injectable filters obtained by injecting cationic hydroxyethylcellulose (HEC +) would impede the flow of toluene and copper ions partitioned in it, protecting downstream receptors. Co-contaminants can be subsequently extracted upstream of the filters (using pumping wells), to enable their simultaneous removal from aquifers.
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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) | 0.001 | 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".