Capacitive Deionization for Selective Extraction of Lithium from Aqueous Solutions
Bibliographic record
Abstract
The paper deals with extraction of lithium by means of two capacitive deionization systems: one composed of lithium selective electrode and second with electrode wrapped with Li-selective membrane. In the case of the first system, hybrid electrodes where obtained by mixing λ-MnO2sorbent with activated carbon .The best Li-capacity was determined for electrode with 20 wt.-% of manganese oxide. For larger amounts of λ-MnO2 the electrode capacity decreased significantly. The second system was composed of carbon electrodes wrapped with ion-exchange membranes. The lithium selective membranes were synthesized by plasma induced interpolymerization of (meth)acrylic monomersinpores of Celgard 2400 support. Two functional monomers, poly(di(ethylene glycol)methyl ether methacrylate) and poly(glycidylmethacylate modified with hydroxymethyl-12-crown-4) were copolymerized with acrylic acid. It was found that the extraction of lithium chloride was the best for membrane caring copolymers of acrylic acid and glycidyl methacrylate modified with crown ether, andit was better than for membranes with sole poly(acrylic acid).
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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 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".