Fundamental properties and practical applications of ionic liquids: concluding remarks
Bibliographic record
Abstract
The Faraday Discussion on Ionic Liquids: From Fundamental Properties to Practical Applications took place in Cambridge in September 2017. Fundamental understanding of behaviour of liquids in the bulk and at surfaces was the primary emphasis of most of the talks, although applications were the motivation for the selection of many of the research projects. However, the conference almost entirely omitted discussion of the potential role of ionic liquids in green chemistry. Although initial claims of ionic liquids (ILs) being green were overstated, the search for green ionic liquids is still very much a worthwhile endeavour. Some confusion in the field has been caused by an overemphasis on the environmental impacts of ILs themselves, despite the fact that the manufacture of ILs causes greater impacts. Additional confusion has arisen from the mistaken use of the ready biodegradability test as an indicator for ultimate degradation. Because some ILs contain cores that are highly resistant to degradation, the ready biodegradability test can give a false positive result. The author offers suggestions as to how to tackle the problem of searching for greener ILs, including a greater focus on the impacts of the synthetic pathways of relevant ions. The final decision of whether an IL is green can only come from an application-specific life cycle assessment of a product or process using the IL compared to the same product/process using competing liquids.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.005 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.004 |
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".