Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
A virtually unprecedented exponential burst of activity resulted following the publication, in 1998, of an article by Michael Freeman (Freemantle, M. Chemical & Engineering News, 1998, March 30, 32), which speculated on the role and contribution that ionic liquids (ILs) might make in the future on the development of clean technology. Up until that time only a handful of researchers were routinely engaged in the study of ILs but frenzied activity followed that continues until the present day. Scientists from all disciplines related to Chemistry have now embarked on studies, including theoreticians who are immersed in the aim of improving the "designer role" so that they can tailor ILs to deliver specified properties. This article, whilst not in any sense attempting to be exhaustive, highlights the main features which characterise ILs, presenting these in a form readily assimilated by newcomers to this area of research. An extensive glossary is featured in this article as well as a chronological list which charts the major areas of development. What follows consists of a number of sections briefly describing the role of lLs as solvents, hypergolic fuels, their use in some electrochemical devices such as solar cells and lithium batteries and their use in polymerisation reactions, followed by a concise summary of some of the other roles that they are capable of playing. The role of empirical, volume-based thermodynamics procedures, as well as large scale computational studies on ILs is also highlighted. These developments which are described are remarkable in that they have been achieved in less than a decade and a half although knowledge of these materials has existed for much longer.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it