Bibliographic record
Abstract
Abstract Reduced use of volatile organic compounds as solvents in chemical processes is highly desirable from a sustainability point of view. This is because many conventional organic solvents have high vapor pressures, which can lead to hazards including low flash points, high flammability, toxicity, and atmospheric pollution. In order to make decisions regarding solvent use in a chemical process, it is important to evaluate the options available both from a chemical point of view and also with regards to the environment and safety. The typical physicochemical properties and parameters that need to be considered are briefly described. An overview of the environmental, health, and safety criteria used to assess all solvent systems (traditional and environmentally friendly) is provided. The concept of life‐cycle assessment when applied to solvents in either a quantitative or a qualitative way is introduced. Guidance provided by industrial users of solvents, especially the pharmaceutical industry, is highlighted. A range of sustainable solvent systems are described in this chapter. These include: water, supercritical carbon dioxide, carbon dioxide‐expanded liquids, solvents of switchable polarity and volatility, room temperature ionic liquids and deep eutectic solvents, bio‐derived solvents (e.g., 2‐methyltetrahydrofuran and glycerol), and solvent‐free systems. Their advantages, disadvantages, and properties are discussed, and examples of chemistries performed in them are given. Biphasic systems based on sustainable solvents and aimed at allowing their more efficient use and potential catalyst recycling are described. These include water/bio‐derived solvent, supercritical carbon dioxide/water, and supercritical carbon dioxide/ionic liquid systems.
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.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.020 | 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".