Novel amino acid ionic liquids prepared via one‐step lactam hydrolysis for the highly efficient capture of <scp>CO<sub>2</sub></scp>
Bibliographic record
Abstract
Abstract This article proposes for the first time the preparation of a series of amino acid ionic liquids (AAILs) via one‐step hydrolysis of cheap lactams for the capture of CO2. The structures of the prepared AAILs are confirmed using NMR, FTIR, and ESI‐MS, and their physical properties are also determined. It is found that these AAILs are reversible CO2 absorbents with very high absorption capacities (0.15 to 0.18 g·g−1 at 313.2 K and 1.0 bar), better than almost all task‐specific ionic liquids reported in literatures. The absorption mechanism is also elucidated to be a combination of 1:1 and 2:1 stoichiometric reaction of AAILs with CO2 from NMR, FTIR, reaction equilibrium thermodynamical modeling and quantum calculations. The AAILs have the advantages of simple synthesis, high yield, and using available cheap raw materials. It is believed that this kind of AAILs have great potentials to be used as efficient CO2 absorbents.
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 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) | 0.000 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".