Use of molecular simulation to design modification of a chromium‐based <scp>MOF</scp> for adsorptive removal of inhalation anaesthetic agents
Bibliographic record
Abstract
Abstract MIL‐101‐Cr‐X (X = OH − , F − ) has been reported to be the most suitable material so far for adsorptive removal of inhalation anaesthetic agents (IAA) sevoflurane and desflurane at the working conditions in hospital operation rooms. To further enhance its affinity and uptake capacity towards IAA, several structural modifications were proposed, and their isotherms were predicted using our molecular simulation approach adopted in our previous publication for the case of the pristine MIL‐101‐Cr (X = F − , OH − ) structure. The proposed modifications include (1) grafting the metal‐cluster site with coordinated NH 3 ligands to produce MIL‐101‐Cr@NH 3 (X = F − , OH − ), (2) anion exchange of the fluorine atom bonded to chromium with chlorine to synthesize MIL‐101‐Cr (X = Cl − ), and (3) functionalization of the benzene rings of the ligand linkers in the MOFs with amino‐ and nitro‐ groups in order to form NH 2 ‐MIL‐101‐Cr (X = Cl − ) and NO 2 ‐MIL‐101‐Cr (X = Cl), respectively. Simulated adsorption isotherms of IAA on these modifications were verified by the experimental results using the standard volumetric technique and they clearly demonstrated that MIL‐101‐Cr@NH 3 (X = F − , OH − ) possesses the highest equilibrium capacity for IAA. This observation can be attributed to the electron‐transfer contribution of the coordinated ammonium molecules to the unsaturated coordinated sites of the MOF while doing away with steric hindrance inside the pore cages. The new compound can significantly enhance the economy of adsorptive removal of IAA from vented gas mixtures.
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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) | 0.000 | 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".