Chemical reaction equilibrium in nanoporous materials: NO dimerization reaction in carbon slit nanopores
Bibliographic record
Abstract
We present a molecular-level simulation study of the effects of confinement on chemical reaction equilibrium in nanoporous materials. We use the reaction ensemble Monte Carlo (RxMC) method to investigate the effects of temperature, nanopore size, bulk pressure, and capillary condensation on the nitric oxide dimerization reaction in a model carbon slit nanopore in equilibrium with a bulk reservoir. In addition to the RxMC simulations, we also utilize the molecular-dynamics method to determine self-diffusion coefficients for confined nonreactive mixtures of nitric oxide monomers and dimers at compositions obtained from the RxMC simulations. We analyze the effects of the temperature, nanopore width, bulk pressure, and capillary condensation on the reaction equilibrium with respect to the reaction conversion, fluid structure, and self-diffusion coefficients. We show that the influence of the temperature, nanopore size, and capillary condensation on the confined reaction equilibrium is quite dramatic while the effect of the bulk pressure on the reaction equilibrium in the carbon slit nanopore is only moderate. This work is an extension of previous work by Turner et al. [J. Chem. Phys. 114, 1851 (2001)] on the confined reactive nitric oxide system.
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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 | 0.001 | 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 | 0.001 | 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 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".