Applications of molecular simulations for separation and adsorption in zeolites
Bibliographic record
Abstract
Zeolites are fascinating and versatile materials which are vital for a wide range of industries, due to their unique structural and chemical properties, which are the basis of applications in gas separation, ion exchange, and catalysis. Given their economic impact, there is a powerful incentive for smart design of new materials with enhanced functionalities for maximizing their application performance. This review article intends to summarize the published reports on the applications of molecular simulation in adsorption, separation and diffusion. The theoretical aspects, adsorption thermodynamics, adsorption isotherm were comprehensively studied in relation to the adsorption applications and how the adsorbates' characteristics influence the adsorption. This review comprehensively discusses the theoretical and computational aspects of diffusion of pure components, long chain hydrocarbons or mixture diffusion, including the molecular dynamics simulations and kinetic Monte Carlo. Furthermore, the cation-zeolite-adsorbate interactions are thoroughly examined so as to elucidate the role of cations in zeolites applications and how the cation exchange influences structural dynamics and properties of zeolites. This study also focuses on the role of cations in gas/liquid adsorption and separations.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".