Determination of the adsorption isotherms and transport diffusivities of gases in mixtures inside zeolitic crystals using Infra-Red Micro-imaging
Bibliographic record
Abstract
Different regions of Infra-Red (IR) light absorption by guest molecules inside a zeolitic crystal are measured and quantified to determine binary adsorption isotherms and transport diffusivities. This has been achieved using a vacuum capable setup which includes an Infra-Red Microscope (IRM) and Fourier Transform Infra-Red (FTIR) Spectrometer. By utilizing IR light and FTIR spectroscopy, this method can be used to describe the behavior of low concentrations of relatively fast molecules inside zeolitic crystals as an alternative to chromatographic pulse methods. To demonstrate the capabilities of this method, binary adsorption isotherms and transport diffusivities of CO 2 in mixtures composed of CO 2 and N 2 inside silicalite have been determined. From the fundamental measurements determined using this method, complex gas separation processes such as swing adsorption and multi stage membrane systems can be designed for novel zeolite materials. This method can also be used to develop models for complex adsorption and diffusion systems, and validate sophisticated molecular simulation models. •IR microimaging with static gas dosing system for measuring transient uptake, diffusion and chemical reactions of gases and their mixtures in individual crystals or particles of nanoporous materials •Using giant crystals the setup allows to study adsorption and transport of single components and mixtures in nanoporous materials also for fast diffusing guest molecules
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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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".