Hydrophilic zeolite sorbents for In‐situ water removal in high temperature processes
Bibliographic record
Abstract
Abstract An attractive approach to reduce anthropogenic emission of carbon dioxide (CO 2 ) would be to valorize it into value‐added products (e.g. alcohols or dimethylether) by chemical recycling. However, in most of these important reactions, water is produced as a byproduct that limits CO 2 conversion thermodynamically and can lead to the deactivation of catalysts. Water removal in sorption‐enhanced reaction process (SERP) would allow the overcoming of these drawbacks and several zeolites (SOD, LTA, and FAU) have been selected to assess their potential to adsorb water in‐situ at high temperatures. This work aims to study the water adsorption capacity and kinetics in a large temperature range of 25–250 °C and evaluate the potential of the selected adsorbents for in‐situ water removal in the reverse water gas shift (RWGS) reaction. For all zeolites, the water uptake showed an important decrease at higher temperatures but the capacity at 250 °C was still significant. While the poor adsorption kinetics of SOD limit its use, FAU‐13X powder gave better results than LTA‐4A, which were confirmed by a more important increase of CO concentration at the exit of the reactor for the RWGS reaction. Transient adsorption data obtained in this study were fitted by a double stretched equation and the kinetic constants were determined. These results are essential to model and design an efficient SERP process and determine the optimal reaction conditions.
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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 | 0.000 | 0.001 |
| 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 | 0.000 | 0.001 |
| 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".