Uncovering the Dynamic CO<sub>2</sub> Gas Uptake Behavior of CALF‐20 (Zn) under Varying Conditions via Positronium Lifetime Analysis
Bibliographic record
Abstract
Abstract Carbon dioxide (CO 2 ) is a major greenhouse gas contributing to global warming. Adsorption in porous sorbents offers a promising method for CO 2 capture and storage. The zinc‐triazole‐oxalate‐based Calgary framework 20 (CALF‐20) demonstrates high CO 2 capacity, low H 2 O affinity, and low adsorption heat, enabling energy‐efficient and stable performance over multiple cycles. This study examines CO 2 adsorption mechanism in CALF‐20 using positron annihilation lifetime spectroscopy (PALS), in situ powder X‐ray diffraction (PXRD), and gas adsorption experiments under varying temperatures and humidity levels. Variable‐temperature PALS experiments demonstrate that CO₂ molecules are spatially localized within the CALF‐20 cages, leaving temperature‐ and pressure‐dependent gaps. CO 2 begins at cage centers, forming 1D chains, and ultimately adheres to pore walls. Interestingly, positronium intensity correlates with the Langmuir‐Freundlich isotherm, reflecting gas uptake behavior. Moreover, under pure relative humidity (RH), water molecules form isolated clusters or small oligomers at low RH, transitioning to hydrogen‐bonded networks above 35 %RH, significantly altering free volumes. In humid CO₂ conditions, competitive interactions arise: CO₂ initially disrupts water propagation, but higher RH leads to extensive water networks filling the framework. The synergy between in situ‐PALS, in situ‐PXRD, and gas adsorption techniques provides comprehensive insights into CALF‐20′s potential for efficient CO 2 capture under varying 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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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".