Cooperative Carbon Dioxide Capture in Diamine-Appended Magnesium–Olsalazine Frameworks
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide Diamine-appended Mg 2 (dobpdc) (dobpdc 4– = 4,4′-dioxidobiphenyl-3,3′-dicarboxylate) metal–organic frameworks have emerged as promising candidates for carbon capture owing to their exceptional CO 2 selectivities, high separation capacities, and step-shaped adsorption profiles, which arise from a unique cooperative adsorption mechanism resulting in the formation of ammonium carbamate chains. Materials appended with primary, secondary -diamines featuring bulky substituents, in particular, exhibit excellent stabilities and CO 2 adsorption properties. However, these frameworks display double-step adsorption behavior arising from steric repulsion between ammonium carbamates, which ultimately results in increased regeneration energies. Herein, we report frameworks of the type diamine–Mg 2 (olz) (olz 4– = ( E )-5,5′-(diazene-1,2-diyl)bis(2-oxidobenzoate)) that feature diverse diamines with bulky substituents and display desirable single-step CO 2 adsorption across a wide range of pressures and temperatures. Analysis of CO 2 adsorption data reveals that the basicity of the pore-dwelling amine─in addition to its steric bulk─is an important factor influencing adsorption step pressure; furthermore, the amine steric bulk is found to be inversely correlated with the degree of cooperativity in CO 2 uptake. One material, ee-2–Mg 2 (olz) (ee-2 = N, N -diethylethylenediamine), adsorbs >90% of the CO 2 from a simulated coal flue stream and exhibits exceptional thermal and oxidative stability over the course of extensive adsorption/desorption cycling, placing it among top-performing adsorbents to date for CO 2 capture from a coal flue gas. Spectroscopic characterization and van der Waals-corrected density functional theory calculations indicate that diamine–Mg 2 (olz) materials capture CO 2 via the formation of ammonium carbamate chains. These results point more broadly to the opportunity for fundamentally advancing materials in this class through judicious design.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".