A Diaminopropane-Appended Metal–Organic Framework Enabling Efficient CO<sub>2</sub> Capture from Coal Flue Gas via a Mixed Adsorption Mechanism
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Bibliographic record
Abstract
A new diamine-functionalized metal–organic framework comprised of 2,2-dimethyl-1,3-diaminopropane (dmpn) appended to the Mg 2+ sites lining the channels of Mg 2 (dobpdc) (dobpdc 4– = 4,4′-dioxidobiphenyl-3,3′-dicarboxylate) is characterized for the removal of CO 2 from the flue gas emissions of coal-fired power plants. Unique to members of this promising class of adsorbents, dmpn–Mg 2 (dobpdc) displays facile step-shaped adsorption of CO 2 from coal flue gas at 40 °C and near complete CO 2 desorption upon heating to 100 °C, enabling a high CO 2 working capacity (2.42 mmol/g, 9.1 wt %) with a modest 60 °C temperature swing. Evaluation of the thermodynamic parameters of adsorption for dmpn–Mg 2 (dobpdc) suggests that the narrow temperature swing of its CO 2 adsorption steps is due to the high magnitude of its differential enthalpy of adsorption (Δ h ads = −73 ± 1 kJ/mol), with a larger than expected entropic penalty for CO 2 adsorption (Δ s ads = −204 ± 4 J/mol·K) positioning the step in the optimal range for carbon capture from coal flue gas. In addition, thermogravimetric analysis and breakthrough experiments indicate that, in contrast to many adsorbents, dmpn–Mg 2 (dobpdc) captures CO 2 effectively in the presence of water and can be subjected to 1000 humid adsorption/desorption cycles with minimal degradation. Solid-state 13 C NMR spectra and single-crystal X-ray diffraction structures of the Zn analogue reveal that this material adsorbs CO 2 via formation of both ammonium carbamates and carbamic acid pairs, the latter of which are crystallographically verified for the first time in a porous material. Taken together, these properties render dmpn–Mg 2 (dobpdc) one of the most promising adsorbents for carbon capture applications.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 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 it