Evaluation of the Stability of Diamine-Appended Mg<sub>2</sub>(dobpdc) Frameworks to Sulfur Dioxide
Bibliographic record
Abstract
Diamine-appended Mg 2 (dobpdc) (dobpdc 4– = 4,4′-dioxidobiphenyl-3,3′-dicarboxylate) metal–organic frameworks are a promising class of CO 2 adsorbents, although their stability to SO 2 ─a trace component of industrially relevant exhaust streams─remains largely untested. Here, we investigate the impact of SO 2 on the stability and CO 2 capture performance of dmpn–Mg 2 (dobpdc) (dmpn = 2,2-dimethyl-1,3-propanediamine), a candidate material for carbon capture from coal flue gas. Using SO 2 breakthrough experiments and CO 2 isobar measurements, we find that the material retains 91% of its CO 2 capacity after saturation with a wet simulated flue gas containing representative levels of CO 2 and SO 2, highlighting the robustness of this framework to SO 2 under realistic CO 2 capture conditions. Initial SO 2 cycling experiments suggest dmpn–Mg 2 (dobpdc) may achieve a stable operating capacity in the presence of SO 2 after initial passivation. Evaluation of several other diamine–Mg 2 (dobpdc) variants reveals that those with primary, primary (1°,1°) diamines, including dmpn–Mg 2 (dobpdc), are more robust to humid SO 2 than those featuring primary, secondary (1°,2°) or primary, tertiary (1°,3°) diamines. Based on the solid-state 15 N NMR spectra and density functional theory calculations, we find that under humid conditions, SO 2 reacts with the metal-bound primary amine in 1°,2° and 1°,3° diamine-appended Mg 2 (dobpdc) to form a metal-bound bisulfite species that is charge balanced by a primary ammonium cation, thereby facilitating material degradation. In contrast, humid SO 2 reacts with the free end of 1°,1° diamines to form ammonium bisulfite, leaving the metal–diamine bond intact. This structure–property relationship can be used to guide further optimization of these materials for CO 2 capture applications.
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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".