A scalable robust microporous Al-MOF for post-combustion carbon capture
Bibliographic record
Abstract
Adsorptive separation via scalable and inexpensive adsorbents is now considered among the credible alternative solutions for post-combustion carbon mitigation via selective physisorption of CO2. As industrial gas streams contain many times water vapours, the use of sorbents showing limited detrimental effect of humidity on the working capacity in the operating conditions is considered as a major advantage contributing to lowering the operating costs and/or accelerating the capture process. Here we report on a robust microporous aluminum tetracarboxylate framework, MIL-120(Al)-AP, (MIL and AP refers to Materials from Institute Lavoisier and for Ambient Pressure synthesis, respectively), which possesses high CO2 uptake (1.9 mmol g-1 at 0.1 bar, 298 K) due to a favorable pore architecture combining high density of µ2-OH groups and stacked aromatic rings, close to the performances of the benchmark CO2 physisorbent, CALF-20 (CALF stands for Calgary Frameworks). Advanced in situ synchrotron X-ray diffraction measurement together with GCMC simulations allowed to get deeper insights into the preferential sites that the structure of MIL-120(Al) offers for a favorable CO2 capture, while revealing the importance of the µ2-OH and their accessibility to CO2 for controlling the gas uptakes at low pressure. This supports further the great potential of MIL-120(Al)-AP towards post-combustion capture. Meanwhile, Qst (CO2) value of MIL-120(Al)-AP (44 kJ mol-1) prone to relatively low energy penalty for full regeneration compared to amine-based solutions (90~140 kJ mol-1) and to their stability limitations. Moreover, a phase transition from monoclinic to triclinic occurs due to partial removal of free water molecules, with ca. 40% water molecules still remaining trapped between Al oxo/hydroxo chains, enabling additional interactions with CO2 molecules during adsorption step. Finally, an environmentally friendly ambient pressure green route, relying on the use of inexpensive raw materials, was optimized to prepare the MIL-120(Al)-AP at kg-scale with high yield and high quality. The MOF was further shaped as millimeter (mm)-sized beads with inorganic binders while first evidences of its efficient CO2/N2 separation ability were validated by breakthrough experiments, thus suggesting the high potential of this MOF in a view of integration into an industrial scale CO2 capture process.
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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".