A single-ligand ultra-microporous MOF for precombustion CO <sub>2</sub> capture and hydrogen purification
Bibliographic record
Abstract
Metal organic frameworks (MOFs) built from a single small ligand typically have high stability, are rigid, and have syntheses that are often simple and easily scalable. However, they are normally ultra-microporous and do not have large surface areas amenable to gas separation applications. We report an ultra-microporous (3.5 and 4.8 Å pores) Ni-(4-pyridylcarboxylate)2 with a cubic framework that exhibits exceptionally high CO2/H2 selectivities (285 for 20:80 and 230 for 40:60 mixtures at 10 bar, 40°C) and working capacities (3.95 mmol/g), making it suitable for hydrogen purification under typical precombustion CO2 capture conditions (1- to 10-bar pressure swing). It exhibits facile CO2 adsorption-desorption cycling and has CO2 self-diffusivities of ~3 × 10(-9) m(2)/s, which is two orders higher than that of zeolite 13X and comparable to other top-performing MOFs for this application. Simulations reveal a high density of binding sites that allow for favorable CO2-CO2 interactions and large cooperative binding energies. Ultra-micropores generated by a small ligand ensures hydrolytic, hydrostatic stabilities, shelf life, and stability toward humid gas streams.
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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".