Adsorption dynamics of aromatic and polar volatile organic compounds on metal-organic frameworks
Bibliographic record
Abstract
The study explores the effectiveness of metal-organic frameworks (MOFs) in capturing volatile organic compounds (VOCs). Specifically, it investigates the effect of polarity and aromaticity of VOCs on their adsorption behavior on two MOFs, CuBTC and FeBTC. Cyclic adsorption breakthroughs and isotherms were completed using toluene, 2-methylpyridine, n-hexane, and 2-methyl-2-butanol as adsorbates to assess the frameworks' adsorption and regeneration capabilities. X-ray diffraction, X-ray photoelectron spectroscopy, thermogravimetry analysis, Fourier transform infrared spectroscopy and nitrogen adsorption/desorption isotherm were used to evaluate the MOFs' crystallinity, thermal stability, and surface properties. The results suggest that CuBTC demonstrates superior adsorption capabilities for all tested VOCs, due to its larger surface area and higher crystallinity. However, FeBTC has a broader pore sizes, allowing faster VOC mass transfer rates and accommodating larger molecules, albeit with slightly lower adsorption capacities. Notably, VOCs with polar and aromatic properties, such as 2-methylpyridine, exhibited higher adsorption levels due to increased π-π interactions within the frameworks. However, regeneration of 2-methylpyridine was challenging due to chemisorption, forming strong, irreversible metal–nitrogen coordination bonds. Toluene and 2-methyl-2-bustanol showed similar adsorption capacities and could be effectively regenerated, indicating physisorption mechanisms involving π–π interactions and polar interactions, respectively. N-hexane exhibited the lowest adsorption capacities, relying on weaker van der Waals forces. These results highlight the promising potential of CuBTC and FeBTC in mitigating air pollution. The research also offers valuable insights for tailoring MOFs to contaminants' molecular properties, and advances our understanding of MOF applications in air quality engineering. • CuBTC, FeBTC effectiveness in capture of polar and aromatic VOCs. • Polar/aromatic VOCs were adsorbed by polar and π-π interactions. • CuBTC high adsorption capacity due to high surface area and microporosity. • Effective regeneration was achieved in all selected VOC except 2-methylpyridine. • 2-Methylpyridine was chemically adsorbed on both MOFs.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".