Removal of Sulfur Compounds by a Copper-Based Metal Organic Framework under Ambient Conditions
Bibliographic record
Abstract
A copper-based metal organic framework (MOF-199) was synthesized by a hydrothermal method and was used to remove hydrogen sulfide, ethyl mercaptan, and dimethyl sulfide. Characterizations of the samples before and after desulfurization were carried out by Fourier transform infrared (FTIR) spectroscopy, X-ray diffraction (XRD), and X-ray photoelectron spectroscopy (XPS). The adsorption performance of the prepared sample MOF-199 was evaluated by breakthrough experiments in a fixed-bed reactor. Heat treatment was carried out in nitrogen flow to activate the prepared MOFs. The optimum activation temperature was found to be 180 °C. Evaluation results showed that the breakthrough capacity of MOF-199 for hydrogen sulfide removal increased with the working temperature, whereas the capacity for ethyl mercaptan and dimethyl sulfide removal decreased with the temperature. MOF-199 had the highest breakthrough sulfur capacity for dimethyl sulfide removal (8.48 g of sulfur/100 g of MOF-199). The color of the MOF changed during sulfur capture in all cases, indicating a change in the chemical environment of the copper metal site. Interactions between the unsaturated copper sites in MOFs and the sulfur compounds differed because of the steric effect. A strong interaction was apparent during adsorption of ethyl mercaptan and hydrogen sulfide, which resulted in the formation of various amounts of CuS and serious damage to the MOF structure. The relatively weak interaction with dimethyl sulfide originated from electrostatic force and a weak coordination effect, which led to easy recycling and recovery of MOF-199 by thermal regeneration at 180 °C.
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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) | 0.000 | 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) | 0.007 | 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".