Enhanced methyl green adsorption of ZIF-8 metal-organic framework: Insights from different solvents
Why this work is in the frame
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Bibliographic record
Abstract
This study investigates the effect of solvent type on the structural properties and adsorption performance of the ZIF-8 metal-organic framework for removing various dyes including, methyl green (MG), methylene blue (MB), and methyl orange (MO) from water in acidic and alkaline environments. ZIF-8 samples were synthesized using zinc nitrate, methylimidazole, and three different solvents including, water, methanol, and ethanol under atmospheric pressure and 70 °C. Characterization using BET, XRD, FT-IR, and TGA techniques sheds light on the structural, chemical, and thermal properties of ZIF-8 samples. Among the samples, ZIF-8/M, synthesized using methanol, stands out, demonstrating the high surface area of 2172.7 m2/g, large total pore volume of 1.5412 cm3/g, and high crystallinity of 31.9% with improved thermal stability. Furthermore, ZIF-8/M shows better adsorption performance for methyl green with a removal percentage of 81.9%, 87.1%, and an adsorption capacity of 20.5 mg/g and 21.8 mg/g, in acidic and alkaline environments, respectively. Enhanced dye adsorption of ZIF-8/M is associated with both physical and effective chemical adsorption mechanisms via tuning the environment's acidity.
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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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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 it