2D and 3D Metal–Organic Framework at the Oil/Water Interface: A Case Study of Copper Benzenedicarboxylate
Bibliographic record
Abstract
Abstract Metal–organic framework nanosheets (MOF NSs) have drawn a lot of attention lately; however, the interfacial behavior of these 2D MOFs has rarely been investigated. Here, the partition and distribution of 2D NS and 3D nanoparticle (NP) of copper benzenedicarboxylate (CuBDC) at the oil/water interface are imaged by cryo‐scanning electron microscopy. A layer of ≈20 nm NS‐CuBDC is detected with a lateral orientation along the interface, which is attributed to the existence of relatively hydrophobic planes and hydrophilic edges in NS‐CuBDC. The highly hydrophilic CuBDC localizes along the interface within the water phase. The self‐assembly of NS‐CuBDC is found to be a facile method to construct small cubical NPs. The exchange of water into CuBDC leads to super hydrophilic wettability. Ascribed to their amphiphilic properties, NP‐CuBDC acts as sole stabilizer to form stable oil‐in‐water emulsions. Synchrotron‐based computed tomography is used to characterize the 3D distribution of CuBDC in emulsions at room temperature. This work provides great insights in the fundamental study of MOFs at the oil/water interface and may lead to further development of ultrathin 2D MOF membranes.
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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 | 0.001 | 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".