Recent Developments in Fabrication of Giant Nanomembranes
Bibliographic record
Abstract
Giant nanomembranes that are characterized by aspect ratios (size/thickness)of greater than one million are dis-cussed.The combination of nanometer thickness and macroscopic size facilitates important applications in materialsseparation, selective transport and electrochemical devices. Their fabrication procedure and hybridization aredescribed here. Spin coating of precursor solutions on appropriate underlayer is effectively used to prepare 10-30 nmthick nanomembranes of metal oxides, interpenetrating network of crosslinked acrylate with metal oxide, and highlycross-linked organic polymers (epoxy resin, etc.). When the underlayer is removed, self-supporting nanomembranesbecome separated from the substrate without damage. These nanomembranes are surprisingly robust and defect-free, and can be hybridized by physical and chemical means. The latter method provides mechanical properties ofnanomembranes reveal that the texture of the nanomembranes is essentially identical with those of the macroscopiccounterparts. Their application potentials as 2D materials are discussed.
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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) | 0.000 | 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".