Functionalization of Multiwalled Carbon Nanotubes by Mild Aqueous Sonication
Bibliographic record
Abstract
Sonication has been widely used in the dispersal of carbon nanotubes (CNTs) in various liquids as well as in their functionalization in aqueous acids. Here, for the first time, we study the sonication of multiwalled CNTs (MWCNTs) in deionized water. Our results indicate an improvement in the aqueous dispersal of MWCNTs as well as an increase in their adhesive interaction with Au substrates. Field emission scanning electron and high-resolution transmission electron microscopies as well as X-ray photoelectron, photoacoustic Fourier transform IR, and Raman spectroscopies have shown this to be due to the production of low concentrations of O-containing functionalizations (alcohol, carbonyl, acid, with the total O concentration being approximately 2%), without damaging the basic CNT structure; this production of functional groups is mirrored by the disappearance of -CH(n) groups existing on the pristine CNTs. These new functional groups are capable of hydrogen bonding, which plays an important role in their aqueous dispersal and enhanced substrate interactions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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".