Scanning probe block copolymer lithography
Bibliographic record
Abstract
Integration of individual nanoparticles into desired spatial arrangements over large areas is a prerequisite for exploiting their unique electrical, optical, and chemical properties. However, positioning single sub-10-nm nanoparticles in a specific location individually on a substrate remains challenging. Herein we have developed a unique approach, termed scanning probe block copolymer lithography, which enables one to control the growth and position of individual nanoparticles in situ. This technique relies on either dip-pen nanolithography (DPN) or polymer pen lithography (PPL) to transfer phase-separating block copolymer inks in the form of 100 or more nanometer features on an underlying substrate. Reduction of the metal ions via plasma results in the high-yield formation of single crystal nanoparticles per block copolymer feature. Because the size of each feature controls the number of metal atoms within it, the DPN or PPL step can be used to control precisely the size of each nanocrystal down to 4.8 ± 0.2 nm.
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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 | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.003 |
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".