Nanoimprint Lithography‐Directed Self‐Assembly of Bimetallic Iron–M (M=Palladium, Platinum) Complexes for Magnetic Patterning
Bibliographic record
Abstract
Abstract Self‐assembly of d8 metal polypyridine systems is a well‐established approach for the creation of 1D organometallic assemblies but there are still challenges for the large‐scale construction of nanostructured patterns from these building blocks. We describe herein the use of high‐throughput nanoimprint lithography (NIL) to direct the self‐assembly of the bimetallic complexes [4′‐ferrocenyl‐(2,2′:6′,2′′‐terpyridine)M(OAc)]+(OAc)− (M=Pd or Pt; OAc=acetate). Uniform nanorods are fabricated from the molecular self‐organization and evidenced by morphological characterization. More importantly, when top‐down NIL is coupled with the bottom‐up self‐assembly of the organometallic building blocks, regular arrays of nanorods can be accessed and the patterns can be controlled by changing the lithographic stamp, where the mold imposes a confinement effect on the nanorod growth. In addition, patterns consisting of the products formed after pyrolysis are studied. The resulting arrays of ferromagnetic FeM alloy nanorods suggest promising potential for the scalable production of ordered magnetic arrays and fabrication of magnetic bit‐patterned media.
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 | 0.001 |
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".