Identification of Topotactic Surface‐Confined Ullmann‐Polymerization
Bibliographic record
Abstract
On-surface Ullmann coupling is an established method for the synthesis of 1D and 2D organic structures. A key limitation to obtaining ordered polymers is the uncertainty in the final structure for coupling via random diffusion of reactants over the substrate, which leads to polymorphism and defects. Here, a topotactic polymerization on Cu(110) in a series of differently-halogenated para-phenylenes is identified, where the self-assembled organometallic (OM) reactants of diiodobenzene couple directly into a single, deterministic product, whereas the other precursors follow a diffusion driven reaction. The topotactic mechanism is the result of the structure of the iodine on Cu(110), which controls the orientation of the OM reactants and intermediates to be the same as the final polymer chains. Temperature-programmed X-ray photoelectron spectroscopy and kinetic modeling reflect the differences in the polymerization regimes, and the effects of the OM chain alignments and halogens are disentangled by Nudged Elastic Band calculations. It is found that the repulsion or attraction between chains and halogens drive the polymerization to be either diffusive or topotactic. These results provide detailed insights into on-surface reaction mechanisms and prove the possibility of harnessing topotactic reactions in surface-confined Ullmann polymerization.
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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 | 0.000 |
| 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".