Two-channel conduction through polyacenes—Extension of the source–sink potential method to multichannel coupling to leads
Bibliographic record
Abstract
The source and sink potential method of Goyer et al. [J. Chem. Phys. 126, 144104 (2007)] is extended to the case of multichannel coupling to leads. The formulation leads to a nonlinear equation for just one (the elastic) reflection coefficient. Solution of this equation, in general, requires repeated computation of an n × n determinant, where n is the number of supermolecule basis functions directly coupled to the source lead, as opposed to a determinant with order equal to the full size of supermolecule basis. The method is applied to a Hückel model of two-channel polyacene conduction. A simple model of resonance lineshapes is developed in case of weak coupling to leads. The model accurately relates peak characteristics to orbital probabilities associated with the eigenvectors of the isolated molecule Hamiltonian. The model shows how orbital probabilities that give rise to transmission resonances (i.e., 100% transmission), in the case of single-channel conduction, give rise to equal probabilities (of 1∕4) for the two reflections and two transmissions, in the case of two-channel conduction. The model also shows how splitting of degenerate eigenvalues of the isolated molecule Hamiltonian results in overlapping resonances characterized by a single complex lineshape.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".