Molecular QCA design with chemically reasonable constraints
Bibliographic record
Abstract
In this article we examine the impacts of the fundamental constraints required for circuits and systems made from molecular Quantum-dot Cellular Automata (QCA) devices. Our design constraints are “chemically reasonable” in that we consider the characteristics and dimensions of devices and scaffoldings that have actually been fabricated. This work is a necessary first step for any work in QCA CAD, and can also help shape experiments in the physical sciences for emerging, nano-scale devices. Our work shows that QCA circuits, scaffoldings, substrates, and devices should all be considered simultaneously. Otherwise, there is a very real possibility that the devices and scaffoldings that are eventually manufactured will result in devices that only work in isolation. “Chemically reasonable” also means that expected manufacturing defects must be considered. In our simulations we introduce defects associated with self-assembled systems into various designs to begin to define manufacturing tolerances. This work is especially timely as experimentalists are beginning to work on merging experimental tracks that address devices and scaffolds—and the end result should facilitate correct logical operations.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".