Bibliographic record
Abstract
Molecular Electronics has the potential to greatly enhance existing silicon-based microelectronics to realize new functions, higher device density, lower power consumption, and lower cost. Although the investigation of electron transport through single molecules and molecular monolayers in "molecular junctions" is a recent development, many of the relevant concepts and phenomena are derived from electrochemistry, as practiced for the past several decades. The past 10+ years have seen an explosion of research activity directed toward how the structure of molecules affects electron transport in molecular junctions, with the ultimate objective of "rational design" of molecular components with new electronic functions, such as chemical sensing, interactions with light, and low-cost, low-power consumer electronics. In order to achieve these scientifically and commercially important objectives, the factors controlling charge transport in molecules "connected" to conducting contacts must be understood, and methods for massively parallel manufacturing of molecular circuits must be developed. This Personal Account describes the development of reproducible and robust molecular electronic devices, starting with modified electrodes used in electrochemistry and progressing to manufacturable molecular junctions. Although the field faced some early difficulties in reliability and characterization, the pieces are now in place for rapid advances in understanding charge transport at the molecular level. Inherent in the field of Molecular Electronics are many electrochemical concepts, including tunneling, redox exchange, activated electron transfer, and electron coupling between molecules and conducting contacts.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".