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Record W7132895113

Long-range Charge Transport in Linear Molecular Chains

2022· dissertation· W7132895113 on OpenAlexaff
Francisco Chun Lai-Liang

Bibliographic record

VenueTSpace · 2022
Typedissertation
Language
FieldEngineering
TopicMolecular Junctions and Nanostructures
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsDephasingQuantum tunnellingCharge (physics)AsymmetrySpin (aerodynamics)Work (physics)Electron
DOInot available

Abstract

fetched live from OpenAlex

Charge transport (CT) is the flow of charge through a medium, in this work we focus on electron CT. Due to the longer timescale of CT in longer chains, nuclear degrees of freedom must be included. In this work, we use the Landauer-B ̈uttiker probe (LBP) method to incorporate dephasing and energy exchange to the system electrons. We first present short systems of length < 1 nm to demonstrate the transition from tunneling to hopping transport mechanism. Next, we demonstrate non-trivial behaviours in high intersite tunneling energy systems. Following, we simulate longer systems up to 50 nm, showing the advantages of different transport mechanisms. We further simulate an alternating-rigidity system based on Geobacter Sulfurreducen by alternating the dephasing conditions. Finally, we apply the LBP method to study chiral-induced spin selectivity in proteins. While the results are preliminary, simulations show asymmetry of the transmission probability for different electron spin species.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0040.000

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.

Opus teacher head0.007
GPT teacher head0.265
Teacher spread0.258 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2022
Admission routes1
Has abstractyes

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