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Viscous Current-Induced Forces

2024· preprint· en· W4392781674 on OpenAlexfundno aff
V. U. Nazarov, Tchavdar N. Todorov, E. K. U. Gross

Bibliographic record

VenuePhysical Review Letters · 2024
Typepreprint
Languageen
FieldPhysics and Astronomy
TopicForce Microscopy Techniques and Applications
Canadian institutionsnot available
FundersH2020 European Research CouncilHorizon 2020 Framework ProgrammeQueen's UniversityQueen's University BelfastEuropean Commission
KeywordsCurrent (fluid)MechanicsPhysicsThermodynamics

Abstract

fetched live from OpenAlex

We study the motion (translational, vibrational, and rotational) of a diatomic impurity immersed in an electron liquid and exposed to electronic current. An approach based on the linear response time-dependent density functional theory combined with the Ehrenfest dynamics leads to a system of linear algebraic equations, which account for the competing and counteracting effects of the current-induced force (electron wind) and the electronic friction. We find and emphasize the coupling between the center of mass motion and that of the nuclei relative to each other, the feature due to the mediation of the two-body interaction by the environment. The current-induced forces, by means of the dynamic exchange-correlation (xc) kernel f_{xc}(r,r^{'},ω), include the electronic viscosity contribution. Starting from the ground state at the equilibrium internuclear distance and applying a current pulse, we observe three phases of the motion: (i) acceleration due to the prevalence of the current-induced force, (ii) stabilization upon balancing of the two forces, and (iii) deceleration due to the friction after the end of the pulse. At lower, but still metallic, electron densities, the dynamic xc contribution to the force significantly affects the acceleration (deceleration) at the first (third) phase of the process. For the Cs density (r_{s}≈6 a.u.), this correction amounts up to 40% in the rotation regime.

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)0.001
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.022
GPT teacher head0.365
Teacher spread0.343 · 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

Citations1
Published2024
Admission routes1
Has abstractyes

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