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Record W4381186163 · doi:10.11159/tann23.002

Theoretical Modelling of Interactions of Moving Charged Particles withTwo-Dimensional Materials

2023· article· en· W4381186163 on OpenAlexaff
Z. L. Mišković

Bibliographic record

VenueProceedings of the International Conference of Theoretical and Applied Nanoscience and Nanotechnology · 2023
Typearticle
Languageen
FieldEngineering
TopicElectrohydrodynamics and Fluid Dynamics
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsComputer scienceMaterials science

Abstract

fetched live from OpenAlex

I shall review some of our recent work on theoretical modelling of the interaction of a charged particle with mono-layer black phosphorus, called phosphorene, which is well known for its strong in-plane optical and electronic anisotropy [1].First, using a relativistic formulation of the problem, I shall show that the angular patterns in the transition radiation emitted from doped phosphorene, triggered by a traversal of a fast electron in a Transmission Electron Microscope (TEM), can be related to the in-plane conductivity tensor of this material in the frequency range from the terahertz to the mid-infrared (THz-MIR) [2].This can be used to probe the dispersion of the so-called hyperbolic plasmon polariton modes in doped phosphorene at such low frequencies, which are still not accessible via energy loss measurements in TEM [3].Second, using a nonrelativistic formulation, I shall show some results on an anisotropic stopping force that acts on a charge moving parallel to a supported layer of doped phosphorene on a SiO2 substrate [4].For this configuration, I shall also show results on an anisotropic wake effect in the electric potential induced in phosphorene by a fast-moving charge, as well as illustrate an application of the concept of stopping force to the calculation of an anisotropic dc mobility tensor in doped phosphorene.In our calculations for both configurations [2,4], we have used an empirical model for the conductivity tensor of doped phosphorene in the THz-MIR frequency range that was developed by a careful calibration against the ab initio data, which include both the intraband and interband electronic transitions in this material [5].

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.283
Threshold uncertainty score0.622

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.011
GPT teacher head0.209
Teacher spread0.198 · 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 teacher head, 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
Published2023
Admission routes1
Has abstractyes

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