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Record W4319319395 · doi:10.1142/s021797922350234x

Effect of electromagnetic permeability on transition temperature of superconductivity

2023· article· en· W4319319395 on OpenAlexaff
M. M. Bagheri–Mohagheghi, Behnam Pourhassan, M. Adelifard, Mehrdad Shokooh‐Saremi, Sudhaker Upadhyay

Bibliographic record

VenueInternational Journal of Modern Physics B · 2023
Typearticle
Languageen
FieldPhysics and Astronomy
TopicPhysics of Superconductivity and Magnetism
Canadian institutionsCanadian Quantum Research Center
Fundersnot available
KeywordsCondensed matter physicsSuperconductivityPhysicsVortexMagnetic monopoleTransition temperatureLattice (music)PermittivityQuantum mechanicsThermodynamicsDielectric

Abstract

fetched live from OpenAlex

The description of superconductivity at high-temperature is a problem that has recently been addressed. Transition temperature of superconductivity, [Formula: see text], depends on the lattice structure type, size and room pressure. In super-lattices and low-dimensional layered nanostructures, [Formula: see text] is increased by increasing the complexity of the structure and internal pressures in solid lattice. In this paper, we investigate the relation between physical parameters ([Formula: see text]) of matter and superconductivity properties as well as transition temperature ([Formula: see text]), and explain the superconductivity at high-temperature. In this study, a semi-classical electromagnetic description along with vortex topologic theory and quantum dynamic models with experimental data is considered to justify the relation between superconductivity phenomena and magnetic monopole properties. We find that the electromagnetic energy of magnetic monopole is in agreement with vortex energy in topological theory and it can get close to thermal energy at high-temperature. These models suggest that the superconductivity is related to the mobile monopole or vortices. We show that the electrical permittivity ([Formula: see text]) and magnetic permeability ([Formula: see text]) of matter have a key role in the superconductive properties.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.168
Threshold uncertainty score0.589

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 studies0.0000.000
Scholarly communication0.0000.001
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 head0.009
GPT teacher head0.266
Teacher spread0.256 · 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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