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Record W4416869288 · doi:10.1103/p1t4-hst3

Berezinskii-Kosterlitz-Thouless phase transition in nanoporous films of superconducting NbN

2025· article· en· W4416869288 on OpenAlexaff
A. Verma, Robert Vedin, John Jesudasan, Jack Lidmar, Ilaria Maccari, Sangita Bose

Bibliographic record

VenuePhysical review. B./Physical review. B · 2025
Typearticle
Languageen
FieldPhysics and Astronomy
TopicPhysics of Superconductivity and Magnetism
Canadian institutionsRoyal Ottawa Mental Health Centre
FundersDepartment of Atomic Energy, Government of India
KeywordsNanoporousSuperconductivityNanoporeMonte Carlo methodVortexPhase transitionSuperfluidityTransition temperature

Abstract

fetched live from OpenAlex

We present a study of the Berezinskii-Kosterlitz-Thouless (BKT) transition in mildly disordered NbN nanoporous (NP) films. The measured superfluid stiffness, ${J}_{s}$, is found to be much lower than that predicted considering a reduced geometric area. For a 5 nm thick NP film, a distinct BKT transition is observed. By fitting the experimental data via the BKT renormalization-group equations, we show how both ${J}_{s}$ and the vortex-core energy, $\ensuremath{\mu}$, decrease in the presence of nanopores. The variation of ${J}_{s}$ and $\ensuremath{\mu}$ is also reproduced theoretically via Monte Carlo numerical simulations on a 2D diluted XY model. Our results show that nanopore geometries effectively enhance the 2D nature of the superconducting films, increasing the parameter space to explore the BKT physics while offering a pathway to systematically control the two energy scales, ${J}_{s}$ and $\ensuremath{\mu}$, that govern the vortex physics in these systems.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

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 studies0.0000.000
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 head0.018
GPT teacher head0.384
Teacher spread0.367 · 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
Published2025
Admission routes1
Has abstractyes

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