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Record W4406844260 · doi:10.3390/photonics12020111

Highly Efficient Polarization-Insensitive Grating Couplers on Thin-Film Lithium Niobate with an Integrated Gold Layer

2025· article· en· W4406844260 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuePhotonics · 2025
Typearticle
Languageen
FieldPhysics and Astronomy
TopicPhotorefractive and Nonlinear Optics
Canadian institutionsMcMaster University
Fundersnot available
KeywordsLithium niobateMaterials sciencePolarization (electrochemistry)GratingOptoelectronicsOpticsDiffraction gratingThin filmLayer (electronics)NanotechnologyChemistry

Abstract

fetched live from OpenAlex

The thin-film lithium niobate platform, which is emerging as a promising photonic integration platform, currently lacks a polarization-insensitive grating coupler (GC), a crucial component for polarization-independent fiber interfaces. This limitation restricts its use in many applications, such as polarization-insensitive modulation systems and polarization management. In this study, we propose a polarization-insensitive nonuniform GC, achieved by intersecting optimal TE- and TM-mode grating periods. Based on our simulation results, the proposed design delivers a coupling efficiency (CE) of 80% for TE and 78.5% for TM polarization, with a polarization-dependent loss of less than 0.14 dB at a wavelength of 1550 nm. The inserted gold layer, i.e., that inside the substrate layer, boosts the CEs of the optimal TE- and TM-mode GC by about 50%, resulting in a highly efficient, polarization-insensitive solution. This advancement enables on-chip polarization diversity applications on the thin-film lithium niobate platform. We also investigate the fabrication and alignment tolerances of the proposed design to ensure robust performance under practical conditions.

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.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.378
Threshold uncertainty score0.819

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 communication0.0000.000
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 head0.010
GPT teacher head0.256
Teacher spread0.246 · 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