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Laser-Induced Graphene (LIG) Smart Contact Lens (SCL) for the Wireless Monitoring of Intra-Ocular Health

2025· article· en· W4417052339 on OpenAlexfundno aff
F. Nanni, Alessia Buccella, Gaetano Marrocco

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicWireless Power Transfer Systems
Canadian institutionsnot available
FundersNextGenerationEUCanadian University PressElectrochemical Society
KeywordsMiniaturizationWirelessContact lensLens (geology)GraphenePlanarAntenna (radio)

Abstract

fetched live from OpenAlex

This paper presents a novel smart contact lens (sCL) for wireless ocular monitoring, fabricated using LaserInduced Graphene (LIG) directly patterned on a polyether ether ketone (PEEK) substrate. The antenna, designed as a planar loop structure, is integrated with an EM4152 RFID microchip and a tuning inductor, forming a fully passive ultra-high frequency (UHF) system. The device was tested on a porcine eye phantom, which mimics the anatomy and dielectric properties of the human eye. Electromagnetic simulations guided the antenna design to balance miniaturization constraints with radiation performance. Experimental results demonstrate that the 6 mm diameter loop performs stable communication at a distance of nearly 2 cm, achieving a measured realized gain of −37 dB at 915 MHz. These findings validate the feasibility of LIG-based RFID sCLs for non-invasive, real-time eye health monitoring using a compact handheld reader.

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 score0.407
Threshold uncertainty score0.708

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 head0.019
GPT teacher head0.252
Teacher spread0.233 · 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
Published2025
Admission routes1
Has abstractyes

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