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Record W4417438661 · doi:10.1109/jrfid.2025.3644960

Ultracompact RF Rectifier Circuit for Implantable Devices

2025· article· W4417438661 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

VenueIEEE Journal of Radio Frequency Identification · 2025
Typearticle
Language
FieldEngineering
TopicWireless Power Transfer Systems
Canadian institutionsInstitut National de la Recherche Scientifique
FundersResearch and DevelopmentTelekom Malaysia BerhadAlMaarefa University
KeywordsRectifier (neural networks)Wireless power transferInductorImpedance matchingMaximum power transfer theoremElectrical impedanceRectificationEnergy conversion efficiencyEmphasis (telecommunications)

Abstract

fetched live from OpenAlex

This study proposes an innovative design approach for an ultra-compact RF rectifier, emphasizing high power conversion efficiency (PCE). The rectifier design employs a dual-branch cell configuration, labeled as Section-1 (S1) and Section-2 (S2), to enhance its performance characteristics. To support biomedical implant applications, these branches are incorporated with a meandered line network, designated as (ML1 and ML2). A radial stub is employed in the S1 structure, while series inductors are additionally connected to S1 and S2 to achieve improved performance characteristics. To improve power delivery performance, the proposed rectifier is specifically optimized for enhanced transfer efficiency within the frequency range of 1.28 GHz to 1.52 GHz. This makes it highly suitable for integration into wireless power transfer systems (WPTs) designed for biomedical implants. Both the simulated (experimental) results confirmed a maximum RF-to-DC PCE of 78.80% (77.7%), achieved at an input power <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">P<sub>in</sub></i> level of 4 dBm. Moreover, the proposed design achieves an RF-to-DC conversion efficiency greater than 25% at <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">P<sub>in</sub></i> level of -20 dBm, thereby demonstrating its suitability for efficient operation under low-power conditions. The rectifier is fabricated on an RT/Duroid substrate, resulting in a compact footprint measuring 7.8 mm by 9.3 mm. A single-series diode (SSrd) configuration is employed to achieve the desired rectification performance. To ensure a wide impedance bandwidth, a sequential matching technique is applied, effectively optimizing the device’s performance throughout the specified frequency spectrum. This work demonstrates the effectiveness of the proposed rectifier in enabling WPT for biomedical implant applications, with particular emphasis on scenarios that demand efficient harvesting of ambient energy.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.752
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0010.000
Research integrity0.0000.001
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 head0.020
GPT teacher head0.270
Teacher spread0.250 · 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