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Record W4406858060 · doi:10.1109/jerm.2025.3529656

Broadband Wide-Angle Absorber for Microwave Imaging of Tissue

2025· article· en· W4406858060 on OpenAlexaff
Zhen-Yuan Zhang, Golap Kanti Dey, Nooshin Valizade Shahmirzadi, Natalia K. Nikolova

Bibliographic record

VenueIEEE Journal of Electromagnetics RF and Microwaves in Medicine and Biology · 2025
Typearticle
Languageen
FieldEngineering
TopicMicrowave Imaging and Scattering Analysis
Canadian institutionsMcMaster University
Fundersnot available
KeywordsBroadbandMicrowaveMaterials scienceOpticsMicrowave imagingPhysicsComputer scienceTelecommunications

Abstract

fetched live from OpenAlex

A broadband wide-angle absorbing structure for the non-reflective termination of tissue is proposed for enclosures needed in microwave tissue imaging. A prototype consisting of 10 × 10 unit cells is fabricated and experimentally tested using breast-tissue phantoms. Through simulations and measurements, it is demonstrated that the proposed absorbing structure achieves a reflection coefficient better than −20 dB for TE polarization and better than −12 dB for TM polarization for incidence angles from 0° to 80° and within the frequency band from 3 GHz to 8 GHz. The design principles are delineated, enabling the development of other absorbing structures suitable for any tissue of interest. A calibration method and procedure are also developed and employed with the reported measurements, which allow for de-embedding the effect of the lossy tissue medium and extracting the intrinsic reflection coefficient of the absorber. The proposed structure demonstrates superior absorption compared to prior designs and provides a much-needed solution for the construction of non-reflective enclosures for microwave biomedical imaging applications.

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 score0.053
Threshold uncertainty score0.509

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.011
GPT teacher head0.282
Teacher spread0.271 · 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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