Evidence map›Paper›PMID 41682511›Full record

ArticleSensors (Basel, Switzerland)2026

A Novel 3D Probe for Near-Field Scanning Microwave Microscopy.

Ali M Almuhlafi, Omar M Ramahi

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Ali M AlmuhlafiDepartment of Electrical Engineering, College of Engineering, King Saud University, Riyadh 12372, Saudi Arabia.ORCID 0000-0002-9184-9936
Omar M RamahiDepartment of Electrical and Computer Engineering, University of Waterloo, Waterloo, ON N2L 3G1, Canada.ORCID 0000-0002-9403-0029

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Near-field scanning microwave microscopy (NSMM) offers the ability to probe local electromagnetic properties beyond the classical Abbe diffraction limit, but achieving high resolution over practical scan areas remains challenging. In this work, we introduce a novel three-dimensional (3D) NSMM probe consisting of a split-ring resonator (SRR) coupled to a microstrip line and loaded with vertically extended metallic bars. The 3D loading enhances electric-field localization in the sensing region by introducing field singularities. Full-wave numerical simulations are used to extract the field-spread function (FSF) of the probe and to quantify how probe geometry, stand-off distance, and bar dimensions control the FSF and its spatial-frequency (k-space) content. An imaging model is then developed in which the NSMM image is represented as a convolution between the object and FSF in one and two dimensions. This framework demonstrates that progressively localized FSFs, obtained through 3D loading and resonator miniaturization, systematically improve image fidelity and preserve higher spatial frequencies. The probe is fabricated using printed circuit board technology (PCB) with vertically attached metallic bars, and its performance is validated by imaging a dielectric slab containing a cylindrical air-filled void. The measured line profiles and two-dimensional images are in good agreement in general characteristics with the convolution-based model, confirming that the proposed 3D SRR-based probe operates as a spatial filter whose engineered near-field distribution governs the achievable resolution in NSMM imaging.

Indexed as

complementary split-ring resonatorsfield-spread functionnear-field scanning microwave microscopypoint-spread function

Identifiers

PMID41682511
PMCPMC12900001

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.