Evidence map›Paper›PMID 42796179›Full record

ArticleMicromachines2026

Topology-Free EM Modeling and Analysis of Pixelated Microstrip Low-Pass Filters Under Comparable Footprint.

Jorge Davalos-Guzman, Jose L Chavez-Hurtado, Lina M Aguilar-Lobo

Abstract read
In one paragraph

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

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0citing papers in PubMed
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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

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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

3 authors.

Jorge Davalos-GuzmanDivisión de Ingenierías, Subdirección de Investigación y Extensión, Centro de Enseñanza Técnica Industrial, Plantel Tonalá, Tonalá 45402, Jalisco, Mexico.ORCID 0000-0001-8267-9261
Jose L Chavez-HurtadoDepartment of Electronics, Systems, and Informatics, Instituto Tecnológico y de Estudios Superiores de Occidente (ITESO), The Jesuit University of Guadalajara, Tlaquepaque 45604, Jalisco, Mexico.ORCID 0000-0003-4115-0999
Lina M Aguilar-LoboDepartamento de Computación e Industrial, Universidad Autónoma de Guadalajara, Av. Patria 1201, Zapopan 45129, Jalisco, Mexico.ORCID 0000-0002-0896-5320

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Pixelated electromagnetic representations enable topology-free numerical exploration of microwave layouts without enforcing a predefined circuit template. This work presents a simulation-based electromagnetic modeling and analysis framework for pixelated microstrip low-pass filters within a physical footprint comparable to that of a classical stepped-impedance reference. A binary metallization encoding is embedded in a fixed microstrip domain and explored through full-wave electromagnetic optimization under consistent material, excitation, and specification conditions. The objective is not extreme miniaturization or hardware prototyping, but to assess whether topology-free pixelated layouts can produce useful low-pass responses within the same general physical scale and to analyze the structural properties of the resulting feasible layouts. Across 20 independent optimization runs, 12 specification-compliant and geometrically unique metallization layouts were identified. Aggregate analysis of 360 single-pixel perturbations reveals topology-dependent sensitivity, while finite-width regularization of ideal corner contacts preserves modeled specification compliance after refined-mesh verification, with the suitable bridge width depending on the topology. The scope is deliberately limited to full-wave EM modeling and numerical analysis; experimental fabrication and measurement are left as a subsequent validation stage. These findings support topology-free pixelated EM modeling and analysis as a route for investigating non-obvious low-pass filter layouts under comparable footprint constraints.

Indexed as

electromagnetic modelingfull-wave simulationinverse designlow-pass filtersmicrostrip filterspixelated structurestopology-free optimization

Identifiers

PMID42796179
PMCPMC13608989

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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.