Evidence map›Paper›PMID 35241767›Full record

ArticleScientific reports2022

Exploitation of response surface method for the optimization of RF-MEMS reconfigurable devices in view of future beyond-5G, 6G and super-IoT applications.

Jacopo Iannacci, Girolamo Tagliapietra, Alessio Bucciarelli

Abstract read
In one paragraph

Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Progress in RF-MEMS.Micromachines · 2025
    Article
  5. Article
  6. Review
  7. Article
  8. Article
  9. Article
  10. Article
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.

Jacopo IannacciCenter for Sensors and Devices (SD), Fondazione Bruno Kessler (FBK), 38123, Trento, Italy. iannacci@fbk.eu.
Girolamo TagliapietraCenter for Sensors and Devices (SD), Fondazione Bruno Kessler (FBK), 38123, Trento, Italy.
Alessio BucciarelliCNR-Nanotec, National Council or Research, Campus Ecotekne-Università del Salento, 73100, Lecce, Italy.

Funding

Agenzia Spaziale Italiana F36C18000400005
6 · The paper itself

Abstract

The emerging paradigms of the Beyond-5G, 6G and Super-IoT will demand for high-performance Radio Frequency (RF) passive components, and RF-MEMS technology, i.e. Microsystems-based RF passives, is a good candidate to meet such a challenge. As known, RF-MEMS have a complex behavior, that crosses different physical domains (mechanical; electrical; electromagnetic), making the whole design optimization and trimming phases particularly articulated and time consuming. In this work, we propose a novel design optimization approach based on the Response Surface Method (RSM) statistical methodology, focusing on a class of RF-MEMS-based programmable step power attenuators. The proposed method is validated both against physical simulations, performed with Finite Element Method (FEM) commercial software tools, as well as experimental measurements of physical devices. The case study here discussed features 3 DoFs (Degrees of Freedom), comprising both geometrical and material parameters, and aims to optimize the RF performances of the MEMS attenuator in terms of attenuation (S21 Scattering parameter) and reflection (VSWR-Voltage Standing Wave Ratio). When validated, the proposed RSM-based method allows avoiding physical FEM simulations, thus making the design optimization considerably faster and less complex, both in terms of time and computational load.

Identifiers

PMID35241767
PMCPMC8894374

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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.