Evidence map›Paper›PMID 42297771›Full record

ArticleMicrosystems & nanoengineering2026

Spatially tailored spin wave excitation for spurious-free, low-loss magnetostatic wave filters with ultra-wide frequency tunability.

Shuxian Wu, Shun Yao, Xingyu Du, Chin-Yu Chang, Roy H Olsson

Abstract read
In one paragraph

Article in Microsystems & nanoengineering, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

5 authors.

Shuxian Wu *Department of Electrical and Systems Engineering, University of Pennsylvania, Philadelphia, PA, USA.ORCID http://orcid.org/0000-0003-1189-2932
Shun Yao *Department of Electrical and Systems Engineering, University of Pennsylvania, Philadelphia, PA, USA.ORCID http://orcid.org/0000-0001-5226-5084
Xingyu DuDepartment of Electrical and Systems Engineering, University of Pennsylvania, Philadelphia, PA, USA.ORCID http://orcid.org/0000-0002-4974-5551
Chin-Yu ChangDepartment of Electrical and Systems Engineering, University of Pennsylvania, Philadelphia, PA, USA.ORCID http://orcid.org/0000-0002-5123-0565
Roy H OlssonDepartment of Electrical and Systems Engineering, University of Pennsylvania, Philadelphia, PA, USA. rolsson@seas.upenn.edu.ORCID http://orcid.org/0000-0002-8007-5082

Funding

United States Department of Defense | Defense Advanced Research Projects Agency (DARPA) FA8650-21-1-7010
6 · The paper itself

Abstract

Yttrium iron garnet (YIG) magnetostatic wave (MSW) radio frequency cavity filters are promising for sixth-generation (6G) communication systems due to their wide frequency tunability. However, the presence of severe spurious modes arising from the finite cavity dimensions severely degrades the filter performance. We present a half-cone transducer that spatially tailors spin wave excitation to selectively enhance the primary cavity modes comprising the YIG-based MSW filter passband, while strongly suppressing the undesired spurious modes. Theoretical analysis, numerical simulations and experiments verify the effectiveness of the spatially tailored technique. We utilize the half-cone transducer to demonstrate a spurious-free, single-cavity half-cone MSW filter (HC-MSWF) with an insertion loss (IL) of 2.4-3.2 dB over a frequency tuning range of 6.3-16.8 GHz. Extending our study, we further demonstrate a spurious-free, dual-cavity HC-MSWF with an unprecedented tuning range of 21.7 GHz (9.8-31.5 GHz) while maintaining a low IL of 2.9-3.8 dB. This significant advance in performance will enable highly reconfigurable and robust 6G networks.

Identifiers

PMID42297771
PMCPMC13269825

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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.