Evidence map›Paper›PMID 40389410›Full record

ArticleMicrosystems & nanoengineering2025

Ultra-small millimeter-wave filter chips based on high-K single-crystal lithium niobate.

Qun Li, Junyan Zheng, Yansong Yang

Abstract read
In one paragraph

Article in Microsystems & nanoengineering, 2025. 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

3 authors.

Qun LiDepartment of Electronic and Computer Engineering, Hong Kong University of Science and Technology, Hong Kong, China.ORCID http://orcid.org/0000-0002-9559-124X
Junyan ZhengDepartment of Electronic and Computer Engineering, Hong Kong University of Science and Technology, Hong Kong, China.
Yansong YangDepartment of Electronic and Computer Engineering, Hong Kong University of Science and Technology, Hong Kong, China. eeyyang@ust.hk.ORCID http://orcid.org/0000-0003-2325-3505

Funding

National Natural Science Foundation of China (National Science Foundation of China) 62304193
6 · The paper itself

Abstract

Next-generation communication systems require the mass deployment of ultra-small, high-performance filters that integrate multi-physical domains. However, achieving an optimal balance between miniaturization, low insertion loss, high selectivity, and low cost of millimeter-wave filters remains a challenge for existing technologies. Herein, we propose and demonstrate ultra-small millimeter-wave filters based on the multifunctional lithium niobate (LN) with outstanding nonlinear optical, electro-optic, piezoelectric, ferroelectric, and thermoelectric characteristics. As a high-K material with low dielectric loss and straightforward fabrication, LN provides an ideal platform for integrating photonic, acoustic, and electromagnetic functionalities. Notably, while LN is already proven for acoustic and optical signal processing, its potential for electromagnetic signal processing remains largely unexplored. In this work, we introduce second-order and fourth-order LN-based millimeter-wave bandpass filters (BPFs) tailored for narrowband and wideband millimeter-wave applications, respectively. Through careful optimization of the LN thickness, we elevate the cutoff frequencies of high-order modes, enhancing frequency selectivity while maintaining compactness. The LN-based BPFs exhibit record-breaking performance metrics, including minimal insertion loss, high selectivity, and compatibility with microfabrication processes. The LN-based BPFs fulfill the critical demands of millimeter-wave wireless communications, sensing, imaging, and emerging quantum information systems, paving the way for scalable, multi-physical integrated circuits.

Identifiers

PMID40389410
PMCPMC12089415

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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.