Evidence map›Paper›PMID 39927201›Full record

ArticleNanophotonics (Berlin, Germany)2025

A novel intelligent photonic design method enabled by metamaterials and k-nearest neighbor.

Hangming Fan, Junlin Pan, Yongchen Wang, Zhe Yuan, Mengfan Cheng, Qi Yang, Deming Liu, Lei Deng

Abstract read
In one paragraph

Article in Nanophotonics (Berlin, Germany), 2025. 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

8 authors.

Hangming FanWuhan National Laboratory for Optoelectronics and School of Optical and Electronic Information, Huazhong University of Science and Technology, Wuhan 430074, China.
Junlin PanWuhan National Laboratory for Optoelectronics and School of Optical and Electronic Information, Huazhong University of Science and Technology, Wuhan 430074, China.ORCID https://orcid.org/0009-0008-4928-8072
Yongchen WangWuhan National Laboratory for Optoelectronics and School of Optical and Electronic Information, Huazhong University of Science and Technology, Wuhan 430074, China.
Zhe YuanWuhan National Laboratory for Optoelectronics and School of Optical and Electronic Information, Huazhong University of Science and Technology, Wuhan 430074, China.
Mengfan ChengWuhan National Laboratory for Optoelectronics and School of Optical and Electronic Information, Huazhong University of Science and Technology, Wuhan 430074, China.
Qi YangWuhan National Laboratory for Optoelectronics and School of Optical and Electronic Information, Huazhong University of Science and Technology, Wuhan 430074, China.
Deming LiuWuhan National Laboratory for Optoelectronics and School of Optical and Electronic Information, Huazhong University of Science and Technology, Wuhan 430074, China.
Lei DengWuhan National Laboratory for Optoelectronics and School of Optical and Electronic Information, Huazhong University of Science and Technology, Wuhan 430074, China.ORCID https://orcid.org/0000-0003-2647-4610

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The utilization of metamaterials plays a pivotal role in integrated photonics. The precise design of metamaterials enables them to finely manipulate light, resulting in an ultra-compact footprint and exceptional performance that cannot be achieved by traditional structures. The conventional methods for metamaterial design, however, encounter challenges from intricate targets. Although attempts have been made to apply inverse design to metamaterials, there is still a need for a highly intelligent, low-computation method, and easy-to-fabricate metamaterial structure. Here, we present an efficient methodology that combines metamaterials, heuristic algorithms, and machine learning to facilitate the rapid development of intricate devices. The method is used to design 1 × N power splitters with arbitrary power ratios, as an application example. Specifically, 1 × 2, 1 × 3, 1 × 4 power splitters with arbitrary ratios are fabricated and experimentally demonstrated. The application of this method in arbitrary power splitter highlights its appropriateness for the design and optimization within integrated photonics devices.

Indexed as

inverse designmachine learningmetamaterialpower splitter

Identifiers

PMID39927201
PMCPMC11806503

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

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.