Evidence map›Paper›PMID 40642282›Full record

ArticleEngineering (Beijing, China)2025

Real-Time Programmable Nonlinear Wavefront Shaping with Si Metasurface Driven by Genetic Algorithm.

Ze Zheng, Gabriel Sanderson, Soheil Sotoodeh, Chris Clifton, Cuifeng Ying, Mohsen Rahmani, Lei Xu

Abstract read
In one paragraph

Article in Engineering (Beijing, China), 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. Electrically Tunable VONanomaterials (Basel, Switzerland) · 2026
    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

7 authors.

Ze ZhengAdvanced Optics and Photonics Laboratory, Department of Engineering, School of Science & Technology, Nottingham Trent University, Nottingham NG11 8NS, UK.
Gabriel SandersonAdvanced Optics and Photonics Laboratory, Department of Engineering, School of Science & Technology, Nottingham Trent University, Nottingham NG11 8NS, UK.
Soheil SotoodehSony Europe B.V., Basingstoke, Hampshire RG22 4SB, UK.
Chris CliftonSony Europe B.V., Basingstoke, Hampshire RG22 4SB, UK.
Cuifeng YingAdvanced Optics and Photonics Laboratory, Department of Engineering, School of Science & Technology, Nottingham Trent University, Nottingham NG11 8NS, UK.
Mohsen RahmaniAdvanced Optics and Photonics Laboratory, Department of Engineering, School of Science & Technology, Nottingham Trent University, Nottingham NG11 8NS, UK.
Lei XuAdvanced Optics and Photonics Laboratory, Department of Engineering, School of Science & Technology, Nottingham Trent University, Nottingham NG11 8NS, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Nonlinear wavefront shaping is crucial for advancing optical technologies, enabling applications in optical computation, information processing, and imaging. However, a significant challenge is that once a metasurface is fabricated, the nonlinear wavefront it generates is fixed, offering little flexibility. This limitation often necessitates the fabrication of different metasurfaces for different wavefronts, which is both time-consuming and inefficient. To address this, we combine evolutionary algorithms with spatial light modulators (SLMs) to dynamically control wavefronts using a single metasurface, reducing the need for multiple fabrications and enabling the generation of arbitrary nonlinear wavefront patterns without requiring complicated optical alignment. We demonstrate this approach by introducing a genetic algorithm (GA) to manipulate visible wavefronts converted from near-infrared light via third-harmonic generation (THG) in a silicon metasurface. The Si metasurface supports multipolar Mie resonances that strongly enhance light-matter interactions, thereby significantly boosting THG emission at resonant positions. Additionally, the cubic relationship between THG emission and the infrared input reduces noise in the diffractive patterns produced by the SLM. This allows for precise experimental engineering of the nonlinear emission patterns with fewer alignment constraints. Our approach paves the way for self-optimized nonlinear wavefront shaping, advancing optical computation and information processing techniques.

Indexed as

Genetic algorithmNonlinear metasurfaceWavefront manipulation

Identifiers

PMID40642282
PMCPMC12239666

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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.