Evidence map›Paper›PMID 42236465›Full record

ArticleNature communications2026

Closed-loop high-precision two-photon lithography based on a multiplexed single-cavity dual-comb laser.

Yalan Yu, Zhiwei Zhu, Benjamin Willenberg, Justinas Pupeikis, Christopher R Phillips, Shih-Chi Chen

Abstract read
In one paragraph

Article in Nature communications, 2026. 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

6 authors.

Yalan Yu *Department of Mechanical and Automation Engineering, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong.
Zhiwei Zhu *Department of Mechanical and Automation Engineering, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong.
Benjamin WillenbergDepartment of Physics, Institute for Quantum Electronics, ETH, Zurich, Switzerland.
Justinas PupeikisDepartment of Physics, Institute for Quantum Electronics, ETH, Zurich, Switzerland.
Christopher R PhillipsDepartment of Physics, Institute for Quantum Electronics, ETH, Zurich, Switzerland.
Shih-Chi ChenDepartment of Mechanical and Automation Engineering, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong. scchen@mae.cuhk.edu.hk.ORCID http://orcid.org/0000-0002-4935-8412

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Two-photon lithography fabricates three-dimensional structures with 100-nanometer resolution; yet its industrial adoption is hindered by poor reproducibility and the need for complex manual tuning processes. While post-fabrication metrology, such as scanning electron microscopy, characterizes final morphologies, it cannot prevent manufacturing errors. Here we show a two-photon lithography platform powered by a single-cavity dual-comb laser that addresses this limitation through real-time correction. During fabrication, one laser comb, after frequency conversion, performs two-photon printing, while the dual-comb system simultaneously performs in-situ phase measurements across the full work field at 360 hertz. By feeding the phase profiles into a dynamic model, the platform automatically modulates printing parameters to correct height errors. We demonstrate this capability through a continuous 14-hour fabrication process to manufacture different millimeter-scale diffractive optical elements with less than 100-nm absolute errors. The resulting devices exhibit superior signal-to-noise ratios, process repeatability, and focus quality. This closed-loop dual-comb platform offers a cost-effective, scalable solution for high-precision, high-yield nanomanufacturing.

Identifiers

PMID42236465
PMCPMC13396189

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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.