Evidence map›Paper›PMID 41184280›Full record

ArticleNature communications2025

High-throughput printing of functionally gradient material from self-propagation.

Yan Zhang, Yuqiang Liu, Guangzhen Ren, Chen Yu

Abstract read
In one paragraph

Article in Nature communications, 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

4 authors.

Yan Zhang *School of Mechanical Engineering, Xinjiang University, Wulumuqi, China. yanzhang4967@163.com.ORCID http://orcid.org/0000-0002-1132-1147
Yuqiang Liu *School of Mechanical Engineering, Xinjiang University, Wulumuqi, China. 18793437879@163.com.
Guangzhen RenSchool of Materials Science and Engineering, Xinjiang University, Wulumuqi, China.
Chen YuSchool of Materials Science and Engineering, Xinjiang University, Wulumuqi, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

While combinatorial deposition techniques have accelerated the screening and understanding of materials, the creation of multi-material integration and gradient libraries is limited by mixing and distribution challenges. Here we show arbitrarily formable 3D-printable precursor materials, which are precisely formulated with their compositions by high-throughput techniques to achieve multiple degrees of freedom, efficiently realizing multi-scale, multi-component, and high-throughput printing. Meanwhile, a highly adaptive self-propagating-energy deposition technique based on a redox reaction between the precursors has been established, reducing the dependence on specific equipment and processes. We have realized printing strategies for multiple copper-based composites and multicomponent gradient materials, making possible multiple metallic and nonmetallic compounds as well as multigradient materials with multiple compositions and structures with simultaneous gradient properties. Multi-gradient materials are able to be printed synchronously during the printing process, avoiding structural defects such as thermal accumulation and cracks through thermal stacking between gradients, which cannot be obtained by conventional manufacturing methods.

Identifiers

PMID41184280
PMCPMC12583493

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

None linked

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.