Evidence map›Paper›PMID 40808184›Full record

ReviewPolymers2025

Recent Progress on the Research of 3D Printing in Aqueous Zinc-Ion Batteries.

Yating Liu, Haokai Ding, Honglin Chen, Haoxuan Gao, Jixin Yu, Funian Mo, Ning Wang

Abstract readReview
In one paragraph

Review in Polymers, 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

7 authors.

Yating LiuFuture Technology School, Shenzhen Technology University, Shenzhen 518118, China.ORCID 0009-0002-1144-4937
Haokai DingFuture Technology School, Shenzhen Technology University, Shenzhen 518118, China.ORCID 0009-0001-6158-9897
Honglin ChenFuture Technology School, Shenzhen Technology University, Shenzhen 518118, China.
Haoxuan GaoFuture Technology School, Shenzhen Technology University, Shenzhen 518118, China.
Jixin YuFuture Technology School, Shenzhen Technology University, Shenzhen 518118, China.
Funian MoFuture Technology School, Shenzhen Technology University, Shenzhen 518118, China.ORCID 0000-0002-9437-1878
Ning WangDepartment of Materials Science and Engineering, Shenzhen Technology University, Shenzhen 518118, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The global transition towards a low-carbon energy system urgently demands efficient and safe energy storage solutions. Aqueous zinc-ion batteries (AZIBs) are considered a promising alternative to lithium-ion batteries due to their inherent safety and environmental friendliness. However, conventional manufacturing methods are costly and labor-intensive, hindering their large-scale production. Recent advances in 3D printing technology offer innovative pathways to address these challenges. By combining design flexibility with material optimization, 3D printing holds the potential to enhance battery performance and enable customized structures. This review systematically examines the application of 3D printing technology in fabricating key AZIB components, including electrodes, electrolytes, and integrated battery designs. We critically compare the advantages and disadvantages of different 3D printing techniques for these components, discuss the potential and mechanisms by which 3D-printed structures enhance ion transport and electrochemical stability, highlight critical existing scientific questions and research gaps, and explore potential strategies for optimizing the manufacturing process.

Indexed as

3D printingelectrodeselectrolytesenergy-densityzinc-ion batteries

Identifiers

PMID40808184
PMCPMC12349459

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.