Evidence map›Paper›PMID 41444478›Full record

ArticleNature communications2025

Machine learning-assisted kinetic matching model for rational electrode design in aqueous zinc-ion batteries.

Qian Xie, Yurong You, Dingshuo Qiao, Huan Xia, Hanning Zhang, Song-Zhu Kure-Chu, Tomasz Wejrzanowski, Tao Shui, Wei Zhang, ZhengMing Sun

Abstract read
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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 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. 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

10 authors.

Qian Xie *State Key Laboratory of Engineering Materials for Major Infrastructure, School of Materials Science and Engineering, Southeast University, Nanjing, China.
Yurong You *State Key Laboratory of Engineering Materials for Major Infrastructure, School of Materials Science and Engineering, Southeast University, Nanjing, China.
Dingshuo QiaoState Key Laboratory of Engineering Materials for Major Infrastructure, School of Materials Science and Engineering, Southeast University, Nanjing, China.
Huan XiaState Key Laboratory of Engineering Materials for Major Infrastructure, School of Materials Science and Engineering, Southeast University, Nanjing, China.
Hanning ZhangState Key Laboratory of Engineering Materials for Major Infrastructure, School of Materials Science and Engineering, Southeast University, Nanjing, China.
Song-Zhu Kure-ChuDepartment of Materials Function and Design, Nagoya Institute of Technology, Nagoya, Aichi, Japan.
Tomasz WejrzanowskiFaculty of Materials Science and Engineering, Warsaw University of Technology, Warsaw, Poland.
Tao ShuiState Key Laboratory of Engineering Materials for Major Infrastructure, School of Materials Science and Engineering, Southeast University, Nanjing, China. tshui@seu.edu.cn.ORCID http://orcid.org/0000-0002-3691-2744
Wei ZhangState Key Laboratory of Engineering Materials for Major Infrastructure, School of Materials Science and Engineering, Southeast University, Nanjing, China. w69zhang@seu.edu.cn.ORCID http://orcid.org/0000-0002-4700-2658
ZhengMing SunState Key Laboratory of Engineering Materials for Major Infrastructure, School of Materials Science and Engineering, Southeast University, Nanjing, China. zmsun@seu.edu.cn.ORCID http://orcid.org/0000-0001-9798-9385

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Aqueous zinc-ion batteries offer inherent safety and low cost, yet performance is limited by unstable zinc metal negative electrodes and dissolution-prone positive electrodes, causing dendrite growth, sluggish ion transport, and rapid capacity decay. Replacing both electrodes with intercalation hosts provides a solution, but progress is slowed by the lack of a universal principle for selecting kinetically compatible pairs. Most existing efforts optimize single components rather than addressing the electrodes' kinetic mismatch governing full-cell stability. Here we show a machine-learning-assisted kinetic-matching framework that quantitatively evaluates ion-transport compatibility in intercalation-type zinc-ion batteries electrodes. By correlating interlayer spacing with Zn

Identifiers

PMID41444478
PMCPMC12864823

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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.