Evidence map›Paper›PMID 41931603›Full record

ArticleScience advances2026

Machine learning-assisted discovery of outside-in structure Ni-rich cathode with high performance.

Guihong Mao, Ying Wang, Tengyu Yao, Xianlin Qu, Jieyu Yang, Zhenming Xu, Xiuwen Wang, Zijuan Ge, Yi Wang, Laifa Shen

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Science advances, 2026. 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

10 authors.

Guihong MaoJiangsu Key Laboratory of Materials and Technologies for Energy Storage, College of Materials Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China.ORCID 0009-0009-9115-2803
Ying WangState Key Laboratory of Rare Metals Separation and Comprehensive Utilization, Guangdong Provincial Key Laboratory of Rare Earth Development and Application, Institute of Resources Utilization and Rare Earth Development, Guangdong Academy of Sciences, Guangzhou 510650, China.
Tengyu YaoJiangsu Key Laboratory of Materials and Technologies for Energy Storage, College of Materials Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China.
Xianlin QuCenter for Microscopy and Analysis, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China.
Jieyu YangJiangsu Key Laboratory of Materials and Technologies for Energy Storage, College of Materials Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China.ORCID 0009-0009-7608-5059
Zhenming XuJiangsu Key Laboratory of Materials and Technologies for Energy Storage, College of Materials Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China.ORCID 0000-0002-7039-3845
Xiuwen WangCenter for Microscopy and Analysis, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China.
Zijuan GeCenter for Microscopy and Analysis, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China.
Yi WangCenter for Microscopy and Analysis, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China.ORCID 0000-0002-6541-4584
Laifa ShenJiangsu Key Laboratory of Materials and Technologies for Energy Storage, College of Materials Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China.ORCID 0000-0001-5114-6446

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Ni-rich oxides have emerged as leading cathode candidates for lithium-ion batteries because of high specific energy, lower cost, and improved sustainability compared to cobalt-based materials. However, Ni-rich cathodes suffer from voltage and capacity degradation driven by anisotropic lattice strain and interfacial reconstruction. Here, we report a high-performance Ni-rich cathode featuring a robust outside-in architecture, achieved via machine learning-assisted identification of Al

Identifiers

PMID41931603
PMCPMC13048256

What OpenQuestion holds

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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.