Evidence map›Paper›PMID 41639573›Full record

ArticleNature2026

Discovery Learning predicts battery cycle life from minimal experiments.

Jiawei Zhang, Yifei Zhang, Baozhao Yi, Yao Ren, Qi Jiao, Hanyu Bai, Weiran Jiang, Ziyou Song

Abstract read
PubMed Publisher
In one paragraph

Article in Nature, 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

8 authors.

Jiawei ZhangDepartment of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI, USA.ORCID 0000-0002-4503-498X
Yifei ZhangDepartment of Mechanical Engineering, National University of Singapore, Singapore, Singapore.
Baozhao YiDepartment of Mechanical Engineering, National University of Singapore, Singapore, Singapore.
Yao RenFarasis Energy USA, Inc., Hayward, CA, USA.
Qi JiaoFarasis Energy USA, Inc., Hayward, CA, USA.
Hanyu BaiDepartment of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI, USA.
Weiran JiangFarasis Energy USA, Inc., Hayward, CA, USA. wjiang@farasis.com.
Ziyou SongDepartment of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI, USA. ziyou@umich.edu.ORCID 0000-0003-3164-5234

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Fast and reliable validation of new designs in complex physical systems such as batteries is critical to accelerating technological innovation. However, battery development remains bottlenecked by the high time and energy costs required to evaluate the lifetime of new designs

Indexed as

Electric Power SuppliesMachine LearningHumansLithiumTime FactorsLithium

Identifiers

What OpenQuestion holds

Textmetadata
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.