Evidence map›Paper›PMID 42557833›Full record

ArticleSmall methods2026

Bridging Materials and Performance in Batteries: The Role of Accurate Models in Electrode Design and Manufacturing.

Liqi Zhao, Dongsheng Ren, Li Wang, Xiangming He

Abstract read
In one paragraph

Article in Small methods, 2026. 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

4 authors.

Liqi ZhaoInstitute of Nuclear & New Energy Technology, Tsinghua University, Beijing, China.
Dongsheng RenSchool of Vehicle and Mobility, Tsinghua University, Beijing, China.ORCID https://orcid.org/0000-0002-8764-9819
Li WangInstitute of Nuclear & New Energy Technology, Tsinghua University, Beijing, China.ORCID https://orcid.org/0000-0002-9615-1879
Xiangming HeInstitute of Nuclear & New Energy Technology, Tsinghua University, Beijing, China.ORCID https://orcid.org/0000-0001-7146-4097

Funding

Beijing Natural Science Foundation L242005National Key Research and Development Program of China 2025YFF0513401National Natural Science Foundation of China 22279070
6 · The paper itself

Abstract

The electrochemical performance of batteries is governed not only by the intrinsic properties of active materials but, more critically, by the architecture of porous electrodes. A key bottleneck is ion diffusion hindered by tortuous pore pathways, which induces significant overpotential that limits high-rate operation. Inefficient electron conduction further exacerbates performance losses. To meet the growing demand for fast-charging capabilities, electrode design must strategically balance material composition and pore structure to enhance both ionic and electronic transport. Yet, identifying the optimal combination remains challenging. Mathematical models offer a powerful and resource-efficient approach to pinpoint critical design parameters and guide optimization. This review examines semi-empirical models and physics-based frameworks rooted in mass transport equations, comparing their principles, applications, strengths, and limitations in electrode design. Furthermore, it organizes electrode models around how they link composition and microstructure to transport, performance, and manufacturing. We further discuss the challenges and future directions for translating model-based insights into mass production, focusing on four key enablers: model accuracy, robust parameter identification, intelligent optimization, and integration with manufacturing processes guided by cross-model synergies.

Indexed as

battery manufacturingelectrode designmodel‐assisted optimizationphysics‐based modelsporous electrode structuresemi‐empirical models

Identifiers

PMID42557833
PMCPMC13555659

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.