Evidence map›Paper›PMID 42487614›Full record

ArticleAdvanced materials (Deerfield Beach, Fla.)2026

Direct Modeling of the Interfacial Resistance in All-Solid-State Battery.

Da Wang, Yaqiao Luo, Jia Yu, Gaozhan Liu, Jianfang Wu, Xiaobin Yin, Bingxu Chen, Wenzhi Zhang, Xiayin Yao, Maxim Avdeev and 2 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Advanced materials (Deerfield Beach, Fla.), 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

12 authors.

Da WangState Key Laboratory of Materials for Advanced Nuclear Energy, School of Materials Science and Engineering, and Materials Genome Institute, Shanghai University, Shanghai, China.ORCID https://orcid.org/0000-0002-4512-7860
Yaqiao LuoState Key Laboratory of Materials for Advanced Nuclear Energy, School of Materials Science and Engineering, and Materials Genome Institute, Shanghai University, Shanghai, China.
Jia YuState Key Laboratory of Materials for Advanced Nuclear Energy, School of Materials Science and Engineering, and Materials Genome Institute, Shanghai University, Shanghai, China.ORCID https://orcid.org/0000-0002-4766-8054
Gaozhan LiuNingbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo, China.
Jianfang WuCollege of Materials Science and Engineering, Hunan University, Changsha, China.ORCID https://orcid.org/0000-0002-2414-4979
Xiaobin YinState Key Laboratory of Materials for Advanced Nuclear Energy, School of Materials Science and Engineering, and Materials Genome Institute, Shanghai University, Shanghai, China.
Bingxu ChenState Key Laboratory of Materials for Advanced Nuclear Energy, School of Materials Science and Engineering, and Materials Genome Institute, Shanghai University, Shanghai, China.
Wenzhi ZhangState Key Laboratory of Materials for Advanced Nuclear Energy, School of Materials Science and Engineering, and Materials Genome Institute, Shanghai University, Shanghai, China.
Xiayin YaoNingbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo, China.ORCID https://orcid.org/0000-0002-2224-4247
Maxim AvdeevSchool of Chemistry, The University of Sydney, Sydney, NSW, Australia.
Liquan ChenBeijing National Laboratory for Condensed Matter Physics, Institute of Physics, Chinese Academy of Sciences, Beijing, China.
Siqi ShiState Key Laboratory of Materials for Advanced Nuclear Energy, School of Materials Science and Engineering, and Materials Genome Institute, Shanghai University, Shanghai, China.ORCID https://orcid.org/0000-0001-8988-9763

Funding

Advanced Materials National Science and Technology Major Project 2025ZD0618801National Natural Science Foundation of China 22279077National Natural Science Foundation of China 52372208National Natural Science Foundation of China 52472223National Natural Science Foundation of China 92472207
6 · The paper itself

Abstract

Interfacial reconstruction and its associated high resistance govern the performance of all-solid-state batteries (ASSBs). However, indirectly inferring interfacial potentials from bulk band alignments masks the true solid-solid electrochemistry, causing orders-of-magnitude discrepancies in predicting space-charge layer (SCL) resistances and impeding interface screening. Herein, by traversing 310 distinct interfaces from ∼29,000 literatures, we develop a non-empirical numerical procedure that directly maps lithium‑ion redistribution to interfacial resistance by integrating ligand‑field theory with the SCL model. Considering electric potential differences and intrinsic carrier properties during interfacial reconstruction via a modified ligand-field splitting strength (MLFSS) descriptor yields unprecedented bridging between modeling and measurement, reducing predicted resistance discrepancies from over ten orders of magnitude to within two. On this basis, we resolve the highly system-dependent controversy over oxide interfacial resistances by identifying extreme MLFSS disparities (>3.5 eV) as the decisive factor, while emphasizing ion‑intercalation sulfides (<0.2 eV) as cathodes for their intrinsic SCL suppression. The predictive capability of this tunable criterion is validated in an all-sulfide V

Indexed as

all‐solid‐state batteryelectronic structureinterfacial resistanceligand‑field theoryspace‐charge layer

Identifiers

PMID42487614
PMCPMC13532437

What OpenQuestion holds

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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.