Evidence map›Paper›PMID 40791150›Full record

ReviewAdvanced science (Weinheim, Baden-Wurttemberg, Germany)2025

Advances in High-Entropy Catalysts for Lithium-Sulfur Batteries: Design Principles, Recent Progress, and Prospects.

Ruohan Hou, Yixin Wei, Jiaxiang Zhang, Jiaying Chen, Shaojie Chen, Shuaiting Sun, Guosheng Shao, Peng Zhang

Abstract readReview
In one paragraph

Review in Advanced science (Weinheim, Baden-Wurttemberg, Germany), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
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.

Ruohan HouState Center for International Cooperation on Designer Low-carbon & Environmental Materials (CDLCEM), School of Materials Science and Engineering, Zhengzhou University, 100 Kexue Avenue, Zhengzhou, 450001, China.
Yixin WeiState Center for International Cooperation on Designer Low-carbon & Environmental Materials (CDLCEM), School of Materials Science and Engineering, Zhengzhou University, 100 Kexue Avenue, Zhengzhou, 450001, China.
Jiaxiang ZhangState Center for International Cooperation on Designer Low-carbon & Environmental Materials (CDLCEM), School of Materials Science and Engineering, Zhengzhou University, 100 Kexue Avenue, Zhengzhou, 450001, China.
Jiaying ChenState Center for International Cooperation on Designer Low-carbon & Environmental Materials (CDLCEM), School of Materials Science and Engineering, Zhengzhou University, 100 Kexue Avenue, Zhengzhou, 450001, China.
Shaojie ChenState Center for International Cooperation on Designer Low-carbon & Environmental Materials (CDLCEM), School of Materials Science and Engineering, Zhengzhou University, 100 Kexue Avenue, Zhengzhou, 450001, China.
Shuaiting SunState Center for International Cooperation on Designer Low-carbon & Environmental Materials (CDLCEM), School of Materials Science and Engineering, Zhengzhou University, 100 Kexue Avenue, Zhengzhou, 450001, China.
Guosheng ShaoState Center for International Cooperation on Designer Low-carbon & Environmental Materials (CDLCEM), School of Materials Science and Engineering, Zhengzhou University, 100 Kexue Avenue, Zhengzhou, 450001, China.
Peng ZhangState Center for International Cooperation on Designer Low-carbon & Environmental Materials (CDLCEM), School of Materials Science and Engineering, Zhengzhou University, 100 Kexue Avenue, Zhengzhou, 450001, China.ORCID https://orcid.org/0000-0001-9505-3858

Funding

Central Plains Science and Technology Innovation Leading Talents 254000510052National Natural Science Foundation of China 51972287National Natural Science Foundation of China 52472110National Natural Science Foundation of China U2004172National Natural Science Foundation of Henan Province 242300421008Program for Science& Technology Innovation Talents in Universities of Henan Province 23HASTIT001
6 · The paper itself

Abstract

Lithium-sulfur (Li-S) batteries are regarded as one of the most promising next-generation energy storage technologies due to their exceptionally high theoretical energy density, cost-effectiveness, and environmental sustainability. Nevertheless, their practical deployment is significantly constrained by several challenges, including the intrinsic low conductivity of sulfur, the shuttle effect of lithium polysulfides (LiPS), sluggish redox kinetics, and instability of the Li anode. To overcome these limitations, the integration of catalytic materials has emerged as an effective strategy to accelerate sulfur redox reactions, promote LiPS conversion, and enhance cycling stability. Recently, high-entropy catalysts (HEC), comprising five or more metallic elements in near-equimolar ratios, have garnered increasing attention owing to their entropy-stabilized structures, abundant active sites, and tunable electronic properties. This review presents a comprehensive overview of the design principles, synthesis methods, and electrochemical applications of various HEC families, including high-entropy alloys, oxides, sulfides, nitrides, phosphides, MXenes, and Prussian blue analogues, in Li-S battery systems. The synergistic effects arising from multicomponent interactions, structural advantages, and underlying catalytic mechanisms are systematically discussed. Finally, key challenges such as scalable synthesis, in-depth mechanistic elucidation, and rational compositional design are addressed, along with future directions aimed at advancing high-performance HEC-based Li-S battery systems.

Indexed as

catalysthigh‐entropyLi–S batteriespolysulfide conversionshuttle effect

Identifiers

PMID40791150
PMCPMC12463023

What OpenQuestion holds

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LicenceCC BY
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.