Evidence map›Paper›PMID 42201612›Full record

ArticleNano-micro letters2026

Breaking the Limitations of Sulfur Redox Kinetics by Accelerated Li

Tan Wang, Zhenhua Wang, Xiaotian Gao, Zhe Bai, Wanning Liu, Yu Bai, David Rooney, Kening Sun

Abstract read
In one paragraph

Article in Nano-micro letters, 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

8 authors.

Tan WangBeijing Key Laboratory of Green Hydrogen and Fuel Cells, School of Chemistry and Chemical Engineering, Beijing Institute of Technology, Beijing, 100081, People's Republic of China.
Zhenhua WangBeijing Key Laboratory of Green Hydrogen and Fuel Cells, School of Chemistry and Chemical Engineering, Beijing Institute of Technology, Beijing, 100081, People's Republic of China. wangzh@bit.edu.cn.
Xiaotian GaoBeijing Key Laboratory of Green Hydrogen and Fuel Cells, School of Chemistry and Chemical Engineering, Beijing Institute of Technology, Beijing, 100081, People's Republic of China.
Zhe BaiBeijing Key Laboratory of Green Hydrogen and Fuel Cells, School of Chemistry and Chemical Engineering, Beijing Institute of Technology, Beijing, 100081, People's Republic of China.
Wanning LiuBeijing Key Laboratory of Green Hydrogen and Fuel Cells, School of Chemistry and Chemical Engineering, Beijing Institute of Technology, Beijing, 100081, People's Republic of China.
Yu BaiBeijing Key Laboratory of Green Hydrogen and Fuel Cells, School of Chemistry and Chemical Engineering, Beijing Institute of Technology, Beijing, 100081, People's Republic of China.
David RooneySchool of Chemistry and Chemical Engineering, Queen's University Belfast, Belfast, Northern Ireland, BT9 5AG, UK. d.rooney@qub.ac.uk.
Kening SunBeijing Key Laboratory of Green Hydrogen and Fuel Cells, School of Chemistry and Chemical Engineering, Beijing Institute of Technology, Beijing, 100081, People's Republic of China. sunkn@bit.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The practical deployment of lithium-sulfur batteries (LSBs) is fundamentally limited by the sluggish stepwise sulfur redox kinetics. However, current design philosophies remain heavily constrained by the conventional "adsorption-catalysis" strategy, often overlooking the crucial rate-limiting kinetic obstacle of the high Li

Indexed as

Catalyst desolvationDesolvation energy barrierLithium−sulfur batteriesSingle-atom catalystsSulfur redox kinetics

Identifiers

PMID42201612
PMCPMC13216370

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.