Evidence map›Paper›PMID 38542871›Full record

ReviewMolecules (Basel, Switzerland)2024

Advances and Challenges in Electrolyte Development for Magnesium-Sulfur Batteries: A Comprehensive Review.

Lin Sheng, Junrun Feng, Manxi Gong, Lun Zhang, Jonathan Harding, Zhangxiang Hao, Feng Ryan Wang

Open access · goldAbstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Molecules (Basel, Switzerland), 2024. 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
2.9field-weighted citation impact, top 9% of its field
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, 14 citations in OpenAlex.

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

7 authors at 3 institutions in 2 countries.

Lin ShengSchool of Mechanical and Electronic Engineering, Suzhou University, Suzhou 234000, China.
Junrun FengSchool of Science, School of Chip Industry, Hubei University of Technology, Wuhan 430068, China.
Manxi GongMaterials and Catalysis Laboratory, Department of Chemical Engineering, University College London, London WC1E 7JE, UK.
Lun ZhangMaterials and Catalysis Laboratory, Department of Chemical Engineering, University College London, London WC1E 7JE, UK.
Jonathan HardingDepartment of Electrical Engineering and Electronics, University of Liverpool, Liverpool L69 3GJ, UK.
Zhangxiang HaoSchool of Science, School of Chip Industry, Hubei University of Technology, Wuhan 430068, China.
Feng Ryan WangMaterials and Catalysis Laboratory, Department of Chemical Engineering, University College London, London WC1E 7JE, UK.
University College London · GBHubei University of Technology · CNUniversity of Liverpool · GB

Funding

An-hui Province Higher Education Innovation Team: Key Technologies and Equipment Innovation Team for Clean Energy 2023AH010055China Scholarship Council 201908060125Hubei province High-level talent grantHubei University of Technology Startup fundSuzhou University Scientific Research Foundation Project 2023BSK056
6 · The paper itself

Abstract

Magnesium-sulfur batteries are an emerging technology. With their elevated theoretical energy density, enhanced safety, and cost-efficiency, they have the ability to transform the energy storage market. This review investigates the obstacles and progress made in the field of electrolytes which are especially designed for magnesium-sulfur batteries. The primary focus of the review lies in identifying electrolytes that can facilitate the reversible electroplating and stripping of Mg

Indexed as

batteryelectrolytemagnesium–sulfurnon-nucleophilicnucleophilic

Identifiers

PMID38542871
PMCPMC10976270
OpenAlexW4392659904

What OpenQuestion holds

Textmetadata
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.