Evidence map›Paper›PMID 39222040›Full record

ArticleACS applied materials & interfaces2024

Unraveling the Deposition and Dissolution Behavior of the Ag-Modified Li Surface Based on Electrochemical Atomic Force Microscopy.

Weerawat To-A-Ran, Naila Riaz Mastoi, Young Jae Song, Seong Heon Kim, Young-Jun Kim

Abstract read
In one paragraph

Article in ACS applied materials & interfaces, 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
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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

5 authors.

Weerawat To-A-RanSKKU Advanced Institute of Nano Technology (SAINT), Sungkyunkwan University, Suwon 16419, Republic of Korea.ORCID 0000-0002-1719-5137
Naila Riaz MastoiSKKU Advanced Institute of Nano Technology (SAINT), Sungkyunkwan University, Suwon 16419, Republic of Korea.
Young Jae SongSKKU Advanced Institute of Nano Technology (SAINT), Sungkyunkwan University, Suwon 16419, Republic of Korea.ORCID 0000-0001-6172-3817
Seong Heon KimDepartment of Physics, Jeonbuk National University, Jeonju 54896, Republic of Korea.ORCID 0000-0001-6054-2109
Young-Jun KimSKKU Advanced Institute of Nano Technology (SAINT), Sungkyunkwan University, Suwon 16419, Republic of Korea.ORCID 0000-0002-9801-3066

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Lithium is a promising anode material for advanced batteries because of its high capacity and low redox potential. However, its practical use is hindered by nonuniform Li deposition and dendrite formation, leading to safety concerns in Li metal batteries. Our study shows that Ag-based materials enhance the uniformity of Li deposition on Ag-modified Li (AgLi) surfaces, thereby addressing these key challenges. This improvement is due to the strong affinity of Ag for Li, which promotes uniform deposition and dissolution. Additionally, the AgLi surface demonstrated an improved cycling stability, which is crucial for long-term battery reliability. Emphasizing our analytical approach, we utilized comprehensive techniques such as Kelvin probe force microscopy (KPFM) and electrochemical atomic force microscopy (EC-AFM) to locally analyze the electrical properties and unravel the Li deposition/dissolution mechanisms. KPFM analysis provided crucial insights into surface potential variations, while EC-AFM highlighted topographical changes during the Li deposition and dissolution processes, contributing significantly to the development of safer and more efficient Li metal batteries.

Indexed as

EC-AFMLi depositionLi metal anodesnucleation sitessurface potential

Identifiers

PMID39222040
PMCPMC11404483

What OpenQuestion holds

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Registered trials

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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.