Evidence map›Paper›PMID 41395534›Full record

ReviewSmall science2025

Graphene-Based Liquid Cell Designs for In Situ Liquid-Phase Transmission Electron Microscopy: Recent Developments and Perspectives.

Hyeonjong Ma, Hyeongseung Kim, Jiwoong Yang

Abstract readReview
In one paragraph

Review in Small science, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. 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

3 authors.

Hyeonjong MaDepartment of Energy Science and Engineering Daegu Gyeongbuk Institute of Science and Technology (DGIST) Daegu 42988 Republic of Korea.ORCID https://orcid.org/0000-0002-5057-3152
Hyeongseung KimDepartment of Energy Science and Engineering Daegu Gyeongbuk Institute of Science and Technology (DGIST) Daegu 42988 Republic of Korea.ORCID https://orcid.org/0009-0005-6534-6429
Jiwoong YangDepartment of Energy Science and Engineering Daegu Gyeongbuk Institute of Science and Technology (DGIST) Daegu 42988 Republic of Korea.ORCID https://orcid.org/0000-0002-2346-8197

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Recent advances in liquid-phase transmission electron microscopy (TEM) have enabled the direct visualization of reaction pathways of nanomaterials, providing critical insights into diverse nanoscale processes such as crystallization, phase transition, shape transformation, etching, and nanoparticle motions. Among various liquid cells, graphene liquid cells (GLCs) are particularly advantageous due to the intrinsic properties of graphene-high electrical and thermal conductivity, exceptional mechanical flexibility, and radical scavenging effects-which allow atomic-scale spatial resolution and enhanced imaging stability. This review article highlights the recent progress in GLC-based liquid-phase TEM, focusing on the evolution of structural designs, including veil-type, well-type, liquid-flowing-type, and mixing-type GLCs. Each configuration offers unique advantages tailored to observing distinct types of nanoscale dynamic processes. These studies have elucidated both classical reaction pathways and complex, nonclassical mechanisms involving transient intermediates. Overall, this review highlights how developments in GLC designs have significantly advanced the capabilities of in situ liquid-phase TEM, providing unprecedented opportunities to study nanoscale processes at atomic resolution.

Indexed as

cell designgraphene liquid cellsin situ transmission electron microscopyliquid‐phase transmission electron microscopynanoscale dynamics

Identifiers

PMID41395534
PMCPMC12697908

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.