Evidence map›Paper›PMID 38628354›Full record

ArticleResearch (Washington, D.C.)2024

Laser-Guided, Self-Confined Graphitization for High-Conductivity Embedded Electronics.

Haiyang Yu, Jing Bian, Furong Chen, Kan Li, YongAn Huang

Abstract read
In one paragraph

Article in Research (Washington, D.C.), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
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  4. Review
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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.

Haiyang YuState Key Laboratory of Intelligent Manufacturing Equipment and Technology, Huazhong University of Science and Technology, Wuhan 430074, China.
Jing BianState Key Laboratory of Intelligent Manufacturing Equipment and Technology, Huazhong University of Science and Technology, Wuhan 430074, China.
Furong ChenState Key Laboratory of Intelligent Manufacturing Equipment and Technology, Huazhong University of Science and Technology, Wuhan 430074, China.
Kan LiState Key Laboratory of Intelligent Manufacturing Equipment and Technology, Huazhong University of Science and Technology, Wuhan 430074, China.
YongAn HuangState Key Laboratory of Intelligent Manufacturing Equipment and Technology, Huazhong University of Science and Technology, Wuhan 430074, China.ORCID https://orcid.org/0000-0001-7713-8380

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Facile fabrication of highly conductive and self-encapsulated graphene electronics is in urgent demand for carbon-based integrated circuits, field effect transistors, optoelectronic devices, and flexible sensors. The current fabrication of these electronic devices is mainly based on layer-by-layer techniques (separate circuit preparation and encapsulation procedures), which show multistep fabrication procedures, complicated renovation/repair procedures, and poor electrical property due to graphene oxidation and exfoliation. Here, we propose a laser-guided interfacial writing (LaserIW) technique based on self-confined, nickel-catalyzed graphitization to directly fabricate highly conductive, embedded graphene electronics inside multilayer structures. The doped nickel is used to induce chain carbonization, which firstly enhances the photothermal effect to increase the confined temperature for initial carbonization, and the generated carbon further increases the light-absorption capacity to fabricate high-quality graphene. Meanwhile, the nickel atoms contribute to the accelerated connection of carbon atoms. This interfacial carbonization inherently avoids the exfoliation and oxidation of the as-formed graphene, resulting in an 8-fold improvement in electrical conductivity (~20,000 S/m at 7,958 W/cm

Identifiers

PMID38628354
PMCPMC11020139

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

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.