Evidence map›Paper›PMID 41422265›Full record

ArticleNature communications2025

Single atom Ru-supported reduced graphene oxide integrated self-assembled monolayer as a nm-scale Cu diffusion barrier.

Sibo Zhao, Dewei Zhang, Guoxiang Cui, Xiangyu Ren, Shenghong Ju, Tao Hang, Ming Li, Yunwen Wu

Abstract read
In one paragraph

Article in Nature communications, 2025. 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.

Sibo ZhaoSchool of Material Science and Engineering, Shanghai Jiao Tong University, Shanghai, China.ORCID http://orcid.org/0009-0009-5818-2170
Dewei ZhangChina-UK Low Carbon College, Shanghai Jiao Tong University, Shanghai, China.
Guoxiang CuiSchool of Material Science and Engineering, Shanghai Jiao Tong University, Shanghai, China.
Xiangyu RenSchool of Material Science and Engineering, Shanghai Jiao Tong University, Shanghai, China.
Shenghong JuChina-UK Low Carbon College, Shanghai Jiao Tong University, Shanghai, China. jush@tsinghua.edu.cn.
Tao HangSchool of Material Science and Engineering, Shanghai Jiao Tong University, Shanghai, China.
Ming LiSchool of Material Science and Engineering, Shanghai Jiao Tong University, Shanghai, China.
Yunwen WuSchool of Material Science and Engineering, Shanghai Jiao Tong University, Shanghai, China. tlwuyunwen@sjtu.edu.cn.

Funding

National Natural Science Foundation of China (National Science Foundation of China) 22472095Shanghai International Science and Technology 24160712600Shanghai Municipal Education Commission 2024AIZD012
6 · The paper itself

Abstract

In advanced integrated circuits, signal transmission delay arising from interconnect resistance is a main problem hindering the development of electronic devices, while the conventional several-nanometer-thick TaN/Ta barrier with high resistivity causes a surge in interconnect resistance due to the size effect. To address this issue, it is crucial to develop Cu barrier materials. Here, we design an integrated ultra-thin Cu diffusion barrier (~1.4 nm) consisting of single-atom Ru-supported reduced graphene oxide (Ru SA-rGO) and self-assembled monolayer (SAM) derived from (3-aminopropyl)triethoxysilane, which combines the dual functions of liner and barrier. The supporting of Ru requires N-doping as a bridge. Remarkably, the mean time-to-failure of devices with Ru SA-rGO/SAM is approximately 24 times longer than barrier-free devices. Ru atoms can both physically block Cu diffusion by filling rGO vacancies and chemically capture Cu through enhanced adsorption. Our work provides insight into diffusion barrier development in advanced Cu interconnects.

Identifiers

PMID41422265
PMCPMC12830982

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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.