Evidence map›Paper›PMID 39887793›Full record

ArticleAdvanced materials (Deerfield Beach, Fla.)2025

Vertical Memristive Crossbar Array for Multilayer Graph Embedding and Analysis.

Janguk Han, Yoon Ho Jang, Ji Won Moon, Sung Keun Shim, Sunwoo Cheong, Soo Hyung Lee, Tae Won Park, Joon-Kyu Han, Cheol Seong Hwang

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In one paragraph

Article in Advanced materials (Deerfield Beach, Fla.), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

9 authors.

Janguk HanDepartment of Materials Science and Engineering and Inter-university Semiconductor Research Center, College of Engineering, Seoul National University, Seoul, 08826, Republic of Korea.ORCID https://orcid.org/0009-0000-1588-1005
Yoon Ho JangDepartment of Materials Science and Engineering and Inter-university Semiconductor Research Center, College of Engineering, Seoul National University, Seoul, 08826, Republic of Korea.
Ji Won MoonDepartment of Materials Science and Engineering and Inter-university Semiconductor Research Center, College of Engineering, Seoul National University, Seoul, 08826, Republic of Korea.
Sung Keun ShimDepartment of Materials Science and Engineering and Inter-university Semiconductor Research Center, College of Engineering, Seoul National University, Seoul, 08826, Republic of Korea.
Sunwoo CheongDepartment of Materials Science and Engineering and Inter-university Semiconductor Research Center, College of Engineering, Seoul National University, Seoul, 08826, Republic of Korea.
Soo Hyung LeeDepartment of Materials Science and Engineering and Inter-university Semiconductor Research Center, College of Engineering, Seoul National University, Seoul, 08826, Republic of Korea.
Tae Won ParkDepartment of Materials Science and Engineering and Inter-university Semiconductor Research Center, College of Engineering, Seoul National University, Seoul, 08826, Republic of Korea.
Joon-Kyu HanSystem Semiconductor Engineering and Department of Electronic Engineering, Sogang University, 35 Baekbeom-ro, Mapo-gu, Seoul, 04107, Republic of Korea.
Cheol Seong HwangDepartment of Materials Science and Engineering and Inter-university Semiconductor Research Center, College of Engineering, Seoul National University, Seoul, 08826, Republic of Korea.ORCID https://orcid.org/0000-0002-6254-9758

Funding

National Research Foundation of Korea 2020R1A3B2079882
6 · The paper itself

Abstract

Graph data structures effectively represent objects and their relationships, enabling the modeling of complex connections in various fields. Recent work demonstrate that metal at diagonal crossbar arrays (m-CBA) can effectively represent planar graphs. However, they are unsuitable for representing multilayer graphs having multiple relationships across different layers. Using conventional software, embedding multilayer graphs in high-dimensional Euclidean spaces introduces significant mathematical complexity and computational burden, often resulting in information loss. This study proposes a unique graph embedding (mapping) method utilizing a fabricated vertical m-CBA (vm-CBA), where a custom-built measurement system thoroughly validated its functionality. This structure directly maps multilayer graphs into a 3D vm-CBA, accurately representing inter-layer and intra-layer connections. The practical link prediction and information scores across various real-world datasets demonstrated that vm-CBA achieved enhanced accuracy compared to conventional embeddings, even with a significantly decreased number of operations.

Indexed as

graph data structuregraph embeddinglink predictionmultilayer graphself‐rectifying memritstor

Identifiers

PMID39887793
PMCPMC11899525

What OpenQuestion holds

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LicenceCC BY-NC-ND
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.