Evidence map›Paper›PMID 41027886›Full record

ArticleNature communications2025

Chip-scale reconfigurable carbon nanotube physical unclonable functions.

Yang Liu, Jingfang Pei, Yingyi Wen, Lekai Song, Songwei Liu, Pengyu Liu, Wenyu Cui, Zihan Liang, Teng Ma, Xiaolong Chen and 1 more

Abstract read
PubMed Full text at PMC Publisher
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. 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

11 authors.

Yang Liu *Department of Electronic Engineering, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong SAR, China.
Jingfang Pei *Department of Electronic Engineering, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong SAR, China.
Yingyi WenDepartment of Electronic Engineering, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong SAR, China.
Lekai SongDepartment of Electronic Engineering, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong SAR, China.
Songwei LiuDepartment of Electronic Engineering, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong SAR, China.
Pengyu LiuDepartment of Electronic Engineering, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong SAR, China.ORCID http://orcid.org/0009-0008-9910-5932
Wenyu CuiDepartment of Applied Physics, Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong SAR, China.ORCID http://orcid.org/0000-0003-1558-2093
Zihan LiangDepartment of Electrical and Electronic Engineering, Southern University of Science and Technology, Shenzhen, China.
Teng MaDepartment of Applied Physics, Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong SAR, China.ORCID http://orcid.org/0000-0001-7942-9501
Xiaolong ChenDepartment of Electrical and Electronic Engineering, Southern University of Science and Technology, Shenzhen, China.ORCID http://orcid.org/0000-0001-6208-3161
Guohua HuDepartment of Electronic Engineering, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong SAR, China. ghhu@ee.cuhk.edu.hk.ORCID http://orcid.org/0000-0001-9296-1236

Funding

Innovation and Technology Commission (ITF) ITS/150/23FPResearch Grants Council, University Grants Committee (RGC, UGC) 15306824Research Grants Council, University Grants Committee (RGC, UGC) 24200521
6 · The paper itself

Abstract

With the rapid advancement of edge intelligence, ensuring the security of edge devices and protecting their communication has become critical. Physical unclonable functions, known as hardware fingerprints, are an emerging hardware security solution enabled with the physical variations inherent in the hardware systems. To facilitate a widespread edge deployment, here we present chip-scale reconfigurable physical unclonable functions built with carbon nanotube charge-trapping transistors, where the charge-trapping memory and physical variations of the transistors are harnessed to render over 10

Identifiers

PMID41027886
PMCPMC12484790

What OpenQuestion holds

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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.