Evidence map›Paper›PMID 42412275›Full record

ArticleNano-micro letters2026

Flexible Dual-Modal Sensing Transistor Enabled by Deep Learning Decoupling for Independent Light and Temperature Reconstruction.

Shilin Lu, Ji Hoon Han, Dong Keun Lee, Sun Min Song, Huixin Yu, Sujin Jung, Lu Zhang, Zhao Yao, Jong Bin An, Hyun Jae Kim

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Nano-micro letters, 2026. 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

10 authors.

Shilin LuSchool of Electrical and Electronic Engineering, Yonsei University, Seoul, 03722, Republic of Korea.
Ji Hoon HanSchool of Electrical and Electronic Engineering, Yonsei University, Seoul, 03722, Republic of Korea.
Dong Keun LeeDepartment of Integrated Display Engineering, Yonsei University, Seoul, 03722, Republic of Korea.
Sun Min SongSchool of Electrical and Electronic Engineering, Yonsei University, Seoul, 03722, Republic of Korea.
Huixin YuCollege of Electronic and Information, Qingdao University, Qingdao, 266071, People's Republic of China.
Sujin JungSchool of Electrical and Electronic Engineering, Yonsei University, Seoul, 03722, Republic of Korea.
Lu ZhangSchool of Electrical and Electronic Engineering, Yonsei University, Seoul, 03722, Republic of Korea.
Zhao YaoCollege of Electronic and Information, Qingdao University, Qingdao, 266071, People's Republic of China.
Jong Bin AnSchool of Electrical and Electronic Engineering, Yonsei University, Seoul, 03722, Republic of Korea. jongbin1996@yonsei.ac.kr.
Hyun Jae KimSchool of Electrical and Electronic Engineering, Yonsei University, Seoul, 03722, Republic of Korea. hjk3@yonsei.ac.kr.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Herein, a flexible dual-modal sensing transistor (FDST) is reported, based on zinc oxide nanofibers (ZnO NFs) integrated onto an indium-gallium-zinc-oxide thin-film transistor, and combined with a deep learning-based signal decoupling strategy. Defect-mediated subgap excitation and thermally activated interfacial potential modulation enable high sensitivity dual-modal responses, delivering a broadband photoresponsivity (

Indexed as

Deep learningFlexible electronicsLight-temperature dual-modal sensingThin-film transistorsWearable systems

Identifiers

PMID42412275
PMCPMC13342015

What OpenQuestion holds

Textmetadata
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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.