Evidence map›Paper›PMID 40428709›Full record

ArticleMicromachines2025

Deep Learning Method for Breakdown Voltage and Forward

Hao Zhou, Xiang Wang, Shulong Wang, Chenyu Liu, Dongliang Chen, Jiarui Li, Lan Ma, Guohao Zhang

Abstract read
In one paragraph

Article in Micromachines, 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.

Hao ZhouSchool of Microelectronics, Xidian University, Xi'an 710071, China.ORCID 0009-0007-0248-0457
Xiang WangSchool of Information Engineering, Guangdong University of Technology, Guangzhou 510006, China.
Shulong WangSchool of Microelectronics, Xidian University, Xi'an 710071, China.ORCID 0000-0002-8560-2478
Chenyu LiuSchool of Microelectronics, Xidian University, Xi'an 710071, China.ORCID 0009-0006-7784-5230
Dongliang ChenSchool of Microelectronics, Xidian University, Xi'an 710071, China.
Jiarui LiSchool of Microelectronics, Xidian University, Xi'an 710071, China.
Lan MaSchool of Microelectronics, Xidian University, Xi'an 710071, China.
Guohao ZhangSchool of Information Engineering, Guangdong University of Technology, Guangzhou 510006, China.

Funding

the National Natural Science Foundation of China No.U2241221 and 61904147
6 · The paper itself

Abstract

This work employs a deep learning method to develop a high-precision model for predicting the breakdown voltage (

Indexed as

breakdown voltagedeep learningneural networkSiC

Identifiers

PMID40428709
PMCPMC12113801

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.