Evidence map›Paper›PMID 42103760›Full record

ArticleNature communications2026

CMOS-compatible ferroelectric tunnel junctions integrate stochastic sampling and deterministic computing for image generation.

Ryun-Han Koo, Jonghyun Ko, Wonjun Shin, Sangwoo Ryu, Jiseong Im, Sung-Ho Park, Joon Hwang, Minsuk Song, Youngchan Cho, Jangsaeng Kim and 3 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Nature communications, 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

13 authors.

Ryun-Han Koo *Department of Electrical and Computer Engineering and Inter-university Semiconductor Research Center, Seoul National University, Seoul, Republic of Korea.ORCID http://orcid.org/0000-0002-5708-3308
Jonghyun Ko *Department of Electrical and Computer Engineering and Inter-university Semiconductor Research Center, Seoul National University, Seoul, Republic of Korea.
Wonjun Shin *Department of Semiconductor Convergence Engineering, Sungkyunkwan University, Suwon, Republic of Korea.ORCID http://orcid.org/0000-0001-9122-2458
Sangwoo RyuDepartment of Electrical and Computer Engineering and Inter-university Semiconductor Research Center, Seoul National University, Seoul, Republic of Korea.
Jiseong ImDepartment of Electrical and Computer Engineering and Inter-university Semiconductor Research Center, Seoul National University, Seoul, Republic of Korea.ORCID http://orcid.org/0000-0002-7260-9224
Sung-Ho ParkDepartment of Electrical and Computer Engineering and Inter-university Semiconductor Research Center, Seoul National University, Seoul, Republic of Korea.ORCID http://orcid.org/0000-0001-7416-1059
Joon HwangDepartment of Electrical and Computer Engineering and Inter-university Semiconductor Research Center, Seoul National University, Seoul, Republic of Korea.ORCID http://orcid.org/0000-0003-2998-8174
Minsuk SongDepartment of Nanoscale Semiconductor Engineering, Hanyang University, Seoul, Republic of Korea.
Youngchan ChoDepartment of Semiconductor Convergence Engineering, Sungkyunkwan University, Suwon, Republic of Korea.ORCID http://orcid.org/0009-0004-2796-9396
Jangsaeng KimDepartment of Electronic Engineering, Sogang University, Seoul, Republic of Korea.ORCID http://orcid.org/0000-0003-4519-135X
Gyuweon JungDepartment of Electrical and Computer Engineering and Inter-university Semiconductor Research Center, Seoul National University, Seoul, Republic of Korea.ORCID http://orcid.org/0000-0003-0357-0933
Daewoong KwonDepartment of Nanoscale Semiconductor Engineering, Hanyang University, Seoul, Republic of Korea.
Jong-Ho LeeDepartment of Electrical and Computer Engineering and Inter-university Semiconductor Research Center, Seoul National University, Seoul, Republic of Korea. jhl@snu.ac.kr.ORCID http://orcid.org/0000-0003-3559-9802

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Recent progress in generative modeling has intensified the need for compact, energy-efficient hardware platforms. Yet, implementing image generation directly in hardware remains challenging due to the conflicting requirements of stochastic latent space sampling and deterministic decoding. Here, we show a unified hardware framework based on hafnium-oxide ferroelectric tunnel junctions (FTJs) that intrinsically support both functionalities within a single device array. Leveraging the CMOS- and VLSI-compatible fabrication of hafnia ferroelectrics, we realize dual-mode operation: random telegraph noise generation for controllable stochastic sampling, and high-fidelity vector-matrix multiplication enabled by non-volatile multi-level conductance states. Voltage and sampling-time tuning provide fine control over randomness and reliability, enabling high-quality image generation for tasks such as handwritten digit synthesis (MNIST) and high-resolution facial image generation (CelebA). Circuit-level demonstrations confirm stable performance over 10

Identifiers

PMID42103760
PMCPMC13369162

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.