Evidence map›Paper›PMID 41089064›Full record

ArticleAdvanced materials (Deerfield Beach, Fla.)2025

HZO/HSO Superlattice ReFET Array Integrating Optical Sensing for Neuromorphic Vision Computing.

Bingjie Dang, Kaixuan Sun, Hanxin Su, Jiaxin Chen, Pengyu Yao, Tao Zeng, Shu Shi, Guowei Zhou, Liang Liu, Xiaohong Xu and 1 more

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PubMed Full text at PMC Publisher
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 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Review
  3. 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.

Bingjie DangDepartment of Materials Science and Engineering, National University of Singapore, Singapore, 117575, Singapore.
Kaixuan SunDepartment of Materials Science and Engineering, National University of Singapore, Singapore, 117575, Singapore.
Hanxin SuDepartment of Materials Science and Engineering, National University of Singapore, Singapore, 117575, Singapore.
Jiaxin ChenTsung-Dao Lee Institute, Key Laboratory of Artificial Structures and Quantum Control (Ministry of Education), School of Physics and Astronomy, Shanghai Jiao Tong University, Shanghai, 200240, China.
Pengyu YaoDepartment of Materials Science and Engineering, National University of Singapore, Singapore, 117575, Singapore.
Tao ZengDepartment of Materials Science and Engineering, National University of Singapore, Singapore, 117575, Singapore.
Shu ShiDepartment of Materials Science and Engineering, National University of Singapore, Singapore, 117575, Singapore.
Guowei ZhouSchool of Chemistry and Materials Science of Shanxi Normal University, Taiyuan, 030031, China.
Liang LiuTsung-Dao Lee Institute, Key Laboratory of Artificial Structures and Quantum Control (Ministry of Education), School of Physics and Astronomy, Shanghai Jiao Tong University, Shanghai, 200240, China.
Xiaohong XuSchool of Chemistry and Materials Science of Shanxi Normal University, Taiyuan, 030031, China.
Jingsheng ChenDepartment of Materials Science and Engineering, National University of Singapore, Singapore, 117575, Singapore.ORCID https://orcid.org/0000-0003-3188-2803

Funding

National Research Foundation NRFI10-2024-0013Science and Technology Support Program of Jiangsu Province BZ2022056
6 · The paper itself

Abstract

Neuromorphic vision systems require artificial synapses that integrate sensing, memory, and computation with high precision and stability. Conventional memristors face limitations including forming requirements, few multilevel states, low endurance, and poor integration density, while ferroelectric and flash-based transistors suffer trade-offs among endurance, retention, and switching ratio, and generally lack intrinsic photonic sensitivity, constraining in-sensor computing. Here, a photonic resistive-gate field-effect transistor (ReFET) array is presented that combines optical sensing, forming-free multilevel memory, and analog computation in a single device. The ReFET employs a Hf

Indexed as

in‐sensor computingmemristorneuromorphic computingReFETvision transformer

Identifiers

PMID41089064
PMCPMC12710600

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.