Evidence map›Paper›PMID 40155395›Full record

ArticleNature communications2025

In-memory ferroelectric differentiator.

Guangdi Feng, Xiaoming Zhao, Xiaoyue Huang, Xiaoxu Zhang, Yangyang Wang, Wei Li, Luqiu Chen, Shenglan Hao, Qiuxiang Zhu, Yachin Ivry and 5 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 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. Article
  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

15 authors.

Guangdi Feng *Key Laboratory of Polar Materials and Device, Ministry of Education, Shanghai Center of Brain-inspired Intelligent Materials and Devices, Department of Electronics, East China Normal University, Shanghai, China.
Xiaoming Zhao *Key Laboratory of Polar Materials and Device, Ministry of Education, Shanghai Center of Brain-inspired Intelligent Materials and Devices, Department of Electronics, East China Normal University, Shanghai, China.
Xiaoyue Huang *Key Laboratory of Polar Materials and Device, Ministry of Education, Shanghai Center of Brain-inspired Intelligent Materials and Devices, Department of Electronics, East China Normal University, Shanghai, China.
Xiaoxu ZhangKey Laboratory of Polar Materials and Device, Ministry of Education, Shanghai Center of Brain-inspired Intelligent Materials and Devices, Department of Electronics, East China Normal University, Shanghai, China.
Yangyang WangKey Laboratory of Polar Materials and Device, Ministry of Education, Shanghai Center of Brain-inspired Intelligent Materials and Devices, Department of Electronics, East China Normal University, Shanghai, China.
Wei LiKey Laboratory of Polar Materials and Device, Ministry of Education, Shanghai Center of Brain-inspired Intelligent Materials and Devices, Department of Electronics, East China Normal University, Shanghai, China.
Luqiu ChenKey Laboratory of Polar Materials and Device, Ministry of Education, Shanghai Center of Brain-inspired Intelligent Materials and Devices, Department of Electronics, East China Normal University, Shanghai, China.
Shenglan HaoKey Laboratory of Polar Materials and Device, Ministry of Education, Shanghai Center of Brain-inspired Intelligent Materials and Devices, Department of Electronics, East China Normal University, Shanghai, China.
Qiuxiang ZhuKey Laboratory of Polar Materials and Device, Ministry of Education, Shanghai Center of Brain-inspired Intelligent Materials and Devices, Department of Electronics, East China Normal University, Shanghai, China.ORCID http://orcid.org/0000-0002-3515-315X
Yachin IvryDepartment of Materials Science and Engineering, Solid-State Institute, Technion-Israel Institute of Technology, Haifa, Israel.ORCID http://orcid.org/0000-0002-3045-923X
Brahim DkhilUniversité Paris-Saclay, CentraleSupélec, CNRS-UMR8580, Laboratoire SPMS, Paris, France.ORCID http://orcid.org/0000-0002-9862-625X
Bobo TianKey Laboratory of Polar Materials and Device, Ministry of Education, Shanghai Center of Brain-inspired Intelligent Materials and Devices, Department of Electronics, East China Normal University, Shanghai, China. bbtian@ee.ecnu.edu.cn.ORCID http://orcid.org/0000-0002-4251-2755
Peng ZhouState Key Laboratory of Integrated Chip and Systems, School of Microelectronics, Frontier Institute of Chip and System, Fudan University, Shanghai, China. pengzhou@fudan.edu.cn.ORCID http://orcid.org/0000-0002-7301-1013
Junhao ChuKey Laboratory of Polar Materials and Device, Ministry of Education, Shanghai Center of Brain-inspired Intelligent Materials and Devices, Department of Electronics, East China Normal University, Shanghai, China.
Chungang DuanKey Laboratory of Polar Materials and Device, Ministry of Education, Shanghai Center of Brain-inspired Intelligent Materials and Devices, Department of Electronics, East China Normal University, Shanghai, China. cgduan@clpm.ecnu.edu.cn.ORCID http://orcid.org/0000-0002-5380-4980

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Differential calculus is the cornerstone of many disciplines, spanning the breadth of modern mathematics, physics, computer science, and engineering. Its applications are fundamental to theoretical progress and practical solutions. However, the current state of digital differential technology often requires complex implementations, which struggle to meet the extensive demands of the ubiquitous edge computing in the intelligence age. To face these challenges, we propose an in-memory differential computation that capitalizes on the dynamic behavior of ferroelectric domain reversal to efficiently extract information differences. This strategy produces differential information directly within the memory itself, which considerably reduces the volume of data transmission and operational energy consumption. We successfully illustrate the effectiveness of this technique in a variety of tasks, including derivative function solving, the moving object extraction and image discrepancy identification, using an in-memory differentiator constructed with a crossbar array of 1600-unit ferroelectric polymer capacitors. Our research offers an efficient hardware analogue differential computing, which is crucial for accelerating mathematical processing and real-time visual feedback systems.

Identifiers

PMID40155395
PMCPMC11953435

What OpenQuestion holds

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Registered trials

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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.