Evidence map›Paper›PMID 41810068›Full record

ArticleExploration (Beijing, China)2026

An Analogue Memristor Based on Conjugated Porous Polymer Composite for Artificial Synapse.

Haotian Hao, Xiong Jiao, Guangdong Zhou, Lin Chen, Mixue Wang, Jintao He, Xiaochen Lang, Jiyun Zhang, Linlin Shi, Meiwen An and 3 more

Abstract read
In one paragraph

Article in Exploration (Beijing, China), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

13 authors.

Haotian HaoDepartment of Biomedical Engineering College of Artificial Intelligence Taiyuan University of Technology Taiyuan China.
Xiong JiaoDepartment of Biomedical Engineering College of Artificial Intelligence Taiyuan University of Technology Taiyuan China.
Guangdong ZhouCollege of Artificial Intelligence Chongqing Key Laboratory of Brain-inspired Computing and Intelligent Chips MOE Key Laboratory of Luminescence Analysis and Molecular Sensors Southwest University Chongqing China.
Lin ChenKey Laboratory of Interface Science and Engineering in Advanced Materials Ministry of Education Taiyuan University of Technology Taiyuan China.
Mixue WangAcademy of Medical Sciences Shanxi Medical University Taiyuan China.
Jintao HeKey Laboratory of Interface Science and Engineering in Advanced Materials Ministry of Education Taiyuan University of Technology Taiyuan China.
Xiaochen LangKey Laboratory of Interface Science and Engineering in Advanced Materials Ministry of Education Taiyuan University of Technology Taiyuan China.
Jiyun ZhangFaculty of Engineering Department of Material Science Friedrich-Alexander-University Erlangen-Nuremberg Institute of Materials for Electronics and Energy Technology Erlangen Germany.ORCID https://orcid.org/0000-0001-6939-4771
Linlin ShiCollege of Physics and Optoelectronics Shanxi Key Lab of Photovoltaic Technology and Application Key Lab of Advanced Transducers and Intelligent Control System Ministry of Education Taiyuan University of Technology Taiyuan China.
Meiwen AnDepartment of Biomedical Engineering College of Artificial Intelligence Taiyuan University of Technology Taiyuan China.
Lingpeng YanKey Laboratory of Interface Science and Engineering in Advanced Materials Ministry of Education Taiyuan University of Technology Taiyuan China.
Yizhi ZhuCollege of Physics and Optoelectronics Shanxi Key Lab of Photovoltaic Technology and Application Key Lab of Advanced Transducers and Intelligent Control System Ministry of Education Taiyuan University of Technology Taiyuan China.ORCID https://orcid.org/0000-0002-8673-0535
Yongzhen YangKey Laboratory of Interface Science and Engineering in Advanced Materials Ministry of Education Taiyuan University of Technology Taiyuan China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Artificial synapses have emerged as a pivotal technological advancement in mimicking brain functions. Organic memristors are desirable for hardware implementation of artificial synapses, owing to their remarkable mechanical flexibility, high biocompatibility at cell-device interfaces, and adjustable material structure. Developing appropriate organic polymers with carbon dots modification will enable the memristor to possess analog-type resistive switching behavior, crucial for realizing brain-like associative learning and adapting dynamic variations of neuron connection strength. In this work, an artificial synapse based on the analogue organic memristor integrating neuromorphic computing and neural interface functions is proposed, utilizing synthetic conjugated porous polymers to construct composites with boron-doped carbon dots. The structure-property relationship of alkynyl and alkyl chains in polymers is elucidated, alongside the synergistic effect of local photoinduced redox and hole templating in composites that endows the device with analog-type resistive switching behavior. Moreover, the memristor presents impressive synaptic plasticity and associative memory learning potential for neuromorphic computing, and further serves as a core unit in flexible artificial neural interface chips, demonstrating dynamic information transmission with neural systems. This study will promote the further development of organic artificial synapses for neuromorphic computing and brain-machine interfaces.

Indexed as

artificial synapsecarbon dotconjugated porous polymermemristorneural interfaceneuromorphic computing

Identifiers

PMID41810068
PMCPMC12970212

What OpenQuestion holds

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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.