Organic Memristor with Synaptic Plasticity for Neuromorphic Computing Applications.

Jianmin Zeng, Xinhui Chen, Shuzhi Liu, Qilai Chen, Gang Liu

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Article in Nanomaterials (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it

0cells of the map it votes in

2citing 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

2 citing papers in PubMed.

Recent Advances in Optoelectronic Synaptic Devices for Neuromorphic Computing.Biomimetics (Basel, Switzerland) · 2025
Review
Design of CMOS-memristor hybrid synapse and its application for noise-tolerant memristive spiking neural network.Frontiers in neuroscience · 2025
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

5 authors.

Jianmin ZengSchool of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China.

Xinhui ChenCollege of Information Engineering, Jinhua Polytechnic, Jinhua 321017, China.

Shuzhi LiuSchool of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China.

Qilai ChenAEROSPACE SCIENCE & INDUSTRY SHENZHEN (GROUP) CO., LTD., Shenzhen 518000, China.

Gang LiuSchool of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China.

Funding

National Natural Science Foundation of China 62111540271, 61974090 and 62104267the State Key R&D Program 2022YFB4700102

6 · The paper itself

Abstract

Memristors have been considered to be more efficient than traditional Complementary Metal Oxide Semiconductor (CMOS) devices in implementing artificial synapses, which are fundamental yet very critical components of neurons as well as neural networks. Compared with inorganic counterparts, organic memristors have many advantages, including low-cost, easy manufacture, high mechanical flexibility, and biocompatibility, making them applicable in more scenarios. Here, we present an organic memristor based on an ethyl viologen diperchlorate [EV(ClO

Indexed as

artificial neural networksartificial synapseneuromorphic computingorganic memristorsynaptic plasticity

Identifiers

PMID36903681

DOI10.3390/nano13050803

PMCPMC10005145

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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.