Evidence map›Paper›PMID 40666277›Full record

ArticleNational science review2025

Electrically programmable organic in-display neuromorphic computing.

Shilei Dai, Dingchen Wang, Xu Liu, Binbin Cui, Xinyu Tian, Dingyao Liu, Huawei Hu, Pu Guo, Tongrui Sun, Junyao Zhang and 3 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in National science review, 2025. 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.

  1. Bioinspired Photodetectors: From Nature to Advanced Applications.Advanced materials (Deerfield Beach, Fla.) · 2026
    Review
  2. 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.

Shilei DaiDepartment of Electrical and Electronic Engineering, The University of Hong Kong, Hong Kong 999077, China.ORCID https://orcid.org/0000-0002-5849-0503
Dingchen WangDepartment of Electrical and Electronic Engineering, The University of Hong Kong, Hong Kong 999077, China.
Xu LiuSchool of Materials Science and Engineering, Tongji University, Shanghai 201804, China.
Binbin CuiDepartment of Electrical and Electronic Engineering, The University of Hong Kong, Hong Kong 999077, China.
Xinyu TianDepartment of Electrical and Electronic Engineering, The University of Hong Kong, Hong Kong 999077, China.ORCID https://orcid.org/0009-0009-1522-5951
Dingyao LiuDepartment of Electrical and Electronic Engineering, The University of Hong Kong, Hong Kong 999077, China.
Huawei HuState Key Laboratory for Modification of Chemical Fibers and Polymer Materials & College of Materials Science and Engineering, Donghua University, Shanghai 201620, China.
Pu GuoSchool of Materials Science and Engineering, Tongji University, Shanghai 201804, China.
Tongrui SunSchool of Materials Science and Engineering, Tongji University, Shanghai 201804, China.
Junyao ZhangSchool of Materials Science and Engineering, Tongji University, Shanghai 201804, China.ORCID https://orcid.org/0000-0002-6300-5875
Jia HuangSchool of Materials Science and Engineering, Tongji University, Shanghai 201804, China.
Shiming ZhangDepartment of Electrical and Electronic Engineering, The University of Hong Kong, Hong Kong 999077, China.
Zhongrui WangDepartment of Electrical and Electronic Engineering, The University of Hong Kong, Hong Kong 999077, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The scale-up of AI models and data makes smart edge devices (e.g. smartphones and AR/VR glasses) face increasing challenges in energy consumption, latency and hardware costs. These challenges are due to their physically separated memory, processing and display units. Collocating the functions of these units into a single device for in-display neuromorphic computing (IDNC) shows great promise in overcoming these challenges. Herein, we report an all-in-one electrically programmable IDNC (EP-IDNC) device that leverages the electrochromism of organic semiconductors. The electrochromism empowers the EP-IDNC device with synaptic and neural behaviors (e.g. multi-terminal operability, multi-level weight update, spatiotemporal information encoding), as well as the capability to visually display computing results through color changes. The IDNC functions are validated on tasks such as noise reduction and motion object perception using a prototype 3 × 3 EP-IDNC device array. We ultimately showcase the integration of neuromorphic and display functions for car steering reminders.

Indexed as

in-display computingneuromorphic devicesorganic electronicsreconfigurable device

Identifiers

PMID40666277
PMCPMC12260503

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.