Evidence map›Paper›PMID 40593499›Full record

ArticleNature communications2025

In-material physical computing based on reconfigurable microwire arrays via halide-ion segregation.

Dengji Li, Pengshan Xie, Yuekun Yang, Yunfan Wang, Changyong Lan, Yiyang Wei, Jiachi Liao, Bowen Li, Zenghui Wu, Quan Quan and 10 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. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

20 authors.

Dengji Li *Department of Materials Science and Engineering, City University of Hong Kong, Hong Kong SAR, 999077, P. R. China.ORCID http://orcid.org/0000-0002-4406-0246
Pengshan Xie *Department of Materials Science and Engineering, City University of Hong Kong, Hong Kong SAR, 999077, P. R. China.
Yuekun YangInstitute of Brain-Inspired Intelligence, National Laboratory of Solid State Microstructures, School of Physics, Collaborative Innovation Center of Advanced Microstructures, Nanjing University, Nanjing, 210093, P. R. China. yangyk@nju.edu.cn.ORCID http://orcid.org/0000-0002-6808-0735
Yunfan WangDepartment of Materials Science and Engineering, City University of Hong Kong, Hong Kong SAR, 999077, P. R. China.
Changyong LanState Key Laboratory of Electronic Thin Films and Integrated Devices, University of Electronic Science and Technology of China, Chengdu, 610054, P. R. China.ORCID http://orcid.org/0000-0002-5654-1098
Yiyang WeiState Key Laboratory of Electronic Thin Films and Integrated Devices, University of Electronic Science and Technology of China, Chengdu, 610054, P. R. China.
Jiachi LiaoDepartment of Materials Science and Engineering, City University of Hong Kong, Hong Kong SAR, 999077, P. R. China.
Bowen LiDepartment of Materials Science and Engineering, City University of Hong Kong, Hong Kong SAR, 999077, P. R. China.ORCID http://orcid.org/0000-0001-5133-931X
Zenghui WuDepartment of Materials Science and Engineering, City University of Hong Kong, Hong Kong SAR, 999077, P. R. China.ORCID http://orcid.org/0000-0002-7725-7301
Quan QuanDepartment of Materials Science and Engineering, City University of Hong Kong, Hong Kong SAR, 999077, P. R. China.
Yuxuan ZhangDepartment of Materials Science and Engineering, City University of Hong Kong, Hong Kong SAR, 999077, P. R. China.ORCID http://orcid.org/0000-0002-5240-6606
You MengDepartment of Materials Science and Engineering, City University of Hong Kong, Hong Kong SAR, 999077, P. R. China.ORCID http://orcid.org/0000-0002-5385-4080
Mingqi DingDepartment of Materials Science and Engineering, City University of Hong Kong, Hong Kong SAR, 999077, P. R. China.
Yan YanDepartment of Materials Science and Engineering, City University of Hong Kong, Hong Kong SAR, 999077, P. R. China.
Yi ShenDepartment of Materials Science and Engineering, City University of Hong Kong, Hong Kong SAR, 999077, P. R. China.
Weijun WangDepartment of Materials Science and Engineering, City University of Hong Kong, Hong Kong SAR, 999077, P. R. China.
Sai-Wing TsangDepartment of Materials Science and Engineering, City University of Hong Kong, Hong Kong SAR, 999077, P. R. China.ORCID http://orcid.org/0000-0003-0788-4905
Shi-Jun LiangInstitute of Brain-Inspired Intelligence, National Laboratory of Solid State Microstructures, School of Physics, Collaborative Innovation Center of Advanced Microstructures, Nanjing University, Nanjing, 210093, P. R. China.ORCID http://orcid.org/0000-0003-3235-7621
Feng MiaoInstitute of Brain-Inspired Intelligence, National Laboratory of Solid State Microstructures, School of Physics, Collaborative Innovation Center of Advanced Microstructures, Nanjing University, Nanjing, 210093, P. R. China. miao@nju.edu.cn.ORCID http://orcid.org/0000-0002-0962-5424
Johnny C HoDepartment of Materials Science and Engineering, City University of Hong Kong, Hong Kong SAR, 999077, P. R. China. johnnyho@cityu.edu.hk.ORCID http://orcid.org/0000-0003-3000-8794

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Conventional computer systems based on the Von Neumann architecture rely on silicon transistors with binary states for information representation and processing. However, exploiting emerging materials' intrinsic physical properties and dynamic behaviors offers a promising pathway for developing next-generation brain-inspired neuromorphic hardware. Here, we introduce a stable and controllable photoelectricity-induced halide-ion segregation effect in epitaxially grown mixed-halide perovskite CsPbBr

Identifiers

PMID40593499
PMCPMC12214640

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.