Evidence map›Paper›PMID 41803483›Full record

ArticleNature materials2026

An iontronic reservoir for highly robust neuromorphic prosthesis.

Mengjiao Pei, Tian Gao, Li Liu, Wenlong Li, Haotian Long, Yifei Luo, Zhaogang Teng, Hangyuan Cui, Xiang Li, Qinyong Dai and 14 more

Erratum issuedAbstract read
PubMed Publisher
In one paragraph

Article in Nature materials, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. 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. Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

24 authors.

Mengjiao Pei *School of Electronic Science and Engineering, National Laboratory of Solid-State Microstructures, Nanjing University, Nanjing, P. R. China.
Tian Gao *Collaborative Innovation Center of Advanced Microstructures, School of Physics, Nanjing University, Nanjing, China.
Li Liu *Department of Radiology, Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China.
Wenlong LiInstitute of Materials Research and Engineering (IMRE), Agency for Science, Technology and Research (A*STAR), Singapore, Singapore.ORCID 0000-0003-0729-0357
Haotian LongSchool of Electronic Science and Engineering, National Laboratory of Solid-State Microstructures, Nanjing University, Nanjing, P. R. China.
Yifei LuoInstitute of Materials Research and Engineering (IMRE), Agency for Science, Technology and Research (A*STAR), Singapore, Singapore.ORCID 0000-0002-4454-6318
Zhaogang TengKey Laboratory for Organic Electronics and Information Displays and Jiangsu Key Laboratory for Biosensors, Institute of Advanced Materials, Jiangsu National Synergetic Innovation Centre for Advanced Materials, Nanjing University of Posts and Telecommunications, Nanjing, P. R. China.
Hangyuan CuiSchool of Electronic Science and Engineering, National Laboratory of Solid-State Microstructures, Nanjing University, Nanjing, P. R. China.
Xiang LiSchool of Electronic Science and Engineering, National Laboratory of Solid-State Microstructures, Nanjing University, Nanjing, P. R. China.
Qinyong DaiSchool of Electronic Science and Engineering, National Laboratory of Solid-State Microstructures, Nanjing University, Nanjing, P. R. China.
Kailu ShiSchool of Electronic Science and Engineering, National Laboratory of Solid-State Microstructures, Nanjing University, Nanjing, P. R. China.ORCID 0000-0003-0090-6454
Lesheng QiaoSchool of Electronic Science and Engineering, National Laboratory of Solid-State Microstructures, Nanjing University, Nanjing, P. R. China.
Baocheng PengSchool of Electronic Science and Engineering, National Laboratory of Solid-State Microstructures, Nanjing University, Nanjing, P. R. China.
Qianye XingSchool of Electronic Science and Engineering, National Laboratory of Solid-State Microstructures, Nanjing University, Nanjing, P. R. China.
Manhua WenSchool of Electronic Science and Engineering, National Laboratory of Solid-State Microstructures, Nanjing University, Nanjing, P. R. China.
Mengtao HanSchool of Electronic Science and Engineering, National Laboratory of Solid-State Microstructures, Nanjing University, Nanjing, P. R. China.
Zhenhua WanSchool of Electronic Science and Engineering, National Laboratory of Solid-State Microstructures, Nanjing University, Nanjing, P. R. China.
Yun LiSchool of Electronic Science and Engineering, National Laboratory of Solid-State Microstructures, Nanjing University, Nanjing, P. R. China. yli@nju.edu.cn.ORCID 0000-0003-1753-7317
Bin XueCollaborative Innovation Center of Advanced Microstructures, School of Physics, Nanjing University, Nanjing, China. xuebinnju@nju.edu.cn.ORCID 0000-0002-0822-6501
Yi CaoCollaborative Innovation Center of Advanced Microstructures, School of Physics, Nanjing University, Nanjing, China.ORCID 0000-0003-1493-7868
Yi ShiSchool of Electronic Science and Engineering, National Laboratory of Solid-State Microstructures, Nanjing University, Nanjing, P. R. China. yshi@nju.edu.cn.ORCID 0000-0002-1082-0315
Qing WanYongjiang Laboratory (Y-LAB), Ningbo, China. wanqing@nju.edu.cn.
Xiaodong ChenInstitute of Materials Research and Engineering (IMRE), Agency for Science, Technology and Research (A*STAR), Singapore, Singapore. chenxd@ntu.edu.sg.ORCID 0000-0002-3312-1664
Changjin WanSchool of Electronic Science and Engineering, National Laboratory of Solid-State Microstructures, Nanjing University, Nanjing, P. R. China. cjwan@nju.edu.cn.ORCID 0000-0002-3210-6673

Funding

National Natural Science Foundation of China (National Science Foundation of China) 62174082
6 · The paper itself

Abstract

Neuromorphic prosthesis demands not only the assembly of neural architectures and functions but also robustness against unpredictable failures in dynamic physiological environments. While self-healing electronics have been demonstrated to restore synapse-like functions, their application to higher-order cognitive functions remains limited. Here we present a hydrogel-based iontronic reservoir that demonstrates exceptional physical and functional robustness for neuromorphic prosthesis. The nonlinear dynamics of the hydrogel-electrode interface can serve as a physical reservoir to preprocess time series, with minimized susceptibility to physical damage. Our system based on the hydrogel-based iontronic reservoir achieves 95% accuracy in speech recognition and can restore such capability within 0.02 s after reattaching the fractured points, outperforming biological systems in the neurorehabilitation process. Moreover, its pH-sensitive dynamics enable adaptive closed-loop neural stimulation control in a rat model, validating its potential for neural rehabilitation and sensorimotor function restoration. We expect such a hydrogel-based iontronic reservoir to improve both processing efficiency and robustness for next-generation neuroprosthetics and human-machine interfaces.

Indexed as

Neural ProsthesesAnimalsHumansHydrogelsRatsHydrogels

Identifiers

PMID41803483

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.