Evidence map›Paper›PMID 41309659›Full record

ArticleNature communications2025

Robust biodegradable synapse with sub-biological energy and extended memory for intelligent reflexive system.

Yoojin Chang, Sangyun Na, Yun Goo Ro, Cheolhong Park, Seokhee Jung, Yong-Jin Park, Min Sub Kwak, Jeeyoon Kim, Hyeji Oh, Jaejun Kim and 1 more

Abstract read
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. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Article
  3. 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

11 authors.

Yoojin Chang *School of Energy and Chemical Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan Metropolitan City, Republic of Korea.ORCID http://orcid.org/0000-0002-7603-8668
Sangyun Na *School of Energy and Chemical Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan Metropolitan City, Republic of Korea.
Yun Goo Ro *School of Energy and Chemical Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan Metropolitan City, Republic of Korea.ORCID http://orcid.org/0000-0002-7023-086X
Cheolhong ParkSchool of Energy and Chemical Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan Metropolitan City, Republic of Korea.ORCID http://orcid.org/0000-0001-8992-6317
Seokhee JungSchool of Energy and Chemical Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan Metropolitan City, Republic of Korea.
Yong-Jin ParkSchool of Energy and Chemical Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan Metropolitan City, Republic of Korea.
Min Sub KwakSchool of Energy and Chemical Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan Metropolitan City, Republic of Korea.
Jeeyoon KimSchool of Energy and Chemical Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan Metropolitan City, Republic of Korea.
Hyeji OhSchool of Energy and Chemical Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan Metropolitan City, Republic of Korea.ORCID http://orcid.org/0009-0006-9365-9016
Jaejun KimSchool of Energy and Chemical Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan Metropolitan City, Republic of Korea.
Hyunhyub KoSchool of Energy and Chemical Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan Metropolitan City, Republic of Korea. hyunhko@unist.ac.kr.ORCID http://orcid.org/0000-0003-2111-6101

Funding

National Research Foundation of Korea (NRF) RS-2021-NR059784
6 · The paper itself

Abstract

Biodegradable artificial synapses hold great promise for sustainable neuromorphic electronics, yet combining long-term memory, ultralow energy consumption, and mechanical robustness remains challenging. Here, we report a fully biodegradable multilayer artificial synapse (M-AS) composed of crosslinked chitosan-guar gum (CS-GG) ion-active layers (IALs) and a cellulose acetate (CA) ion-binding layer (IBL). This trilayer architecture enhances ion trapping via ion-dipole coupling (IDC) at the IAL-IBL interface, while hydrogen-bonded crosslinking within the CS-GG matrix enhances mechanical and environmental stability. Sodium chloride, embedded in the IALs, serves as a mobile ionic species analogous to biological neurotransmitters, enabling low-voltage ion migration. Upon electrical stimulation, ion migration and dipole alignment induce IDC, leading to partial ion retention and cascade-like postsynaptic current responses that support memory formation. The M-AS supports key synaptic functionalities-including paired-pulse facilitation, short-term and long-term plasticity, multilevel memory encoding, and bidirectional modulation-under sub-millivolt operation. It achieves the longest long-term memory time (5944 s) reported among biodegradable artificial synapses and an energy consumption (0.85 fJ/event) lower than that of biological synapses. Integration with a thermistor and robotic actuator enables a bioinspired reflexive system capable of adaptive, stimulus-dependent learning and reflex-like behaviors. These results demonstrate the potential of M-AS for low-power, intelligent human-machine interfaces.

Indexed as

Memory, Long-TermSynapsesAnimalsCelluloseChitosanHumansNeuronal PlasticityCelluloseChitosan

Identifiers

PMID41309659
PMCPMC12660886

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.