Evidence map›Paper›PMID 40526926›Full record

ArticleLangmuir : the ACS journal of surfaces and colloids2025

Decoupling of Interfacial Ionic Diffusion from Segmental Dynamics in Silica-Filled Silicone Gel through Experiments.

Ying Lin, Chuanle Heng, Yuhao Liu, Yifan Xu, Tao Wen, Antonio Facchetti, Lijian Ding

Abstract read
In one paragraph

Article in Langmuir : the ACS journal of surfaces and colloids, 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

7 authors.

Ying LinSchool of Electrical and Automation Engineering, Hefei University of Technology, Hefei 230009, China.ORCID 0000-0002-0449-7312
Chuanle HengSchool of Electrical and Automation Engineering, Hefei University of Technology, Hefei 230009, China.
Yuhao LiuCollege of Electrical Engineering and Automation, Fuzhou University, Fuzhou 350108, China.
Yifan XuSchool of Electrical and Automation Engineering, Hefei University of Technology, Hefei 230009, China.
Tao WenSchool of Electrical and Automation Engineering, Hefei University of Technology, Hefei 230009, China.
Antonio FacchettiSchool of Materials Science and Engineering, Georgia Institute of Technology, Atlanta 30332, Georgia, United States.ORCID 0000-0002-8175-7958
Lijian DingSchool of Electrical and Automation Engineering, Hefei University of Technology, Hefei 230009, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study experimentally investigates and models the ionic diffusion coefficient at inert particle/polymer interfaces in silica-filled silicone gels, aiming to elucidate the relationship between ion diffusion and segmental dynamics at interfaces. As the specific surface area of silica increases, more loop-type structure chains form at the silica-silicone gel interface. Enhanced silicone chain flexibility at the interface, coupled with a low dielectric constant, strengthens electrostatic interactions and elastic forces, increasing ion jump energy barriers and reducing ion diffusion. Consequently, the influence of polymer segmental dynamics on ion diffusion becomes more significant, shifting the decoupling index between segmental dynamics and the ionic diffusion coefficient from negative to zero. This study provides a theoretical understanding of how interfacial chain movement impacts ion diffusion at interfaces supported by experiments, which is critical to modeling electrical properties of composite polymers and optimizing the performance of relevant electronic and future bioelectronic devices.

Identifiers

PMID40526926
PMCPMC12269070

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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.