Evidence map›Paper›PMID 39011796›Full record

ArticleAdvanced materials (Deerfield Beach, Fla.)2024

Multifunctional Nanomesh Enables Cellular-Resolution, Elastic Neuroelectronics.

Jaehyeon Ryu, Yi Qiang, Longtu Chen, Gen Li, Xun Han, Eric Woon, Tianyu Bai, Yongli Qi, Shaopeng Zhang, Jyun-You Liou and 3 more

Abstract read
In one paragraph

Article in Advanced materials (Deerfield Beach, Fla.), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Robust Stitching Interface and Deep Learning Empowered Hydrogel Human-Machine Interface.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
    Article
  2. Article
  3. Article
  4. Review
  5. Review
  6. 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.

Jaehyeon RyuThayer School of Engineering, Dartmouth College, Hanover, NH, 03755, USA.ORCID 0009-0006-1397-5562
Yi QiangThayer School of Engineering, Dartmouth College, Hanover, NH, 03755, USA.
Longtu ChenDepartment of Biomedical Engineering, University of Connecticut, Storrs, CT, 06269, USA.
Gen LiThayer School of Engineering, Dartmouth College, Hanover, NH, 03755, USA.
Xun HanElectrical and Computer Engineering, Northeastern University, Boston, MA, 02115, USA.
Eric WoonDepartment of Biomedical Engineering, University of Connecticut, Storrs, CT, 06269, USA.
Tianyu BaiThayer School of Engineering, Dartmouth College, Hanover, NH, 03755, USA.
Yongli QiThayer School of Engineering, Dartmouth College, Hanover, NH, 03755, USA.
Shaopeng ZhangDepartment of Biomedical Engineering, University of Connecticut, Storrs, CT, 06269, USA.
Jyun-You LiouDepartment of Anesthesiology, Weill Cornell Medical College, New York, NY, 10065, USA.
Kyung Jin SeoThayer School of Engineering, Dartmouth College, Hanover, NH, 03755, USA.ORCID 0000-0001-9743-2026
Bin FengDepartment of Biomedical Engineering, University of Connecticut, Storrs, CT, 06269, USA.
Hui FangThayer School of Engineering, Dartmouth College, Hanover, NH, 03755, USA.ORCID 0009-0001-3950-6979

Funding

Novel Transparent, Ultra-soft Neuroelectrode Arrays Based on Nanomeshing Conventional Electrode Materials SUPPLEMENTRF1NS118301 · NINDS · NORTHEASTERN UNIVERSITY · PI FAGIOLINI, MICHELA, FANG, HUI · 2020 to 2022
$2.4M
National Science Foundation 1844762National Science Foundation 2140392NIH HHS RF1NS118301NINDS NIH HHS RF1 NS118301Thayer School of Engineering, Dartmouth College
6 · The paper itself

Abstract

Silicone-based devices have the potential to achieve an ideal interface with nervous tissue but suffer from scalability, primarily due to the mechanical mismatch between established electronic materials and soft elastomer substrates. This study presents a novel approach using conventional electrode materials through multifunctional nanomesh to achieve reliable elastic microelectrodes directly on polydimethylsiloxane (PDMS) silicone with an unprecedented cellular resolution. This engineered nanomesh features an in-plane nanoscale mesh pattern, physically embodied by a stack of three thin-film materials by design, namely Parylene-C for mechanical buffering, gold (Au) for electrical conduction, and Poly(3,4-ethylenedioxythiophene)-poly(styrenesulfonate) (PEDOT:PSS) for improved electrochemical interfacing. Nanomesh elastic neuroelectronics are validated using single-unit recording from the small and curvilinear epidural surface of mouse dorsal root ganglia (DRG) with device self-conformed and superior recording quality compared to plastic control devices requiring manual pressing is demonstrated. Electrode scaling studies from in vivo epidural recording further revealed the need for cellular resolution for high-fidelity recording of single-unit activities and compound action potentials. In addition to creating a minimally invasive device to effectively interface with DRG sensory afferents at a single-cell resolution, this study establishes nanomeshing as a practical pathway to leverage traditional electrode materials for a new class of elastic neuroelectronics.

Indexed as

Ganglia, SpinalGoldPolymersXylenesAction PotentialsAnimalsBridged Bicyclo Compounds, HeterocyclicDimethylpolysiloxanesElasticityMiceMicroelectrodesNanostructuresPolystyrenesThiophenesbaysilonBridged Bicyclo Compounds, HeterocyclicDimethylpolysiloxanesGoldparylenepoly(3,4-ethylenedioxythiophene)-poly(styrenesulfonate)PolymersPolystyrenesThiophenesXyleneselasticmultifunctionnanomeshneuroelectronics

Identifiers

PMID39011796
PMCPMC11410539

What OpenQuestion holds

Textmetadata
LicenceTDM
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.