Evidence map›Paper›PMID 36176270›Full record

ArticleMicrosystems & nanoengineering2022

Multilayer CVD graphene electrodes using a transfer-free process for the next generation of optically transparent and MRI-compatible neural interfaces.

Nasim Bakhshaee Babaroud, Merlin Palmar, Andrada Iulia Velea, Chiara Coletti, Sebastian Weingärtner, Frans Vos, Wouter A Serdijn, Sten Vollebregt, Vasiliki Giagka

Abstract read
In one paragraph

Article in Microsystems & nanoengineering, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
  4. Applications of 2D Nanomaterials in Neural Interface.International journal of molecular sciences · 2024
    Review
  5. Article
  6. Article
  7. Review
  8. Review
  9. Graphene-based nanomaterials for peripheral nerve regeneration.Frontiers in bioengineering and biotechnology · 2023
    Review
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

9 authors.

Nasim Bakhshaee BabaroudDepartment of Microelectronics, Faculty of Electrical Engineering, Mathematics and Computer Science, Delft University of Technology, Mekelweg 4, Delft, 2628 CD The Netherlands.
Merlin PalmarDepartment of Microelectronics, Faculty of Electrical Engineering, Mathematics and Computer Science, Delft University of Technology, Mekelweg 4, Delft, 2628 CD The Netherlands.
Andrada Iulia VeleaDepartment of Microelectronics, Faculty of Electrical Engineering, Mathematics and Computer Science, Delft University of Technology, Mekelweg 4, Delft, 2628 CD The Netherlands.
Chiara ColettiDepartment of Imaging Physics, Faculty of Applied Science, Delft University of Technology, Lorentzweg 1, Delft, 2628 CJ The Netherlands.
Sebastian WeingärtnerDepartment of Imaging Physics, Faculty of Applied Science, Delft University of Technology, Lorentzweg 1, Delft, 2628 CJ The Netherlands.
Frans VosDepartment of Imaging Physics, Faculty of Applied Science, Delft University of Technology, Lorentzweg 1, Delft, 2628 CJ The Netherlands.
Wouter A SerdijnDepartment of Microelectronics, Faculty of Electrical Engineering, Mathematics and Computer Science, Delft University of Technology, Mekelweg 4, Delft, 2628 CD The Netherlands.
Sten VollebregtDepartment of Microelectronics, Faculty of Electrical Engineering, Mathematics and Computer Science, Delft University of Technology, Mekelweg 4, Delft, 2628 CD The Netherlands.
Vasiliki GiagkaDepartment of Microelectronics, Faculty of Electrical Engineering, Mathematics and Computer Science, Delft University of Technology, Mekelweg 4, Delft, 2628 CD The Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Multimodal platforms combining electrical neural recording and stimulation, optogenetics, optical imaging, and magnetic resonance (MRI) imaging are emerging as a promising platform to enhance the depth of characterization in neuroscientific research. Electrically conductive, optically transparent, and MRI-compatible electrodes can optimally combine all modalities. Graphene as a suitable electrode candidate material can be grown via chemical vapor deposition (CVD) processes and sandwiched between transparent biocompatible polymers. However, due to the high graphene growth temperature (≥ 900 °C) and the presence of polymers, fabrication is commonly based on a manual transfer process of pre-grown graphene sheets, which causes reliability issues. In this paper, we present CVD-based multilayer graphene electrodes fabricated using a wafer-scale transfer-free process for use in optically transparent and MRI-compatible neural interfaces. Our fabricated electrodes feature very low impedances which are comparable to those of noble metal electrodes of the same size and geometry. They also exhibit the highest charge storage capacity (CSC) reported to date among all previously fabricated CVD graphene electrodes. Our graphene electrodes did not reveal any photo-induced artifact during 10-Hz light pulse illumination. Additionally, we show here, for the first time, that CVD graphene electrodes do not cause any image artifact in a 3T MRI scanner. These results demonstrate that multilayer graphene electrodes are excellent candidates for the next generation of neural interfaces and can substitute the standard conventional metal electrodes. Our fabricated graphene electrodes enable multimodal neural recording, electrical and optogenetic stimulation, while allowing for optical imaging, as well as, artifact-free MRI studies.

Indexed as

EngineeringOther nanotechnology

Identifiers

PMID36176270
PMCPMC9512798

What OpenQuestion holds

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LicenceCC BY
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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.