Evidence map›Paper›PMID 40963494›Full record

ArticleSmall methods2025

Single-Step Patterning of Biocompatible Neural Electrodes Using Black-Pt Functionalized Laser-Induced Graphene for in Vivo Electrophysiology.

Giheon Kim, Yeonghwa Hong, Haeyun Lee, Minseok Kim, Jonghee Eun, Jimin Lee, Seungjun Lee, Namsun Chou, Hyogeun Shin

Abstract read
In one paragraph

Article in Small methods, 2025. 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. Article
  2. Full-Stack Architectures for Intelligent Brain-Computer Interfaces.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
    Review
  3. Review
  4. Article
  5. Article
  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

9 authors.

Giheon KimSchool of Electronic and Electrical Engineering, College of IT Engineering, Kyungpook National University, Daegu, 41566, Republic of Korea.
Yeonghwa HongSchool of Electronics Engineering, College of IT Engineering, Kyungpook National University, Daegu, 41566, Republic of Korea.
Haeyun LeeSchool of Electronic and Electrical Engineering, College of IT Engineering, Kyungpook National University, Daegu, 41566, Republic of Korea.
Minseok KimSchool of Electronic and Electrical Engineering, College of IT Engineering, Kyungpook National University, Daegu, 41566, Republic of Korea.
Jonghee EunEmotion, Cognition & Behavior Research Group, Korea Brain Research Institute (KBRI), Daegu, 41062, Republic of Korea.
Jimin LeeEmotion, Cognition & Behavior Research Group, Korea Brain Research Institute (KBRI), Daegu, 41062, Republic of Korea.
Seungjun LeeSchool of Electronic and Electrical Engineering, College of IT Engineering, Kyungpook National University, Daegu, 41566, Republic of Korea.
Namsun ChouEmotion, Cognition & Behavior Research Group, Korea Brain Research Institute (KBRI), Daegu, 41062, Republic of Korea.
Hyogeun ShinSchool of Electronic and Electrical Engineering, College of IT Engineering, Kyungpook National University, Daegu, 41566, Republic of Korea.ORCID 0000-0002-3784-2717

Funding

Bio&Medical Technology Development ProgramInnovative Human Resource DevelopmentInstitute of Information & Communications Technology Planning & Evaluation (IITP)Korea Brain Research Institute 25-BR-02-02Korea Brain Research Institute 25-BR-04-01Korea government (MSIT) 2025-RS-2022-00156389Korean government (MSIT) 2025-00557203Korean government (MSIT) 2025-02243041Local Intellectualization programMinistry of Trade, Industry & Energy (MOTIE, Korea)National Research Foundation (NRF)National Research Foundation of Korea (NRF)Neuro-Semi-AI Fusion Superhuman ProjectTechnology Innovation Program 2025-04812973
6 · The paper itself

Abstract

Neural electrodes are essential tools for monitoring electrophysiological activity in the brain, driving advances in neuroscience and neurotechnology. However, conventional semiconductor-based fabrication techniques suffer from high costs, complex procedures, and limited adaptability for customized designs. Here, a single-step patterning, scalable method is presented for fabricating biocompatible neural electrodes using laser-induced graphene (LIG) patterned directly onto polyimide substrates. This process requires only a standard CO

Indexed as

Biocompatible MaterialsElectrodes, ImplantedGraphiteLasersPlatinumAnimalsBrainElectrocorticographyElectrodesElectroencephalographyMiceBiocompatible MaterialsGraphitePlatinumflexible neural electrodehigh‐throughput fabricationin vivo electrophysiologylaser‐induced graphene (LIG)neural interface

Identifiers

PMID40963494
PMCPMC12641342

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.