Improving high throughput manufacture of laser-inscribed graphene electrodes via hierarchical clustering

Qian, Hanyu; Moreira, Geisianny; Vanegas, Diana; Tang, Yifan; Pola, Cicero; Gomes, Carmen; McLamore, Eric; Bliznyuk, Nikolay

Improving high throughput manufacture of laser-inscribed graphene electrodes via hierarchical clustering

File

2024-Gomes-ImprovingHigh.pdf (1.49 MB)

Date

2024-04-05

Authors

Qian, Hanyu

Moreira, Geisianny

Vanegas, Diana

Tang, Yifan

Pola, Cicero

Gomes, Carmen

McLamore, Eric

Bliznyuk, Nikolay

Publisher

Scientific Report

Abstract

Laser-inscribed graphene (LIG), initially developed for graphene supercapacitors, has found widespread use in sensor research and development, particularly as a platform for low-cost electrochemical sensing. However, batch-to-batch variation in LIG fabrication introduces uncertainty that cannot be adequately tracked during manufacturing process, limiting scalability. Therefore, there is an urgent need for robust quality control (QC) methodologies to identify and select similar and functional LIG electrodes for sensor fabrication. For the first time, we have developed a statistical workflow and an open-source hierarchical clustering tool for QC analysis in LIG electrode fabrication. The QC process was challenged with multi-operator cyclic voltammetry (CV) data for bare and metalized LIG. As a proof of concept, we employed the developed QC process for laboratory-scale manufacturing of LIG-based biosensors. The study demonstrates that our QC process can rapidly identify similar LIG electrodes from large batches (n ≥ 36) of electrodes, leading to a reduction in biosensor measurement variation by approximately 13% compared to the control group without QC. The statistical workflow and open-source code presented here provide a versatile toolkit for clustering analysis, opening a pathway toward scalable manufacturing of LIG electrodes in sensing. In addition, we establish a data repository for further study of LIG variation.

Academic or Administrative Unit

Mechanical Engineering

Type

article

Comments

This article is published as Qian, Hanyu, Geisianny Moreira, Diana Vanegas, Yifan Tang, Cicero Pola, Carmen Gomes, Eric McLamore, and Nikolay Bliznyuk. "Improving high throughput manufacture of laser-inscribed graphene electrodes via hierarchical clustering." Scientific Reports 14, no. 1 (2024): 7980. doi: https://doi.org/10.1038/s41598-024-57932-z. © The Author(s) 2024. This open-access article is licensed under a Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/).