Author, as appears in the article.: José Carlos Santos-Ceballos, Foad Salehnia, Alfonso Romero, Xavier Vilanova
Department: Enginyeria Electrònica, Elèctrica i Automàtica
URV's Author/s: Romero Nevado, Alfonso José / Salehnia, Foad / Santos Ceballos, José Carlos / Vilanova Salas, Javier
Abstract: In the era of man–machine interfaces, digital twins stand as a key technology, offering virtual representations of real-world objects, processes, and systems through computational models. They enable novel ways of interacting with, comprehending, and manipulating real-world entities within a virtual realm. The real implementation of graphene-based sensors and electronic devices remains challenging due to the integration complexities of high-quality graphene materials with existing manufacturing processes. To address this, scalable techniques for the in-situ fabrication of graphene-like materials are essential. One promising method involves using a CO2 laser to convert polyimide into graphene. Optimizing this graphitization process is hindered by complex parameter interactions and nonlinear terms. This article explores how these digital replicas can enhance the fabrication of laser-induced graphene (LIG) through laser simulation and machine learning methods to enable rapid single-step LIG patterning. This approach aims to create a universal simulation for all CO2 lasers, calculating optical energy flux and utilizing machine learning to control and predict LIG conductivity (ability to conduct current), morphology, and electrical resistance. The proposed procedure, integrating digital twins in the LIG production process, will avoid or reduce the preliminary tests required to determine the proper laser parameters to reach the desired LIG characteristics. Accordingly, this approach will reduce the time and costs associated with these tests and thus increase the efficiency and optimize the procedure.
Thematic Areas: Zootecnia / recursos pesqueiros Saúde coletiva Química Psicología Odontología Nutrição Multidisciplinary sciences Multidisciplinary Medicina veterinaria Medicina iii Medicina ii Medicina i Materiais Matemática / probabilidade e estatística Letras / linguística Interdisciplinar Geografía Geociências Farmacia Engenharias iv Engenharias iii Engenharias ii Enfermagem Educação física Educação Economia Ciências biológicas iii Ciências biológicas ii Ciências biológicas i Ciências ambientais Ciências agrárias i Ciência de alimentos Ciência da computação Biotecnología Biodiversidade Astronomia / física
licence for use: https://creativecommons.org/licenses/by/3.0/es/
Author's mail: foad.salehnia@urv.cat josecarlos.santos@urv.cat josecarlos.santos@urv.cat xavier.vilanova@urv.cat alfonsojose.romero@urv.cat
Author identifier: 0000-0002-6245-7933 0000-0003-3502-0813
Record's date: 2024-08-03
Papper version: info:eu-repo/semantics/publishedVersion
Link to the original source: https://www.nature.com/articles/s41598-024-61237-6
Licence document URL: https://repositori.urv.cat/ca/proteccio-de-dades/
Papper original source: Scientific Reports. 14 (14): 10363-10
APA: José Carlos Santos-Ceballos, Foad Salehnia, Alfonso Romero, Xavier Vilanova (2024). Application of digital twins for simulation based tailoring of laser induced graphene. Scientific Reports, 14(14), 10363-10. DOI: 10.1038/s41598-024-61237-6
Article's DOI: 10.1038/s41598-024-61237-6
Entity: Universitat Rovira i Virgili
Journal publication year: 2024
Publication Type: Journal Publications