Digital Twins in Graphene Technology
Elena F. Sheka

TL;DR
This paper explores the application of Digital Twins in graphene material science, highlighting a conceptual shift from traditional modeling to independent digital replicas that provide new insights into real objects.
Contribution
It introduces the first conceptual rethinking of Digital Twins in the context of graphene technology, emphasizing a transition to independent digital representations.
Findings
Digital Twins offer an independent view of real objects.
A new conceptual framework for Digital Twins in material science.
Potential for enhanced understanding of graphene materials.
Abstract
The Digital Twins concept in science has a long history that goes back to the beginnings of now widely accepted modelling. The ever-expanding amount of digital data accompanying modelling could not but cause a qualitative transition from modelling, subordinated to the goal of reproducing a real object, to an equal-right Digital Twins concept that offers an independent view of the real object. This chapter presents the first example of such a conceptual rethinking, using the example of material science of high-tech graphene materials.
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Taxonomy
TopicsMachine Learning in Materials Science
