Roadmap on multiscale materials modeling

Abstract

Modeling and simulation is transforming modern materials science, becoming an important tool for the discovery of new materials and material phenomena, for gaining insight into the processes that govern materials behavior, and, increasingly, for quantitative predictions that can be used as part of a design tool in full partnership with experimental synthesis and characterization. Modeling and simulation is the essential bridge from good science to good engineering, spanning from fundamental understanding of materials behavior to deliberate design of new materials technologies leveraging new properties and processes. This Roadmap presents a broad overview of the extensive impact computational modeling has had in materials science in the past few decades, and offers focused perspectives on where the path forward lies as this rapidly expanding field evolves to meet the challenges of the next few decades. The Roadmap offers perspectives on advances within disciplines as diverse as phase field methods to model mesoscale behavior and molecular dynamics methods to deduce the fundamental atomic-scale dynamical processes governing materials response, to the challenges involved in the interdisciplinary research that tackles complex materials problems where the governing phenomena span different scales of materials behavior requiring multiscale approaches. The shift from understanding fundamental materials behavior to development of quantitative approaches to explain and predict experimental observations requires advances in the methods and practice in simulations for reproducibility and reliability, and interacting with a computational ecosystem that integrates new theory development, innovative applications, and an increasingly integrated software and computational infrastructure that takes advantage of the increasingly powerful computational methods and computing hardware.

Insights from the quantitative calibration of an elasto-plastic model from a Lennard-Jones atomic glass

“…Multi-scale models of plastic deformation aim to gain a qualitative and quantitative understanding of the relation between microstructural properties and the dynamics of plastic activity. Ultimately, such models can help design new microstructures tailored to meet the demands of specific engineering applications and industries [1,2]. An essential ingredient for a successful multiscale approach is establishing links between atomistic and macroscale continuum descriptions in a physically grounded manner.…”

Mechanical Metamaterials on the Way from Laboratory Scale to Industrial Applications: Challenges for Characterization and Scalability

“…Continuum mechanics methodology is based on the assumption that materials behave as a continuum; this can be a drastic simplification. Therefore data and model development need to be improved [75]. Analytical methods can provide additional insight for the fundamental design and description of metamaterials, where mechanical equivalent models can be established.…”

“…Analytical methods can provide additional insight for the fundamental design and description of metamaterials, where mechanical equivalent models can be established. However, the employment of numerical approaches is usually preferred, especially with regard to the scaling of the problem [2,16,38,58,75].…”

Structural hierarchy from wavelet zoom and invariant construction

“…Although the concept of structure genome is useful, the structures considered in the finite element models [7,8] are only idealized structures tailored for the convenience of mathematical treatment and by no means represent the frequently encountered realistic and complex microstructure in metallurgy and MSE. Multiscale materials modeling [9] can generate a plethora of useful data, but it still represents the traditional way of problem solving based on logical derivations. There is no doubt that a data-driven based approach empowered by artificial intelligence (AI) machine learning (ML) is a true enabler and driver for MGI.…”