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Multiscale modelling: the spiral staircase from theory to experiment
Uppsala University, Disciplinary Domain of Science and Technology, Chemistry, Department of Chemistry - Ångström, Structural Chemistry.
2017 (English)Conference paper, Oral presentation with published abstract (Other academic)
Abstract [en]

Multiscale modelling has become a catch phrase in modern e-science, and is widely (and rather broadly) used in many different research fields. From Wikipedia, one can read the following definition of the phrase:

In engineering, mathematics, physics, chemistry, bioinformatics, computational biology, meteorology and computer science, multiscale modelling or multiscale mathematics is the field of solving problems which have important features at multiple scales of time and/or space.”

The materials science community often deals with just such multiscale problems, i.e. problems that at the same time concern macroscale properties such as hardness, colour and ductility, which in turn heavily relies on the microscale (electrons and atoms). In this community, multiscale modelling is often referred to as a solution to bridge existing gaps between “first-principles” theoretical approaches and experiments. The strategy, or aim, of multiscale materials modelling is to connect data from different distinguishable levels of models, either in a sequential or a concurrent manner. Generally, these levels are i) quantum mechanical models, which concern electrons, ii) molecular dynamics models, which concern the movement of atoms and molecules, iii) coarse graining models, which concerns groups of atoms/molecules, iv) continuum models, and finally, v) the level of device modelling. Each of these levels is capable of describing a certain time- and length scale, and multiscale materials modelling is thereby often visualized schematically in the form of a “multiscale ladder” or a “multiscale staircase”.

One of the key obstacles in multiscale materials modelling is to link and harmonize the different models. In some cases, the link between different levels of models can be obvious and made using empirical approaches. Here, constitutive relations, often based on very simplistic ideas such as linearization, or symmetry, plays an important role. However, extending these simple empirical approaches to be used for more complex systems, where discrete and finite size effects are of importance, has been proven difficult.

In this talk, I will present and discuss common methods used in materials chemistry to link the various levels of models. Both simple (linearized) models and more complex multi-dimensional approaches will be discussed, as well as how this emerging field opens up new opportunities for research collaboration with other disciplines, such as computer science.

Place, publisher, year, edition, pages
2017.
National Category
Materials Chemistry Theoretical Chemistry
Identifiers
URN: urn:nbn:se:uu:diva-338326OAI: oai:DiVA.org:uu-338326DiVA, id: diva2:1171898
Conference
Swedish e-Science Academy 2017, October 11-12, Umeå, Sweden.
Available from: 2018-01-08 Created: 2018-01-08 Last updated: 2018-02-22Bibliographically approved

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Broqvist, Peter

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