In engineering, physics, and computer science, multiscale modeling is the field of solving physical problems which have important features at multiple scales, particularly multiple spatial and(or) temporal scales. Important problems include scale linking (Baeurle 2006, Baeurle 2008, Deminsky 2004, Adamson 2007).

Multiscale modeling in physics is aimed to calculation of material properties or system behaviour on one level using information or models from different levels. On each level particular approaches are used for description of a system. Following levels are usually distinguished: level of quantum mechanical models (information about electrons is included), level of molecular dynamics models (information about individual atoms is included), mesoscale or nano level (information about groups of atoms and molecules is included), level of continuum models, level of device models. Each level addresses a phenomenon over a specific window of length and time. Multiscale modeling is particularly important in integrated computational materials engineering since it allows to predict material properties or system behaviour based on knowledge of the atomistic structure and properties of elementary processes.

In Operations Research, multiscale modeling addresses challenges for decision makers which come from multiscale phenomena across organizational, temporal and spatial scales. This theory fuses decision theory and multiscale mathematics and is referred to as Multiscale decision making. The Multiscale decision making approach draws upon the analogies between physical systems and complex man-made systems.

• Baeurle, S.A. (2006). "A new multiscale modeling approach for the prediction of mechanical properties of polymer-based nanomaterials". Polymer. 47 (26): 8604–8617. doi:10.1016/j.polymer.2006.10.017. {{cite journal}}: Unknown parameter |coauthors= ignored (|author= suggested) (help)

• Baeurle, S.A. (2008). "Multiscale modeling of polymer materials using field-theoretic methodologies". Habilitation-Thesis, University of Regensburg, Germany.

• Deminsky, M. (2004). "Mechanism and kinetics of thin zirconium and hafnium oxide film growth in an ALD reactor". Surface Science. 549: 67–86. doi:10.1016/j.susc.2003.10.056. {{cite journal}}: Unknown parameter |coauthors= ignored (|author= suggested) (help)

• Adamson, S. (2007). "Multiscale multiphysics nonempirical approach to calculation of light emission properties of chemically active nonequilibrium plasma: application to Ar–GaI₃ system". J. Phys. D: Appl. Phys. 40 (13): 3857–3881. doi:10.1088/0022-3727/40/13/S06. {{cite journal}}: Unknown parameter |coauthors= ignored (|author= suggested) (help)

• Edited by Voth, G.A. (2009). Coarse-Graining of Condenced Phase and Biomolecular Systems. CRC Press. {{cite book}}: |last= has generic name (help)

• Multiscale Modeling Group: Institute of Physical & Theoretical Chemistry, University of Regensburg, Regensburg, Germany
• Multiscale modelling of hydrothermal biomass pretreatment for chip size optimization
• Multiscale Materials Modeling: Fourth International Conference, Tallahassee, FL, USA
• Multiscale Modeling Tools for Protein Structure Prediction and Protein Folding Simulations, Warsaw, Poland

• Computational mechanics
• Multiphysics
• Integrated computational materials engineering