Theoretical Foundations of Multiscale Modelling
- 1st Edition - June 1, 2025
- Imprint: Elsevier
- Authors: Michele Cascella, Raffaello Potestio
- Language: English
- Paperback ISBN:9 7 8 - 0 - 3 2 3 - 8 8 4 4 0 - 2
- eBook ISBN:9 7 8 - 0 - 3 2 3 - 9 0 6 0 6 - 7
Multiscale modelling approaches can provide valuable insight to researchers across a broad range of fields. At the same time, the interdisciplinary applicability of these ap… Read more
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Request a sales quoteMultiscale modelling approaches can provide valuable insight to researchers across a broad range of fields. At the same time, the interdisciplinary applicability of these approaches means that both new learners and experienced researchers may not have a clear understanding of the theoretical and computational fundamentals underpinning these methods. Theoretical Foundations of Multiscale Modelling aims to address this knowledge gap, providing a clear insight to the thermodynamical and statistical mechanical foundations of methods commonly employed, and highlighting the potential and limitations of each approach.
Starting with an overview of the basics of statistical mechanics, the first chapters of the book illustrate the general theory of molecular modelling, the concepts and methods for the study of complex molecular systems, then progressing to cover key strategies employed to perform computational calculations and simulations. The second part of the book reviews how the most recent, cutting-edge tools of the trade are used in practice through a selection of case studies highlighting multiscale modelling, multiple resolution simulation methods, and machine-learning applications. This is also achieved by presenting case studies from recent scientific literature, highlighting the advantages of a multiscale treatment for the understanding of complex molecular phenomena.
Drawing on the experience of its authors, Theoretical Foundations of Multiscale Modelling is an insightful guide for all those learning, applying, or interested in exploring multiscale modelling methods for their work.
- Follows a pedogeological path, taking readers from the simplest to the most complex notions
- Rigorously shows the connections between theory and modeling, providing a critical understanding of commonly used models and their level of applicability
- Provides a rich list of case studies to demonstrate the application of theoretical principles in practice
Students in computational chemistry, condensed matter physics and materials sciences, researchers from across chemistry, physics and materials sciences who use or are interested in using multiscale modelling in their work
1. Introduction to soft matter
2. Foundations of classical mechanics
3. Foundations of statistical mechanics
4. Structure and thermodynamics of fluids from spatial distribution functions
5. Modelling atomic systems
6. Simulation and sampling
7. Stochastic dynamics
8. Enhanced sampling and free energy
9. From critical phenomena to coarse-graining
10. Coarse-graining molecular systems
11. The relative entropy method
12. Boltzmann inversion, iterative Boltzmann inversion and inverse Monte Carlo
13. Gradient-based methods for multiscale modelling
14. Hybrid multiresolution approaches
15. Concluding remarks
- Edition: 1
- Published: June 1, 2025
- Imprint: Elsevier
- No. of pages: 500
- Language: English
- Paperback ISBN: 9780323884402
- eBook ISBN: 9780323906067
MC
Michele Cascella
Michele Cascella got his PhD in Statistical and Biological Physics in 2004 at the International School for Advanced Studies (SISSA) in Trieste. After a postdoctoral experience at EPFL, in 2008, being awarded a Swiss National Science Foundation professorship grant, he began his independent career as Assistant Professor at the University of Bern. Since 2016, he is Full Professor in Theoretical Chemistry at the University of Oslo. His research is dedicated to the development and application of multi-scale and multi-resolution methods for biochemical systems in the condensed phase. Recent focus is on soft systems combining computer simulations with SAXS/SANS experiment, and in molecular modelling of main group organometallic compounds (Grignard reagents), using ab initio and machine learning approaches.
Affiliations and expertise
Department of Chemistry and Hylleraas Centre for Quantum Molecular Sciences, University of Oslo, NorwayRP
Raffaello Potestio
Raffaello Potestio received his PhD in Statistical and Biological Physics from the International School for Advanced Studies (SISSA) in Trieste, Italy, in 2010, with a PhD thesis on coarse-grained models of protein structure and interactions. In November 2010 he started a postdoc in the Theory group at the Max Planck Institute for Polymer Research (MPIP) in Mainz, Germany; here, between August 2013 and December 2017, he was Group Leader of the Statistical Mechanics of Biomolecules group. In 2017 he was awarded an ERC starting grant and moved to the University of Trento, Italy, where he currently is associate professor in Physics. His main research interests are the development and application of coarse-graining strategies for soft and biological matter, and the investigation of the relation between model resolution and physical properties in complex systems.
Affiliations and expertise
Department of Physics, University of Trento, Italy