Special Issue "Computational Multiscale Modeling and Simulation in Materials Science"
Deadline for manuscript submissions: closed (31 December 2016)
Dr. Martin O. Steinhauser
Department of Chemistry, University of Basel, Klingelbergstrasse 80, CH-4056 Basel, Switzerland
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Interests: multiscale modeling and simulation of biological and soft matter systems; cancer research; multi-scale characterization of materials; image-based analysis; composite materials; shock wave physics; coarse-grained modeling; polymer physics; method development and high-performance computing
Computational modeling of materials on multiscales, along with high-performance computer simulations, are gradually becoming reliable tools for scientific investigations in materials science, complementing traditional experimental engineering approaches of macroscopic constitutive descriptions of materials and their optimization in elaborate trial and error experiments. The linkage between material microstructure and materials properties is at the heart of all materials modeling. Multiscale modeling approaches are required to make this link from the electronic and atomic structure of matter and discrete structural defects to the continuum descriptions appropriate at larger scales.
Although the field of Computational Multiscale Modeling is very much still under development, modern Multiscale Materials Modeling techniques are clearly demonstrating the ability to solve computational materials problems with unprecedented levels of rigor and accuracy and to provide powerful new tools for materials design.
By its very nature, Computational Multiscale Modeling is a very interdisciplinary research field with useful contributions from physics, chemistry, materials science, and biology, as well as computer science, mathematics, and mechanics. Consequently, this Special Issue will address all research areas pertaining to the general theme of linking structural features on various length or time scales with material properties, which includes:
- Polymer Physics, Modeling of Biological and Soft Materials.
- Crystalline and Granular Structures in Metals, Glasses or Ceramic Materials.
- Modeling of Multifunctional or Composite Materials.
- Micromechanics and Microstructure Modeling.
- Statistical Approaches.
- Material Behavior under Shock and Impact.
- Scale-Bridging Atomistic and Coarse-Grained Approaches.
- Particle-Based, Meshfree Method Development.
Dr. rer. nat. Martin O. Steinhauser
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Materials is an international peer-reviewed open access monthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
- multiscale modeling
- shock and impact
- biological and soft materials
- molecular dynamics simulations
- atomistic simulations
- ab initio methods
- meshfree particle methods
- high-performance scientific computing