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Frontiers in Materials
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Grand Challenges in Computational Materials Science: From Description to Prediction at all Scales

Authors: Thomas Heine;

Grand Challenges in Computational Materials Science: From Description to Prediction at all Scales

Abstract

TRADITIONAL COMPUTATIONAL MATERIALS SCIENCE Materials science is historically linked to engineering driven by the need of materials with specific properties to manufacture infrastructure, machines, and devices. Therefore, there has always been a need for novel and better materials: stronger and lighter-weight, less expensive, easier to process, more durable, and having less environmental impact. Computational means have supported the design of tools, buildings, and vehicles. While for centuries materials have been designed in an ad hoc manner, sometimes guided by empirically developed “rules of thumb,” the field changed when those rules were translated into the language of partial differential equations. The rise of computers and the finite elements method allowed first descriptions of the intrinsic materials properties, and computer simulations on the load-stress relation of buildings, of crack propagation in materials, or on the stability of composite materials became state-of-the-art with great impact on research and development in academia and industry.

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Keywords

Technology, materials science, nanotechnology, T, graphene, GPU computing, Parallel Computing, multiscale simulation model, Nanotechnology, Cloud computing, Graphene, density-functional theory, Materials, computational materials science, Metal-Organic Frameworks

  • BIP!
    Impact byBIP!
    citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    11
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
11
Top 10%
Average
Average
gold