The explosion of nanoscale research driven by computational chemistry is changing how materials are modeled, validated and synthesized. More than ever, research in energy storage, catalysis and alternative fuels is being conducted in a computational sandbox before it is validated experimentally and, ultimately, manufactured. This fast-growing and diverse field demands sophisticated and flexible means of visualization and analysis, and calls for new ways of leveraging high-performance computing resources.
Materials research poses distinct challenges to the conventional pipelines used in scientifi c visualization and analysis; chief among these is the enormous range in scale, from electrostatics to large-scale mechanics, of examined phenomena. Even problems at the same scale can exhibit different behavior and require different analysis. Nanomaterials research often straddles theory, model and reality. In this field in particular, it is imperative to disambiguate illustration and visualization. Choice of representation is important in understanding these problems; in many cases, standard analyses conducted on particles or individual surfaces are less helpful than measurements of electron density in a 3-D volume. Consequently, useful visualization of these phenomena calls for volume rendering techniques in addition to standard particle, ball-and-stick and isosurface modalities.
The scope and diversity of materials problems, as well as the multidisciplinary nature of applied chemistry and physics research, have led to a large but fragmented set of computation and visualization and analysis tools. The challenge is to identify which tools are appropriate for each given problem, and to leverage computational resources for simulation, visualization and analysis as effi ciently as possible.
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