Research computing encompasses computing technology, data storage systems, advanced
instruments, visualization environments, data analysis and management systems, and
human resources, linked by high speed networks to make scientific and engineering
innovation and discoveries possible.
Research Computing is not limited to the sciences and engineering, but can serve the
arts, humanities and social sciences as well. It describes computing environments
that support advanced data acquisition, storage, management, integration, mining,
visualization and other computing and information processing services distributed
over the Internet beyond the scope of a single institution. While processors, storage
devices, sensors, and other physical assets are part of research computing, it is
more than connecting people with advanced networks and sophisticated applications
running on powerful computer systems—it involves those people as participants in the
knowledge generation, thereby giving them the opportunity to share expertise, tools
and facilities.
To enable simulations of complex systems that accurately reflect experimental observations,
continued advances in modeling potential energy surfaces and statistical mechanical
sampling are necessary. While studying systems relevant for catalysis, we develop
new theoretical and computational tools for the investigation of these complex chemical
systems. Our tool development efforts are at the interface between engineering, chemistry,
and physics, and are rooted in classical, statistical, and quantum mechanics with
a special focus on novel multiscale methods.
Andreas Heyden, Department of Chemical Engineering
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