Towards Nanomaterial Design Automation: Hierarchical Computational Architecture Development

Molecular modeling and simulation has been recognized as an effective tool for gaining a comprehensive and insightful understanding of nanomaterial structure-property relationships, which are critical for nanomaterial development. Note that nanomaterial development is a very complicated task involving the design and management of massive runs of simulations and numerous types of subtasks in multiple computational stages. Thus, an effective and efficient nanomaterial development must rely on the appropriate design of a computational architecture as well. In this work, we introduce a generic task-distributed hierarchical computational architecture for nanomaterial design, which can be readily constructed on a usual cluster system. The developed computational architecture, together with the algorithms for hierarchical computations, can facilitate design automation with a high computational efficiency. The efficacy of the architecture will be demonstrated through a case study on nanopaint design, where various fundamental structure-property correlations as well as design guidelines can be fully derived.