Network theory is used to formulate an atomistic material network. Spectral sparsification is applied to the network as a method for approximating the interatomic forces. Local molecular forces and the total force balance is quantified when the internal forces are approximated. In particular, we compare spectral sparsification to conventional thresholding (radial cut-off distance) of molecular forces for a Lennard-Jones potential and a Coulomb potential. The spectral sparsification for the Lennard-Jones potential yields comparable results while spectral sparsification of the Coulomb potential outperforms the thresholding approach. The results show promising opportunities which may accelerate molecular simulations containing long-range electrical interactions which are relevant to many multifunctional materials.
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ASME 2017 Conference on Smart Materials, Adaptive Structures and Intelligent Systems
September 18–20, 2017
Snowbird, Utah, USA
Conference Sponsors:
- Aerospace Division
ISBN:
978-0-7918-5825-7
PROCEEDINGS PAPER
Network Theoretic Approach to Atomistic Material Modeling Using Spectral Sparsification
Peter C. Woerner,
Peter C. Woerner
Florida State University, Tallahassee, FL
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Aditya G. Nair,
Aditya G. Nair
Florida State University, Tallahassee, FL
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Kunihiko Taira,
Kunihiko Taira
Florida State University, Tallahassee, FL
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William S. Oates
William S. Oates
Florida State University, Tallahassee, FL
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Peter C. Woerner
Florida State University, Tallahassee, FL
Aditya G. Nair
Florida State University, Tallahassee, FL
Kunihiko Taira
Florida State University, Tallahassee, FL
William S. Oates
Florida State University, Tallahassee, FL
Paper No:
SMASIS2017-3917, V001T08A012; 8 pages
Published Online:
November 9, 2017
Citation
Woerner, PC, Nair, AG, Taira, K, & Oates, WS. "Network Theoretic Approach to Atomistic Material Modeling Using Spectral Sparsification." Proceedings of the ASME 2017 Conference on Smart Materials, Adaptive Structures and Intelligent Systems. Volume 1: Development and Characterization of Multifunctional Materials; Mechanics and Behavior of Active Materials; Bioinspired Smart Materials and Systems; Energy Harvesting; Emerging Technologies. Snowbird, Utah, USA. September 18–20, 2017. V001T08A012. ASME. https://doi.org/10.1115/SMASIS2017-3917
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