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Title: Predicting Real Optimized Materials: A New Multi-Scale Approach Enabling Ultra-Long Timescale Dynamical Simulation and Optimization of High Energy Density Materials

Abstract

The design and synthesis of novel new high energy density materials (HEDM) is more art than science. Many potential molecular systems have been identified computationally. Most computational studies are performed using traditional gas-phase quantum chemistry methods, which determine high-energy structures of a particular cluster of atoms that are geometrically constrained. At first, a minimum energy optimization of the molecular structure is sought. Once located, the adiabatic stability to decomposition via several channels is explored by locating energy barriers to decomposition. These calculations could then suggest whether a particular cluster is stable and is a viable HEDM candidate. This computational procedure offers nothing in way of practical steps about the synthesis of the HEDM molecule starting from currently existing materials, and therefore is disconnected from experimental undertakings for the realization of novel HEDMs. We propose to apply a new multiscale simulation method for the study of shocked high energy density materials enabling, for the first time, the elucidation of chemistry under shock conditions on the 100 ps timescale. (E. J. Reed, L. E. Fried, J. D. Joannopoulos, Phys. Rev. Lett. 90, 235503 (2003)) The method combines molecular dynamics and the Euler equations for compressible flow. The method allows the molecular dynamicsmore » simulation of the system under dynamical shock conditions for orders of magnitude longer time periods than is possible using the popular non-equilibrium molecular dynamics (NEMD) approach. A computational speedup of 10{sup 5} has been demonstrated for an example calculation for a silicon model potential. Computational speedups orders of magnitude higher are possible in the study of high energy-density materials at the condensed phase, enabling the computational simulation and optimization of these materials for the first time. Our finding will guide experimental realization of such materials by providing the exact thermodynamical variables for the existence of such materials. Proposed systems of study include polynitrogen, oxygen, and their mixtures.« less

Authors:
; ;
Publication Date:
Research Org.:
Lawrence Livermore National Lab., CA (US)
Sponsoring Org.:
US Department of Energy (US)
OSTI Identifier:
15007316
Report Number(s):
UCRL-ID-154140
TRN: US200415%%95
DOE Contract Number:  
W-7405-ENG-48
Resource Type:
Technical Report
Resource Relation:
Other Information: PBD: 15 Jul 2003
Country of Publication:
United States
Language:
English
Subject:
36 MATERIALS SCIENCE; ATOMS; CHEMISTRY; COMPRESSIBLE FLOW; DESIGN; ENERGY DENSITY; MIXTURES; MOLECULAR STRUCTURE; OPTIMIZATION; OXYGEN; SILICON; SIMULATION; STABILITY; SYNTHESIS

Citation Formats

Reed, E, Manaa, R, and Fried, L. Predicting Real Optimized Materials: A New Multi-Scale Approach Enabling Ultra-Long Timescale Dynamical Simulation and Optimization of High Energy Density Materials. United States: N. p., 2003. Web. doi:10.2172/15007316.
Reed, E, Manaa, R, & Fried, L. Predicting Real Optimized Materials: A New Multi-Scale Approach Enabling Ultra-Long Timescale Dynamical Simulation and Optimization of High Energy Density Materials. United States. doi:10.2172/15007316.
Reed, E, Manaa, R, and Fried, L. Tue . "Predicting Real Optimized Materials: A New Multi-Scale Approach Enabling Ultra-Long Timescale Dynamical Simulation and Optimization of High Energy Density Materials". United States. doi:10.2172/15007316. https://www.osti.gov/servlets/purl/15007316.
@article{osti_15007316,
title = {Predicting Real Optimized Materials: A New Multi-Scale Approach Enabling Ultra-Long Timescale Dynamical Simulation and Optimization of High Energy Density Materials},
author = {Reed, E and Manaa, R and Fried, L},
abstractNote = {The design and synthesis of novel new high energy density materials (HEDM) is more art than science. Many potential molecular systems have been identified computationally. Most computational studies are performed using traditional gas-phase quantum chemistry methods, which determine high-energy structures of a particular cluster of atoms that are geometrically constrained. At first, a minimum energy optimization of the molecular structure is sought. Once located, the adiabatic stability to decomposition via several channels is explored by locating energy barriers to decomposition. These calculations could then suggest whether a particular cluster is stable and is a viable HEDM candidate. This computational procedure offers nothing in way of practical steps about the synthesis of the HEDM molecule starting from currently existing materials, and therefore is disconnected from experimental undertakings for the realization of novel HEDMs. We propose to apply a new multiscale simulation method for the study of shocked high energy density materials enabling, for the first time, the elucidation of chemistry under shock conditions on the 100 ps timescale. (E. J. Reed, L. E. Fried, J. D. Joannopoulos, Phys. Rev. Lett. 90, 235503 (2003)) The method combines molecular dynamics and the Euler equations for compressible flow. The method allows the molecular dynamics simulation of the system under dynamical shock conditions for orders of magnitude longer time periods than is possible using the popular non-equilibrium molecular dynamics (NEMD) approach. A computational speedup of 10{sup 5} has been demonstrated for an example calculation for a silicon model potential. Computational speedups orders of magnitude higher are possible in the study of high energy-density materials at the condensed phase, enabling the computational simulation and optimization of these materials for the first time. Our finding will guide experimental realization of such materials by providing the exact thermodynamical variables for the existence of such materials. Proposed systems of study include polynitrogen, oxygen, and their mixtures.},
doi = {10.2172/15007316},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Tue Jul 15 00:00:00 EDT 2003},
month = {Tue Jul 15 00:00:00 EDT 2003}
}

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