2008
DOI: 10.1016/j.jmgm.2008.06.003
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Development of quantitative structure–property relationships for predictive modeling and design of energetic materials

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Cited by 39 publications
(31 citation statements)
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“…28 Due to the complexity of factors that might affect sensitivity, previous theoretical studies on predicting sensitivity have generally tried to correlate with a single molecular or crystal property of EMs, such as oxygen balance, molecular electronegativity, partial atomic charge, electrostatic potentials, weakest bond dissociation energy, band gap, free space per molecule, crystal packing mode, etc. [34][35][36][37][38][39][40][41][42][43][44][45] Despite significant efforts and many suggested empirical correlations, no clear understanding has been achieved of the relationships between sensitivity of materials, their molecular and crystalline structures, and chemical properties. 36,46 We consider that the four compounds, Si-PETN, PETN, Si-PETNC, and PETNC, provide a good challenge to develop an understanding of the molecular and structural determinants controlling their sensitivity to external stimuli.…”
Section: Introductionmentioning
confidence: 99%
“…28 Due to the complexity of factors that might affect sensitivity, previous theoretical studies on predicting sensitivity have generally tried to correlate with a single molecular or crystal property of EMs, such as oxygen balance, molecular electronegativity, partial atomic charge, electrostatic potentials, weakest bond dissociation energy, band gap, free space per molecule, crystal packing mode, etc. [34][35][36][37][38][39][40][41][42][43][44][45] Despite significant efforts and many suggested empirical correlations, no clear understanding has been achieved of the relationships between sensitivity of materials, their molecular and crystalline structures, and chemical properties. 36,46 We consider that the four compounds, Si-PETN, PETN, Si-PETNC, and PETNC, provide a good challenge to develop an understanding of the molecular and structural determinants controlling their sensitivity to external stimuli.…”
Section: Introductionmentioning
confidence: 99%
“…As described previously [23], we used two algorithms within CODESSA for the computation of descriptors and generation of multiple correlation equations. Briefly, the algorithms build correlation equations through forward simple least squares regression, and are called Best Multilinear Regression (BMLR) and Heuristic.…”
Section: Derivation Of Multiple Correlation Equationsmentioning
confidence: 99%
“…For new energetic compounds, the calculated properties can help to decide whether it is worth attempting a new and complex synthesis [5]. Recently a number of methods have been introduced to predict the thermochemical properties of different classes of energetic compounds, such as heat of sublimation [6][7][8], impact sensitivity [9][10][11][12], heat of formation [13][14][15][16][17], and detonation temperature [16,18].…”
Section: Introductionmentioning
confidence: 99%