Crystal density predictions for nitramines based on quantum chemistry

Qiu, Ling; Xiao, Heming; Gong, Xuedong; Ju, Xue‐Hai; Zhu, Weihua

doi:10.1016/j.jhazmat.2006.06.135

Cited by 117 publications

(63 citation statements)

References 42 publications

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“…For the NH 4 + cation we instead used the experimentally determined volume [57] of 0.021 nm 3 . A similar procedure has been successfully demonstrated for nitramine compounds, [58] and our results are in excellent agreement with experimental data, which is available for the ADN salt. [39] Enthalpies of formation: Enthalpies of formation for the gas-phase ions (DH 0 fðvacÞ ) 1-4 were obtained at the CBS-QB3 level of theory.…”

Section: Methodssupporting

confidence: 88%

Kinetic Stability and Propellant Performance of Green Energetic Materials

Rahm

Brinck

2010

Chemistry A European J

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Outside contact: Cells in multicellular organisms regulate their adhesion through specialized integrin receptors, which relay signals bidirectionally between the inside and outside of cells. The transmembrane domains (see picture, blue; the integrin–talin complex is red and green) of integrins are the center of the signaling process. Recently, structures of these domains have been reported that shed light on the signal transduction mechanism.

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Section: Methodssupporting

confidence: 88%

Kinetic Stability and Propellant Performance of Green Energetic Materials

Rahm

Brinck

2010

Chemistry A European J

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“…V eff can also be determined by dividing the volume of the unit cell by the number of molecules or formula units that it contains. For molecular C,H,N,O solids, V eff can be approximated quite well as the volume V(0.001) that is enclosed within the molecule's 0.001 au surface [25][26][27]:…”

Section: Molecular Vs Ionic Crystal Latticesmentioning

confidence: 99%

“…For both types of solids, the V eff can be improved by taking explicit account of the electrostatic potentials on the molecular or ionic surfaces [24][25][26]. The corrected V eff can then be used to make reasonably good estimates of crystal densities via Equation (1).…”

Section: Molecular Vs Ionic Crystal Latticesmentioning

confidence: 99%

Electrostatic Potentials, Intralattice Attractive Forces and Crystal Densities of Nitrogen-Rich C,H,N,O Salts

2016

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Abstract:The computed electrostatic potentials on C,H,N,O molecular solids and nitrogen-rich C,H,N,O salts are used in analyzing and comparing intralattice attractive forces and crystal densities in these two categories of compounds. Nitrogen-rich C,H,N,O salts are not an assured path to high densities. To increase the likelihood of high densities, small cations and large anions are suggested. Caution is recommended in predicting benefits of nitrogen-richness for explosive compounds.

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“…For estimating the crystal density of available energetic materials, various methods have been developed. These include electrostatic potentials using quantum-mechanically determined molecular volumes [11][12][13][14][15], group additivities [8,9,[16][17][18], empirical methods [19][20][21][22] and Quantitative Structure-Property Relationships (QSPR) [23].…”

Section: Introductionmentioning

confidence: 99%

Prediction of the Density of Energetic Materials on the Basis of their Molecular Structures

Rahimi

Keshavarz

Akbarzadeh

2016

Cent. Eur. J. Energ. Mater.

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Abstract:The density of an energetic compound is an essential parameter for the assessment of its performance. A simple method based on quantitative structureproperty relationship (QSPR) has been developed to give an accurate prediction of the crystal density of more than 170 polynitroarenes, polynitroheteroarenes, nitroaliphatics, nitrate esters and nitramines as important classes of energetic compounds, by suitable molecular descriptors. The evaluation techniques included cross-validation, validation through an external test set, and Y-randomization for multiple linear regression (MLR) and training state analysis for artificial neural network (ANN), and were used to illustrate the accuracy of the proposed models. The predicted MLR results are close to the experimental data for both the training and the test molecular sets, and for all of the molecular sets, but not as close as the ANN results. The ANN model was also used with 20 hidden neurons that gave good result. The results showed high quality for nonlinear modelling according to the squared regression coefficients for all of the training, validation and the test sets (R 2 = 0.999, 0.914 and 0.931, respectively). The calculated results have also been compared with those from several of the best available predictive methods, and were found to give more reliable estimates.

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Crystal density predictions for nitramines based on quantum chemistry

Cited by 117 publications

References 42 publications

Kinetic Stability and Propellant Performance of Green Energetic Materials

Kinetic Stability and Propellant Performance of Green Energetic Materials

Electrostatic Potentials, Intralattice Attractive Forces and Crystal Densities of Nitrogen-Rich C,H,N,O Salts

Prediction of the Density of Energetic Materials on the Basis of their Molecular Structures

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