Development of validated QSPR models for impact sensitivity of nitroaliphatic compounds

Prana, Vinca; Fayet, Guillaume; Rotureau, Patricia; Adamo, Carlo

doi:10.1016/j.jhazmat.2012.07.036

Cited by 31 publications

(38 citation statements)

References 55 publications

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“…For C-NO 2 compounds, the three OECD compliant models recently reported yield good fits (0.88 < R 2 < 0.90). 32 In addition, they prove quite robust (0.85 < Q 2 < 0.90). However, they differ significantly regarding their predictive value, with 0.73 < R X 2 < 0.88 and 0.19 < RMSE X < 0.29.…”

Section: Modelsmentioning

confidence: 96%

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Physics-Based Modeling of Chemical Hazards in a Regulatory Framework: Comparison with Quantitative Structure–Property Relationship (QSPR) Methods for Impact Sensitivities

Mathieu

2016

Ind. Eng. Chem. Res.

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A semiempirical model based on simple physical assumptions is rigorously compared to a combination of two recent state-of-the-art quantitative structure−property relationship (QSPR) methods for impact sensitivities of nitroaliphatic and nitramine compounds. For most datasets considered, it yields slightly better predictions than QSPR schemes, which is noteworthy, considering the fact that it relies only on three adjustable parameters and an equation developed independently of the data. Further advantages of this approach include physical interpretability, enhanced robustness, and wider applicability. Therefore, there is no doubt that such physics-based models provide valuable alternatives to the purely empirical relationships usually employed in regulatory contexts, especially in situations where experimental data are scarce.

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Section: Modelsmentioning

confidence: 96%

“…It is presently reoptimized and validated using the training and test sets employed in the QSPR study. 32 The resulting procedure is compared to various QSPR models in Table 2. The quality of fit is better for the QSPR methods, presumably because of the fact that they involve more adjustable parameters.…”

Section: Semiempirical Modelmentioning

confidence: 99%

Physics-Based Modeling of Chemical Hazards in a Regulatory Framework: Comparison with Quantitative Structure–Property Relationship (QSPR) Methods for Impact Sensitivities

Mathieu

2016

Ind. Eng. Chem. Res.

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“…Despite the limitations and uncertainties associated with the impact test, there are many approaches to assess impact sensitivity through different molecular properties, e.g. simple correlations [1][2][3][4]12,14,18,21] and quantum mechanical methods [2,5,[22][23][24][25][26][27] as well as artificial neural network and quantitative structure-property relationship (QSPR) on the basis of molecular structure or suitable property [28][29][30][31][32], especially within chemical families.…”

Section: Introductionmentioning

confidence: 99%

Prediction of Sensitivity of Energetic Compounds with a New Computer Code

Keshavarz

Motamedoshariati

Moghayadnia

et al. 2014

Propellants Explo Pyrotec

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Simple and reliable approaches have been recently introduced to predict impact, electrostatic and shock sensitivities of energetic compounds [1][2][3][4][5][11][12][13][14][15][16][17][18][19][20][21]. Impact SensitivityThe impact sensitivity test involves subjecting a sample to the impact of the standard mass falling from different Abstract: Impact, electrostatic, and shock sensitivities of energetic compounds are three important parameters for the assessment of hazardous energetic materials. A novel easy to handle and user-friendly computer code, written in Visual Basic, is introduced to predict these parameters, by solely using the molecular structure of an energetic molecule. It is able to predict impact sensitivity for different types of energetic compounds including nitropyridines, nitroimidazoles, nitropyrazoles, nitrofurazanes, nitrotriazoles, nitropyrimidines, polynitro arenes, benzofuroxans, polynitro arenes with a-CH, nitramines, nitroaliphatics, nitroaliphatic containing other functional groups, and nitrate energetic compounds. It can also provide reliable results for electrostatic and shock sensitivities of some classes of high explosives including nitroaromatic and nitramine compounds. The prediction of this code give good values for some newly reported energetic compounds, where experimental data are available.

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“…Numerous studies have been done to relate impact sensitivity to various properties of pure HE such as oxygen balance [3][4][5], quantum chemical calculation [6][7][8][9], physicochemical properties and elemental composition of HE [2,[10][11][12][13], quantitative structureproperty relationship (QSPR) models using computational data mining methods [14][15][16][17][18][19] etc. Detonation velocity and the heat of detonation are used in this paper to predict impact sensitivity of the selected mixtures of aluminized HE.…”

Section: Introductionmentioning

confidence: 99%

Prediction of the impact sensitivity of aluminized explosive mixtures using the response surface methodology

Bajić¹,

Jeremić²,

Jevremović³

et al. 2015

Sci Tech Rev

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The possibility of the impact sensitivity prediction based on the physicochemical properties and element composition of explosives contributes to a faster research of novel high explosives (HE), reduces the research costs and helps to improve the explosive safety. This paper analyzes the existing methods for the prediction of impact sensitivity and introduces a response surface methodology (RSM). The new method comprises a correlation between impact sensitivity and two primary properties of HE: detonation velocity and heat of detonation. Calculated impact sensitivities are compared to the experimental values taken from the literature in order to validate the approach.

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Development of validated QSPR models for impact sensitivity of nitroaliphatic compounds

Cited by 31 publications

References 55 publications

Physics-Based Modeling of Chemical Hazards in a Regulatory Framework: Comparison with Quantitative Structure–Property Relationship (QSPR) Methods for Impact Sensitivities

Physics-Based Modeling of Chemical Hazards in a Regulatory Framework: Comparison with Quantitative Structure–Property Relationship (QSPR) Methods for Impact Sensitivities

Prediction of Sensitivity of Energetic Compounds with a New Computer Code

Prediction of the impact sensitivity of aluminized explosive mixtures using the response surface methodology

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