MATEO: A software package for the molecular design of energetic materials

Mathieu, Didier

doi:10.1016/j.jhazmat.2009.11.030

Cited by 16 publications

(19 citation statements)

References 52 publications

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“…The present work aims at implementing a predictive scheme for Gurney velocities in the MATEO software [24]. It is motivated by the fact that available models for this property are not fully satisfactory from the viewpoint of dimensional considerations.…”

Section: Present Modeling Approachesmentioning

confidence: 99%

Prediction of Gurney Parameters Based on an Analytic Description of the Expanding Products

Mathieu

2014

Journal of Energetic Materials

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A new analytic model is introduced to predict Gurney parameters of explosives from their empirical formula, density, and formation enthalpy. It involves the H 2 O-CO 2 arbitrary, the assumption of a constant polytropic coefficient, and two empirical parameters. It is more physically grounded than previous models and proves twice more reliable, hence demonstrating that combining an analytic description of purely academic interest for hot gases with a small number of empirical parameters making up for its deficiencies proves superior to straightforward Quantitative Structure-Property Relationships (QSPR) approaches.

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Section: Present Modeling Approachesmentioning

confidence: 99%

Prediction of Gurney Parameters Based on an Analytic Description of the Expanding Products

Mathieu

2014

Journal of Energetic Materials

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“…They can be predicted by different complex and simple computer codes [5][6][7][8] or simple empirical methods [2,3]. For detonation of an explosive in a borehole, the relevant parameter is its strength.…”

Section: Introductionmentioning

confidence: 99%

A new approach to predict the strength of high energy materials

Keshavarz

Ghorbanifaraz

Rahimi

et al. 2011

Journal of Hazardous Materials

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“…As expected, the RM1 method was quickly implemented in several well-distributed programs, such as MOPAC, 18 Spartan, 20 GAMESS, 21 Amber, 22 HyperChem, 23 AMPAC, 24 MATEO, 25 eLBOW, 26 pDynamo 27 and ConGENER. 28 Of course, the advantage of RM1 over DFT and ab initio methods is the much reduced computation time for performing simulations.…”

Section: The Rm1 Projectmentioning

confidence: 66%

RM1 Semiempirical Model: Chemistry, Pharmaceutical Research, Molecular Biology and Materials Science

Lima¹,

Rocha²,

Freire³

et al. 2018

J. Braz. Chem. Soc.

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In this review, we show improvements to the semiempirical quantum chemical method RM1 and present a wide range of its applications as reported by researchers of various areas, such as theoretical, organic, physical, analytical, and inorganic chemistry, as well as their interfaces with medicinal chemistry, biology, and materials science. Success of RM1 is seemingly due to its ability to predict structural, energetic, electronic and wave function dependent properties of the investigated systems, coupled with its low computational demand required to perform calculations when compared to ab initio and density functional methods. Moreover, RM1 is widely available in several computational chemistry softwares, such as MOPAC, GAMESS, Amber, Spartan, HyperChem, and AMPAC. This review describes various case studies that perhaps can be of interest to researchers who might need a more solid basis from which to expand the frontier of applicability of RM1 to even more complex problems on larger systems.

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MATEO: A software package for the molecular design of energetic materials

Cited by 16 publications

References 52 publications

Prediction of Gurney Parameters Based on an Analytic Description of the Expanding Products

Prediction of Gurney Parameters Based on an Analytic Description of the Expanding Products

A new approach to predict the strength of high energy materials

RM1 Semiempirical Model: Chemistry, Pharmaceutical Research, Molecular Biology and Materials Science

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