Reliable and Versatile Model for the Density of Liquids Based on Additive Volume Increments

Mathieu, Didier; Bouteloup, Rémi

doi:10.1021/acs.iecr.6b03809

Cited by 17 publications

(12 citation statements)

References 45 publications

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“…Similar to enthalpy of formation, additive models, which are based on both the higher- − and zeroth-order approximations, were also applied for density. As in the previous section, we apply the zeroth-order approximation based on pure atomic volumes (Figure ), which are obtained from the corresponding van der Waals radii .…”

Section: Resultsmentioning

confidence: 99%

Magic of Numbers: A Guide for Preliminary Estimation of the Detonation Performance of C–H–N–O Explosives Based on Empirical Formulas

Bondarchuk

2021

Ind. Eng. Chem. Res.

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In this paper, we report a comprehensive analytical study of the factors influencing the detonation properties of C–H–N–O explosives. Besides the commonly applied parameters, namely, solid-state enthalpy of formation (ΔH f) and crystal density (d c), for which simple zeroth-order additive models based on the atomic increments are developed in this work, we also consider compositional factor being an intrinsic characteristic of each single empirical formula. Using a wide number of reference molecules (320 for ΔH f and 360 for d c), we have developed empirical equations, which provide rather good correlation coefficients R 2 = 0.90 and 0.80 for ΔH f and d c, respectively. Knowing these two equations and empirical formula, one can predict the detonation properties of a C–H–N–O explosive using a pocket calculator. Of course, such an approach, which completely neglects chemical structure, can be applied mainly for structurally similar compounds. However, having significant differences between the predicted detonation properties of two compositions, the account of their exact structures cannot reorder the predicted values. Thus, this paper can be used as a simple guide for molecular engineering and explosive structure enhancement. For this purpose, we provide a list of all compositions with the predicted properties up to C30H30N30O30 in the Supporting Information. To demonstrate how it works, we have applied the developed approach along with quantum-chemical calculations to model chemical structures outperforming ε-hexanitrohexaazaisowurtzitane (the most powerful explosive) in detonation performance.

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Section: Resultsmentioning

confidence: 99%

Magic of Numbers: A Guide for Preliminary Estimation of the Detonation Performance of C–H–N–O Explosives Based on Empirical Formulas

Bondarchuk

2021

Ind. Eng. Chem. Res.

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“…60 In other words, we rely on the expectation that noise in the reference data arising from random errors gets averaged out in a large data set. 61 A further advantage of a large data set is that rampant near-linearities that might plague smaller data sets can be alleviated, thus contributing to reduce the model sloppiness. 62 Systematic errors that might arise for specific chemical families are taken into account through the above-mentioned structural corrections.…”

Section: ■ Data Sets and Parametrizationmentioning

confidence: 99%

“…In the lack of sufficient amounts of reliable data to confidently fit all 68 APC parameters on the basis of a minimal number of accurate reference values, we assume that quantity can at least partially make up for quality, as suggested by the demonstration that data availability is as important as data quality to develop successful models . In other words, we rely on the expectation that noise in the reference data arising from random errors gets averaged out in a large data set . A further advantage of a large data set is that rampant near-linearities that might plague smaller data sets can be alleviated, thus contributing to reduce the model sloppiness .…”

Section: Data Sets and Parametrizationmentioning

confidence: 99%

Atom Pair Contribution Method: Fast and General Procedure To Predict Molecular Formation Enthalpies

Mathieu

2018

J. Chem. Inf. Model.

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An atom pair contribution (APC) model aimed at predicting the gas-phase formation enthalpy (ΔH°) of molecules is reported. In contrast to bond contribution (BC) or group contribution (GC) methods, it relies on increments associated with pairs of bonded and geminal atoms along with 15 structural corrections. Another distinctive feature of the present APC method is the large amount of experimental and high-level theoretical data specially compiled in this work to fit and validate the model (2671 entries). Unlike GC methods, the present APC model has wide applicability with the number of adjustable parameters limited to 68. Although it requires only a structural formula as input and involves only back-of-the-envelope calculations, it is more reliable than state-of-the-art quantitative structure-property relationship methods, popular semiempirical Hamiltonians, and even low-level density functional theory approaches based on gradient-corrected functionals. It is therefore a valuable tool for fast screening applications or whenever chemical accuracy is not necessary.

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“…In particular, a feature shared by all recent HSP prediction methods is the fact that they do not explicitly involve the molar volume V m . Actually, there appears to be no reason to not take advantage of this property as it is available for most synthesized compounds on the market and may otherwise be easily evaluated to within a few percents from experiment. − On the other hand, additive contributions to E p / E h are introduced only for groups with heteroatoms/proton acceptors or donors. For the dispersion component E d , all atoms must in principle be considered.…”

Section: Present Strategymentioning

confidence: 99%

Pencil and Paper Estimation of Hansen Solubility Parameters

Mathieu

2018

ACS Omega

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Simple procedures to estimate Hansen solubility parameter (HSP) components from structural formulas are investigated. The best results are obtained using a simple relationship with molar volume and refractivity for the dispersion component, and using additivity models based on tailored fragments specifically designed for the polar and hydrogen bonding components. Despite large errors for some classes of chemicals, including small inorganic molecules, ionic liquids, and high halogen compounds, these models yield average absolute deviations from reference on par with state-of-the-art models and lower than reported using molecular dynamics simulations or nonlinear quantitative structure–property relationship models based on a limited set of quantum chemical descriptors. In contrast to group contribution methods that are either more restricted in scope or heavily parameterized, they are thoroughly validated and very easy to apply. Furthermore, the errors observed are easy to rationalize and may usually be anticipated. This work sheds light on some limitations inherent to pure additivity approaches for HSP prediction and provides a first step toward better models. A Python script implementing the procedure and the fully detailed results are provided as the Supporting Information.

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Reliable and Versatile Model for the Density of Liquids Based on Additive Volume Increments

Cited by 17 publications

References 45 publications

Magic of Numbers: A Guide for Preliminary Estimation of the Detonation Performance of C–H–N–O Explosives Based on Empirical Formulas

Magic of Numbers: A Guide for Preliminary Estimation of the Detonation Performance of C–H–N–O Explosives Based on Empirical Formulas

Atom Pair Contribution Method: Fast and General Procedure To Predict Molecular Formation Enthalpies

Pencil and Paper Estimation of Hansen Solubility Parameters

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