Recent advances for assessment of the condensed phase heat of formation of high-energy content organic compounds and ionic liquids (or salts) to introduce a new computer code for design of desirable compounds

Keshavarz, Mohammad Hossein; Jafari, Mohammad; Ebadpour, Reza

doi:10.1016/j.fluid.2020.112913

Cited by 5 publications

(2 citation statements)

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“…Due to the existence of various molecular interactions, polymorphism, and molecular packing in some solid materials, the prediction of the condensed phase HOFs is more difficult [29]. However, the condensed phase HOF of energetic compounds has been predicted by several group additivity (GA) [29], quantum mechanical (QM) [30], and quantitative structure-property relationships (QSPR) [31,32] methods. In GA methods, assemblages of neighboring atoms are defined as groups, and the enthalpy of the molecule is calculated by summing the contributions of these groups.…”

Section: Chemical Thermodynamics and Thermochemistrymentioning

confidence: 99%

“…Multiple linear regression (MLR), support vector machine (SVM), nonlinear regression (NLR), artificial neural network (ANN), partial least squares (PLS), and genetic algorithm (GA) are examples of statistical tools that are utilized to derive algorithms or mathematical equations between properties and descriptors [37]. Additionally, it has been demonstrated that molecular fragments can also be employed to estimate the heats of formation of various classes of energetic compounds [31]. MLR analyze the association between a response variable and several explanatory variables.…”

Section: Chemical Thermodynamics and Thermochemistrymentioning

confidence: 99%

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Simple Method for Predicting the Heats of Formation of Energetic Metal–Organic Frameworks

Zeinab Dalirandeh,

Jafari,

Mousaviazar

2024

Russ. J. Phys. Chem.

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The heats of formation (HOF) of energetic materials is crucial in determining their performance. A novel approach has been introduced to accurately predict the condensed phase HOF of energetic metal-organic frameworks (EMOFs). The experimental condensed phase HOF data of 63 EMOFs were utilized to develop and evaluate the model. This model relies on particular chemical bonds, elemental composition, and some of the specific structural parameters that can be obtained from the chemical structures of EMOFs. This model can be easily applied to EMOFs with intricate compositions and structures, without the need for complicated computer codes. Statistical parameters along with the internal and external validation approaches were employed to assess the accuracy, precision, goodness-of-fit, and goodness-of-prediction of the model. Values of the coefficients of determination in training set, as well as internal and external validation, i.e., R2, $${\text{Q}}_{{{\text{LOO}}}}^{2}$$, $${\text{Q}}_{{5{\text{-fold}}}}^{2}$$, and $$R_{{{\text{External}}}}^{2}$$ are 0.96, 0.93, 0.91, and 0.94, respectively.

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