Abstract
The standard enthalpy of formation of 1115 compounds from all chemicalgroups, were predicted using genetic algorithm-based multivariate linear regression (GA-MLR). The obtained multivariate linear five descriptors model by GA-MLR has correlationcoefficient ( R 2 = 0.9830 ). All molecular descriptors which have entered in this model arecalculated from chemical structure of any molecule. As a result, application of this modelfor any compound is easy and accurate.
Highlights
Physical and thermodynamic properties data of compounds are needed in the design and operation of industrial chemical processes
Standard enthalpy of formation or standard heat of formation, ∆H f o is an important fundamental physical property of compounds which is defined as change of enthalpy that accompanies the formation of 1 mole of compound in its standard state from its constituent elements in their standard states
In order to perform this algorithm, a program was written based on MATLAB (Mathworks Inc. software). This program finds the best multivariate linear model by genetic algorithm based multivariate linear regression (GA-MLR) which has proposed by Leardi et al [9] and we have used it to our previous works, successfully [10,11,12]
Summary
Physical and thermodynamic properties data of compounds are needed in the design and operation of industrial chemical processes. Standard enthalpy of formation or standard heat of formation, ∆H f o is an important fundamental physical property of compounds which is defined as change of enthalpy that accompanies the formation of 1 mole of compound in its standard state from its constituent elements in their standard states (the most stable form of the element at 1 atm of pressure and the specified temperature usually 298 K or 25 degrees Celsius). All elements in their standard states (such as hydrogen gas, solid carbon in the form of graphite, etc.) have standard enthalpy of formation of zero, as there is no change involved in their formation.
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