A particular problem in the area of liquid-state thermodynamics is the sourcing of reliable thermodynamic constants. These constants are necessary for the successful prediction of the free energy state of the system; without this information it is impossible to model the equilibrium phases of the system.
Obtaining this free energy data is not a trivial problem, and requires careful experiments, such as calorimetry, to successfully measure the energy of the system. Even when this work is performed it is infeasible to attempt to conduct this work for every single possible class of chemicals, and the binary, or higher, mixtures thereof. To alleviate this problem, free energy prediction models, such as UNIFAC, are employed to predict the system's energy based on a few previously measured constants.
Although it is theoretically possible to calculate some of these parameters using ab initio computer simulations, several major problems with this approach exist; firstly, and most importantly, the computational resources for such calculations are immense - scaling extremely unfavourably for systems with more than a few atoms. Secondly the energies obtained from these calculations obtained from ab initio simulations often require experimental verification to confirm their results. Finally such calculations require a significant level of expertise and a good understanding of quantum chemistry. Thus the need for simplified models that still successfully predict the thermodynamic state of the system, such as UNIFAC.
A particular problem in the area of liquid-state thermodynamics is the sourcing of reliable thermodynamic constants. These constants are necessary for the successful prediction of the free energy state of the system; without this information it is impossible to model the equilibrium phases of the system.
Obtaining this free energy data is not a trivial problem, and requires careful experiments, such as calorimetry, to successfully measure the energy of the system. Even when this work is performed it is infeasible to attempt to conduct this work for every single possible class of chemicals, and the binary, or higher, mixtures thereof. To alleviate this problem, free energy prediction models, such as UNIFAC, are employed to predict the system's energy based on a few previously measured constants.
Although it is theoretically possible to calculate some of these parameters using ab initio computer simulations, several major problems with this approach exist; firstly, and most importantly, the computational resources for such calculations are immense - scaling extremely unfavourably for systems with more than a few atoms. Secondly the energies obtained from these calculations obtained from ab initio simulations often require experimental verification to confirm their results. Finally such calculations require a significant level of expertise and a good understanding of quantum chemistry. Thus the need for simplified models that still successfully predict the thermodynamic state of the system, such as UNIFAC.
การแปล กรุณารอสักครู่..
