Quantum Perturbation Theory in Fluid Mixtures

Sep 1, 2013·
Dariush Azimi
Dariush Azimi
Equal contribution
,
S. M. Motevalli
Equal contribution
· 1 min read
Image credit: Unsplash
Abstract
Experimental assessment of macroscopic thermo-dynamical parameters under extreme conditions is almost impossible and very expensive. Therefore, theoretical EOS for further experiments or evaluation is inevitable. In spite of other efficient methods of calculation such as integral equations and computer simulations, we have used perturbation theory because of its extensive qualities. Moreover, other methods are more time consuming than perturbation theories. When one wants to deal with realistic intermolecular interactions, the problem of deriving the thermodynamic and structural properties of the system becomes rather formida‐ ble. Thus, perturbation theories of liquid have been devised since the mid-20th century. Thermodynamic perturbation theory offers a molecular, as opposed to continuum approach to the prediction of fluid thermodynamic properties. Although, perturbation predictions are not expected to rival those of advanced integral-equations or large scale computer simulations methods, they are far more numerically efficient than the latter approaches and often produced comparably accurate results.
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*Advances in Quantum Mechanics, Intech *(1)
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Dariush Azimi
Authors
Dariush Azimi (he/him)
Physicist & Computational Specialist

Darius Azimi is a highly analytical Physicist with a robust foundation in Theoretical, subatomic, and Plasma Physics. With a career spanning multiple M.Sc. degrees from top Swedish and Iranian institution, I specialize in bridging the gap between complex theoretical frameworks and practical computational applications. My expertise lies in developing high-fidelity simulations—using PIC, Monte Carlo, and Molecular Dynamics—to investigate the linear and non-linear properties of dynamic physical systems. ​I am a published author in journals such as the International Journal of Modern Physics B, where I have contributed to the understanding of statistical physics, binary hard sphere mixtures, and quantum perturbation theory. By combining rigorous mathematical modeling with advanced software development in C++, Fortran, and Python, I deliver high-quality analytical solutions for complex equations using iterative solvers like GMRES and BICGSTAB. Whether driving academic research or consulting on technical subatomic systems, I am dedicated to pushing the boundaries of applied physics through algorithmic innovation and data-driven insights. Outside of my research, I have enjoyed contributing to the Swedish educational system as a substitute teacher, which has further refined my ability to communicate complex ideas in Swedish.

Authors
S. M. Motevalli