MolSSI/Tapia Center Webinar: Dr. Eliseo Marin-Rimoldi

The Richard E. Tapia Center for Excellence and Equity at Rice University is sponsoring a webinar featuring MolSSI Software Scientist, Dr. Eliseo Marin-Rimoldi, on Thursday, April 5th, at 4:00pm EDT.

The webinar recording is available here:

In this special webinar, Dr. Marin-Rimoldi will discuss how classical molecular simulations can be applied to obtain phase equilibria properties of novel systems with special emphasis on Monte Carlo simulations.

Phase equilibria thermodynamics has a central role in understanding many processes relevant to chemical engineering. Traditional unit operations such as fractional distillation or liquid-liquid extraction are examples of separations where we require phase equilibria thermodynamic properties of mixtures. Novel technologies in the pharmaceutical, petroleum and medical industry also require phase equilibria information. The associated operations to these processes require high quality data that is not always easy to access experimentally or via equations of state.

Computer simulations offer the possibility to study matter with microscopic detail and predict properties solely based on an accurate description of molecular interactions. Among these techniques, quantum mechanical (QM) calculations provide the most fundamental description of matter by numerically solving the Schrödinger wave equation. In principle, any chemical system can be described by this equation. However, obtaining its solution is a formidable task even for relatively simple systems. Consequently, approximations must be made to address problems whose length and time scales are inaccessible by QM methods.

One path for working toward this objective is classical molecular simulations. These techniques approximate atomic interactions using continuous interaction potentials, which can be developed empirically or through quantum theory. Within classical simulations, two main set of methodologies are used: molecular dynamics (MD) and Monte Carlo (MC). The principle of the first method lies on the numerical solution of Newton’s equations of motion to propagate the system, whereas the second stochastically generates states of a system according to a predetermined statistical mechanical probability distribution.


Dr. Eliseo Marin-Rimoldi received his B.S. degree in Chemical Engineering at the Universidad de Guadalajara, Mexico and his Ph.D. in Chemical Engineering at the University of Notre Dame under the supervision of Dr. Edward Maginn. His doctoral research focused on classical Monte Carlo molecular simulation methods for studying complex chemical systems, such as ionic liquids or surfactants. As part of his doctoral work, he participated in the development of Cassandra, an open-source Monte Carlo code capable of simulating the thermodynamic properties of fluids and solids. His main contributions to this code included the development and implementation of novel Monte Carlo techniques to enhance configurational sampling of realistic molecular models.