Flat-Histogram Monte Carlo as an Efficient Tool To Evaluate Adsorption Processes Involving Rigid and Deformable Molecules

Monte Carlo simulations are the foundational technique for predicting thermodynamic properties of open systems where the process of interest involves the exchange of particles. Thus, they have been used extensively to computationally evaluate the adsorption properties of nanoporous materials and are critical for the in silico identification of promising materials for a variety of gas storage and chemical separation applications. In this work we demonstrate that a well-known biasing technique, known as "flat-histogram" sampling, can be combined with temperature extrapolation of the free energy landscape to efficiently provide significantly more useful thermodynamic information than standard open ensemble MC simulations. Namely, we can accurately compute the isosteric heat of adsorption and number of particles adsorbed for various adsorbates over an extremely wide range of temperatures and pressures from a set of simulations at just one temperature. We extend this derivation of the temperature extrapolation to adsorbates with intramolecular degrees of freedom when Rosenbluth sampling is employed. Consequently, the working capacity and isosteric heat can be computed for any given combined temperature/pressure swing adsorption process for a large range of operating conditions with both rigid and deformable adsorbates. Continuous thermodynamic properties can be computed with this technique at very moderate computational cost, thereby providing a strong case for its application to the in silico identification of promising nanoporous adsorbents

Probability Distribution Function of the Order Parameter: Mixing Fields and Universality

We briefly review the use of the order parameter probability distribution function as a useful tool to obtain the critical properties of statistical mechanical models using computer Monte Carlo simulations. Some simple discrete spin magnetic systems on a lattice, such as Ising, general spin-$S$ Blume-Capel and Baxter-Wu, $Q$-state Potts, among other models, will be considered as examples. The importance and the necessity of the role of mixing fields in asymmetric magnetic models will be discussed in more detail, as well as the corresponding distributions of the extensive conjugate variables.Comment: 14 pages, 13 figures, accepted for publication (Computer Physics Communications

A Computational Investigation of the Thermodynamics and Structure in Colloid and Polymer Mixtures

In this dissertation I use computational tools to study the structure and thermodynamics of colloid-polymer mixtures. I show that fluid-fluid phase separation in mixtures of colloids and linear polymers cannot be universally reduced using polymer-based scaling principles since these assume the binodals exist in a single scaling regime, whereas accurate simulations clearly demonstrate otherwise. I show that rethinking these solutions in terms of multiple length scales is necessary to properly explain the thermodynamic stability and structure of these fluid phases, and produce phase diagrams in nearly quantitative agreement with experimental results. I then extend this work to encompass more geometrically complex "star" polymers revealing how the phase behavior for many of these binary mixtures may be mapped onto that of mixtures containing only linear polymers. I further consider the depletion-driven crystallization of athermal colloidal hard spheres induced by polymers. I demonstrate how the partitioning of a finite amount of polymer into the colloidal crystal phase implies that the polymer's architecture can be tailored to interact with the internal void structure of different crystal polymorphs uniquely, thus providing a direct route to thermodynamically stabilizing one arbitrarily chosen structure over another, e.g., the hexagonal close-packed crystal over the face-centered cubic. I then begin to generalize this result by considering the consequences of thermal interactions and complex polymer architectures. These principles lay the groundwork for intelligently engineering co-solute additives in crystallizing colloidal suspensions that can be used to thermodynamically isolate single crystal morphologies. Finally, I examine the competition between self-assembly and phase separation in polymer-grafted nanoparticle systems by comparing and contrasting the validity of two different models for grafted nanoparticles: "nanoparticle amphiphiles" versus "patchy particles." The latter suggests these systems have some utility in forming novel "equilibrium gel" phases, however, I find that considering grafted nanoparticles as amphiphiles provides a qualitatively accurate description of their thermodynamics revealing either first-order phase separation into two isotropic phases or continuous self-assembly. I find no signs of empty liquid formation, suggesting that these nanoparticles do not provide a route to such phases

mahynski/FHMCSimulation: Bugfix for Z-matrix loop

Fixed accelerated Z-matrix loop so all entries are properly recorded

mahynski/DEVProject v1.0.0

Simple project manager script to setup standardized file tree for new revision-controlled projects

Coarse-graining and phase behavior of model star polymer-colloid mixtures in solvents of varying quality

We study the effective interactions and phase behavior of star polymer-colloid mixtures through theory and Monte Carlo simulations. We extend previous theoretical approaches for calculating the effective star-colloid pair potential to take into account attractive contributions, which become significant at worsening solvent conditions. In order to assess the validity of our simulation and theory, we compute the effective interactions via virtual move parallel tempering Monte Carlo simulations using a microscopic bead-spring model for the star polymer and achieve excellent agreement. Finally, we perform grand canonical Monte Carlo simulations of the coarse-grained systems to study the effect of solvent quality on the phase behavior