Multiscale modeling thermodynamics

Not mentioned in this review but certainly important to multiscale modeling related to solid mechanics are topics, such as self-assemblies, thin films, thermal barrier coatings, patterning, phase transformations, nanomaterials design, and semiconductors, all of which have an economic motivation for study. Studies related to these types of materials and structures require multiphysics formulations to understand the appropriate thermodynamics, kinetics, and kinematics. 

Michael E. Paulaitis is Professor of Chemical and Biomolecular Engineering and Ohio Eminent Scholar at Ohio State University. He is also Director of the Institute of Multiscale Modeling of Biological Interactions at Johns Hopkins University. His research focuses on molecular thermodynamics of hydration, protein solution thermodynamics, and molecular simulations of biological macromolecules. 

The example put forth here demonstrates the connection between kinetic theory and macroscopic thermodynamics. Indeed, it can be argued, I think convincingly, that the twin pillars of statistical mechanics and thermodynamics themselves serve as the paradigmatic example of multiscale modeling. The partition function and its associated derivatives serve as the bridge between microscopic models, on the one hand, and the derived thermodynamic consequences of that model, on the other. 

Multiscale Modeling and Coarse Graining of Polymer Dynamics Simulations Guided by Statistical Beyond-Equilibrium Thermodynamics... 

Many polymer blends or block polymer melts separate microscopically into complex meso-scale structures. It is a challenge to predict the multiscale structure of polymer systems including phase diagram, morphology evolution of micro-phase separation, density and composition profiles, and molecular conformations in the interfacial region between different phases. The formation mechanism of micro-phase structures for polymer blends or block copolymers essentially roots in a delicate balance between entropic and enthalpic contributions to the Helmholtz energy. Therefore, it is the key to establish a molecular thermodynamic model of the Helmholtz energy considered for those complex meso-scale structures. In this paper, we introduced a theoretical method based on a lattice model developed in this laboratory to study the multi-scale structure of polymer systems. First, a molecular thermodynamic model for uniform polymer system is presented. This model can... 

The main purpose of quantum-chemical modeling in materials simulation is to obtain necessary input data for the subsequent calculations of thermodynamic and kinetic parameters required for the next steps of multiscale techniques. Quantum-chemical calculations can also be used to predict various physical and chemical properties of the material in hand (the growing film in our case). Under quantum-chemical, we mean here both molecular and solid-state techniques, which are now implemented in numerous computer codes (such as Gaussian [25], GAMESS [26], or NWCHEM [27] for molecular applications and VASP [28], CASTEP [29], or ABINIT [30] for solid-state applications). 

Miroslav Grmela, Multiscale Equilibrium and Nonequilibrium Thermodynamics in Chemical Engineering Prasanna K.Jog, Valeriy V. Ginzburg, Rakesh Srivastava, Jeffrey D. Weinhold, Shekhar Jain, and Walter G. Chapman, Application of Mesoscale Field-Based Models to Predict Stability of Particle Dispersions in Polymer Melts... 

Franco has designed this model to coimect within a nonequilibrium thermodynamics framework atomistic phenomena (elementary kinetic processes) with macroscopic electrochemical observables (e.g., I-V curves, EIS, Uceii(t)) with reasonable computational efforts. The model is a transient, multiscale, and multiphysics single electrochemical cell model accounting for the coupling between physical mechanistic descriptions of the phenomena taking place in the different component and material scales. For the case of PEMFCs, the modeling approach can account for detailed descriptions of the electrochemical and transport mechanisms in the electrodes, the membrane, the gas diffusion layers and the channels H2, O2, N2, and vapor... 

Solvation behavior can be effectively predicted using electronic structure methods coupled with solvation methods, for example, the combination of continuum solvation methods such as COSMO with DFT as implemented in DMoF of Accelrys Materials Studio. An attractive alternative is statistical-mechanical 3D-RISM-KH molecular theory of solvation that predicts, from the first principles, the solvation structure and thermodynamics of solvated macromolecules with full molecular detail at the level of molecular simulation. In particular, this is illustrated here on the adsorption of bitumen fragments on zeolite nanoparticles. Furthermore, we have shown that the self-consistent field combinations of the KS-DFT and the OFE method with 3D-RISM-KH can predict electronic and solvation structure, and properties of various macromolecules in solution in a wide range of solvent composition and thermodynamic conditions. This includes the electronic structure, geometry optimization, reaction modeling with transition states, spectroscopic properties, adsorption strength and arrangement, supramolecular self-assembly,"and other effects for macromolecular systems in pure solvents, solvent mixtures, electrolyte solutions, " ionic liquids, and simple and complex solvents confined in nanoporous materials. Currently, the self-consistent field KS-DFT/3D-RISM-KH multiscale method is available only in the ADF software. 

Figure 18.1 Regimes of the problem space for multiscale stochastic simulations of chemical reaction kinetics. The r-axis represents the number of molecules of reacting species, x, and the ) -axis measures the frequency of reaction events, A. The threshold variables demarcate the partitions of modeling formalisms. In area I, the number of molecules is so small and the reaction events are so infrequent that a discrete-stochastic simulation algorithm, like the SSA, is needed. In contrast, in area V, which extends to infinity, the thermodynamic limit assumption becomes vahd and a continuous-deterministic modehng formalism becomes valid. Other areas admit different modehng formalisms, such as ones based on chemical Langevin equations, or probabilistic steady-state assumptions.

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