Adsorption processes computer simulation

Wang, N.-H. Versatile model for simulation of reaction and nonequilibrium dynamics in multicomponent fixed-bed adsorption processes, Comput. Chem. Eng., 1991, 15(11), 749-768. 

Abstract In this chapter, adsorption process is simulated by using computational mass transfer (CMT) models as presented in Chap. 3. As the adsorption process is unsteady and accompanied with heat effect, the time parameter and the energy equation as presented in Chap. 2 are involved in the model equations. The simulated concentration profile of the column at different times enables to show the progress of adsorption along the column as an indication of the process dynamics. The simulated breakthrough curve and regeneration curve for adsorption and desorption by the two CMT models, i.e., the - Sc- model and the Reynolds mass flux model, are well checked with the experimental data. Some issues that may cause discrepancies are discussed. 

Chronopotentiometry, galvanostatic transients, 1411 as analytical technique, 1411 activation overpotential, 1411 Clavilier, and single crystals, 1095 Cluster formation energy of, 1304 and Frumkin isotherm, 1197 Cobalt-nickel plating, 1375 Cold combustion, definition, 1041 Cole-Cole plot, impedance, 1129, 1135 Colloidal particles, 880, 882 and differential capacity, 880 Complex impedance, 1135 Computer simulation, 1160 of adsorption processes, 965 and overall reaction, 1259 and rate determining step, 1260... 

The adsorption and diffusion properties of benzene are of immense interest in zeolite research aromatics play important roles in a number of zeolite-catalyzed processes. Theoretical simulations of benzene diffusion first began to be published in the late 1980s. The first studies evaluated and minimized the potential energy of a molecule such as benzene within the channels, a method less computationally demanding than the MD simulations that followed. Most recent studies have used the TST formalism. 

Because of their structural and conformational complexity, polypeptides, proteins, and their feedstock contaminants thus represent an especially challenging case for the development of reliable adsorption models. Iterative simulation approaches, involving the application of several different isothermal representations8,367 369 enable an efficient strategy to be developed in terms of computational time and cost. Utilizing these iterative strategies, more reliable values of the relevant adsorption parameters, such as q, Kd, or the mass transfer coefficients (the latter often lumped into an apparent axial dispersion coefficient), can be derived, enabling the model simulations to more closely approximate the physical reality of the actual adsorption process. 

Cyclic Steady State (CSS) is a unique feature of periodic adsorption processes. It is defuied as a condition whereby the state at the end of each cycle is identical to that at its beginning. Within an engineering context, the theoretical determination of CSS for a given set of periodic conditirms is a key step towards the optimisation of adsorption processes. CSS determination computer simulation, however, is still one of the most challenging procedures for a process engineer to implement. Once achieved, the engineer is more readily able to maximise profit and minimise costs of the adsorption process. 

Classical methods, like DS and HK, show shortcomings in the determination of MSD due to the assumptions involved in their formulation of the adsorption process Dubinin equation does not show linearity in the Dubinin plot for single slit pores and Horvath-Kawazoe equation assumes that at a given pressure a pore is either completely filled or completely empty, which is contrary to the behavior observed in computer simulations Resulting MSD are shifted respect to those obtained by Monte Carlo simulations, by amounts that vary with the actual distribution, and too small micropores are predicted... 

The versatility of the approach, in combination with the ever increasing available computational power, obeys good prospects for future studies. It will be seen in later chapters that it is necessary to introduce a more complex picture of the adsorption processes. Presently, we simulate only what is mobile adsorption on a homogeneous... 

Chemical Process Equipment Selection and Design Stanley M. Walas Chemical Process Structures and Information Flows Richard S.H. Mah Computational Methods for Process Simulation W. Fred Ramirez Constitutive Equations for Polymer Melts and Solutions Ronald G, Larson Fundamental Process Control David M. Prett and Carlos E, Garcia Gas-Liquid-Solid Fluidization Engineering Liang-Shih Fan Gas Separation by Adsorption Processes Ralph T. Yang... 

Pugnaloni, L.A., Ettelaie, R., and Dickinson, E. Computer simulation of interfacial structure and large-deformation rheology during competitive adsorption of proteins and surfactants. Food Colloids Interactions, Microstructure and Processing, E. Dickinson, ed.. Royal Society of Chemistry, Cambridge, U.K., 2005a, p. 131. 

On the basis of the model of a heterogeneous membrane, it is possible to create a simulation scheme based on dynamic Monte Carlo computer simulations of the adsorption and desorption process on heterogeneous surfaces to extract the involved rate constants as a function of the calcium ion concentration. A simple simulation based on a modified, partly reversible, random sequential adsorption (RSA) algorithm provides very good accordance between experiment and measurement. Figure 8 schematically depicts the assumed model. 

In short, the structural order observed for the hydration shell of the Li+ ion at various distances from the mercury surface results from the strong tendency of this ion to form an octahedral arrangement with its six nearest neighbor water molecules in bulk solution. This structure adjusts to the densities and inhomogeneities determined by the metal surface. This example demonstrates how mechanistic information about the process of ion adsorption can be extracted from computer simulations. 

In this problem we will simulate a batch adsorption process that takes place with two adsorbate components. The simulation will allow us to do computational experiments with the aim of learning how the adsorption and desorption parameters affect the behavior of this process. Building the simulation will provide new experience in developing the model equations, utilizing more complex constitutive relationships, finding numerical solutions to these equations, and displaying the results graphically. 

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