Predictions of the mass transfer in structured packings using computational fluid dynamics

Chemical separations are widely performed in industry, with vapor-liquid contactors often accomplishing these separations and providing high-purity products. Structured packings are commonly employed in vapor-liquid contactors and exhibit low pressure drops, high throughputs, and excellent chemical separation performance. Despite the widespread use of these packings, the transport phenomena occurring within them are incompletely understood, inhibiting improvement efforts. Computational fluid dynamics (CFD) is a promising approach to predict the transport phenomena occurring inside the packings and to guide packing innovation. In this work, CFD predicted the gas-phase mass transfer performance of structured packings, and several key observations resulted. After a model for turbulence-aided mass transfer was identified with pipe flow simulations, the gas-phase mass transfer performance of a traditional structured packing was predicted. The mass transfer coefficients from CFD showed a five percent deviation compared to experimental data, validating the simulations. A geometry investigation determined the impact of three fundamental structured packing parameters on the packing performance. Improved mass transfer performance often occurred at the cost of hydrodynamic performance. Turbulence had a large impact on the gas-phase predictions. The liquid-phase mass transfer in structured packings was also simulated. A novel simulation methodology enabled the structured packing performance predictions. To validate the hydrodynamic predictions from the CFD simulations, the predicted liquid holdup was compared to experimental liquid holdup data and showed a deviation of six percent. Comparisons of the predicted liquid flow angle and friction factor to analytical expressions further validated the hydrodynamic CFD predictions. The liquid mass transfer coefficient predictions were validated with experimental data, having a deviation of eight percent, as well as with semi-empirical models. A structured packing geometry study was conducted for the liquid-phase performance, and liquid upheaval near packing crimps significantly contributed to the chemical separation. A novel interfacial mass transfer model was developed for multiphase CFD simulations. This model can handle concentration jumps of multiple orders of magnitude across the gas-liquid interface. An analytical solution to a two-dimensional system validated the CFD predictions, producing an error of less than one percent. The model was adapted for turbulent conditions and was demonstrated on a structured packing system.Chemical Engineerin

Molecular Dynamics Simulations using Advanced Sampling and Polarizable Force Fields

Molecular dynamics (MD) simulations were carried out for aqueous dipeptides, water over self-assembled monolayer (SAM) surfaces, and the nicotinic acetylcholine receptor (nAChR) ion channel. The main goal is to use advanced methods to increase the accuracy of molecular dynamics simulations while seeking solutions to problems relevant to chemistry, biophysics and materials science. In addition, activation energies of several cyclodimerization reactions were studied quantum mechanically. The simulations of the aqueous dipeptides and SAM surfaces involve modeling and detailed analysis of interfacial water, which is of interest to a range of fields from biology to materials science. For example, water has a central role in biology and medicine since biomolecules cannot function without water. Both sets of simulations were performed using both polarizable and nonpolarizable force fields. These systems were used as a test ground to assess the effects of explicit incorporation of polarizability and also to determine whether the models can adequately reproduce the experimental data, in particular, the aggregation data of aqueous dipeptides and contact angles of water over SAMs of different chemical character. Since the systems are well-characterized and relatively simple, they provide excellent models to test polarizable force fields to increase the accuracy of molecular dynamics simulations. Polarizable water was depolarized around dipeptide solutes and also at the interface with different SAM surfaces, reflecting its ability to adapt to heterogeneous electrostatic environments. Although the water shows more realistic structure and dynamics in the polarizable simulations, the peptide aggregation behavior agrees less well with the experiment. In this case, neither model successfully reproduces the experimental degree of aggregation. In the case of SAM surfaces, both sets of simulations produce fairly similar results. More studies are suggested to further test and improve the polarizable force fields. The third system studied is the modeling of wild-type and mutant nAChR ion channel proteins. Adaptive biasing force method was used to achieve improved sampling, and subsequently increase the efficiency and accuracy of MD simulations. The nAChR channels are involved in a number of cognitive and brain functions including learning and memory. Dysfunction in these receptors are associated in a variety of neuronal diseases including epilepsy, schizophrenia and Alzheimer\u27s Disease. The present study models the wild-type and two physiologically-relevant mutant structures to assess the effects of mutations on ion translocation energetics and the geometry of the channel. Open channel (conducting, active) structures were obtained from the available closed channel structure. One of the mutants was found to increase the energetic barrier for ion translocation, while the other one decreased the barrier. The ion channel structures were analyzed in detail to understand the structural changes that took place during the channel opening. The channel opening was found to be mediated by large-scale helix motions rather than small-scale side chain motions. Aside from the MD simulations, the final project involves quantum mechanical simulations, which are often needed in parametrization of molecular dynamics force fields. Density functional theory (DFT) calculations were employed to calculate the activation energies of three cyclodimerization reactions of trifluorovinyl ether monomers. The results agree with and further explain the experimentally observed reactivity in these types of reactions

Characterizing the switching transitions of an adsorbed peptide by mapping the potential energy surface

Peptide adsorption occurs across technology, medicine, and nature. The functions of adsorbed peptides are related to their conformation. In the past, molecular simulation methods such as molecular dynamics have been used to determine key conformations of adsorbed peptides. However, the transitions between these conformations often occur too slowly to be modeled reliably by such methods. This means such transitions are less well understood. In the study reported here, discrete path sampling is used for the first time to study the potential energy surface of an adsorbed peptide (polyalanine) and the transition pathways between various stable adsorbed conformations that have been identified in prior work by two of the authors [Mijajlovic, M.; Biggs, M. J. J. Phys. Chem. C 2007, 111, 15839−15847]. Mechanisms for the switching of adsorbed polyalanine between the stable conformations are elucidated along with the energetics of these switches

Multiphysics Modelling of Energy Storage Devices Using Pore Scale Approaches

The advancement in high-resolution X-ray tomography image acquisition techniques has enabled imaged-based modelling of pore-scale transport processes to better understand structural performance relationship in porous media. The porous components in electrochemical energy storage devices such as lithium-ion batteries, fuel cell and redox flow batteries are subject to intense research to maximize performance and hence reduce the cost of energy storage systems. The image-based pore-scale modelling approaches such as direct numerical simulation (DNS) are, however, very computationally expensive and it gets infeasible to simulate a representative element volume of porous structure on a standard workstation or laptop machine. Pore network modelling (PNM) approach has been previously used to simulate large size porous domains of fuel cell and redox flow batteries at substantially lower computational cost, however, its application in lithium-ion batteries has not been attempted due to the multiphysics and transient nature of transport mechanism involved during charging and discharging process. Lithium-ion batteries are considered as the top candidate for electrochemical energy storage, so modelling their structure-performance relationship at less computational cost will enable development of efficient numerical pore network modelling framework. Therefore, this thesis aims towards developing pore network modelling framework for lithium-ion batteries to study the impact of microstructure on multiphysics transport processes occurring inside battery electrodes. The development of lithium-ion battery pore network model requires enhancements in the current implementation of pore network modelling algorithms. For example, current pore network extraction algorithms only extract a single phase from a tomography image (usually the pores). On the other hand, lithium-ion battery electrodes contain three phases, namely active material (e.g. NMC), carbon binder, and electrolyte filled void phase. To resolve this issue, multiphase pore network extraction algorithms were developed that connect any two phases via interconnections. This allowed investigating inter- and intra-phase transport processes between phases which are common in lithium-ion battery. The extraction algorithms were tested on random sphere packings and three-phase lithium-ion battery cathode and found to agree well with experimental data and DNS model. Computational performance of PNM model was also compared with other modelling approaches and found to give appreciable performance gain on large size porous domains, while yielding similar or equivalent results.Although modelling of transport process using the PNM approach is computationally efficient, extracting pore networks from tomography images is a computationally expensive task. Also, image resolution plays a vital role to determine the relative accuracy of extracted geometrical properties and hence simulation accuracy. To remove these bottlenecks, an efficient, parallelized network extraction technique was developed that enabled pore network extraction from massive size images. A geometric domain decomposition technique was adopted to reduce the computational cost of extraction. The network extraction was observed 7 times faster and consumed 50% less RAM when used in parallel and serial mode respectively. Finally, a case study was performed to reduce the effect of resolution during pore network extraction. This enabled more reliable extracted pore networks for pore network modelling studies. Finally, pore network modelling of lithium-ion batteries cathodes was performed to study galvanostatic discharge behaviour of half-cells. A massive reduction in computational cost was observed when compared with DNS approach. The structural features of two electrodes were investigated to understand the performance-structural relationship. Also, particle-to-particle and pore-to-pore analysis was performed to analyze the state of lithiation, solid-phase potential distribution and lithium-ion concentration distribution, electrolyte phase potential distribution in solid and electrolyte phase respectively. The study enabled modelling of large size lithium-ion electrodes to analyze the impact of internal microstructure on the overall performance of the cell. The presented work in this thesis is focused on developing, validating, and applying a pore network modelling framework for lithium-ion battery discharge. It has enabled the study of structural performance relationship of battery electrodes on a particle to particle basis without estimating effective transport properties using empirical or experimental data. The excellent computational performance of PNMs has allowed multiphysics modelling on standard workstation or laptop with minimal computational resources. Although developed for lithium-ion battery cathodes the developed framework can be used for any anode structure or study thermal performance-structure relationship as well

Computational Studies of Molecular Mechanisms Mediating Protein Adsorption on Material Surfaces

Protein adsorption at material surfaces is a fundamental concept in many scientific applications ranging from the biocompatibility of implant materials in bioengineering to cleaning environmental material surfaces from toxic proteins in the area of biodefense. Understanding the molecular-level details of protein-surface interactions is crucial for controlling protein adsorption. While a range of experimental techniques has been developed to study protein adsorption, these techniques cannot produce the fundamental molecular-level information of protein adsorption. All-atom empirical force field molecular dynamics (MD) simulations hold great promise as a valuable tool for elucidating and predicting the mechanisms governing protein adsorption. However, current MD simulation methods have not been validated for this application. This research addresses three limitations of the standard MD when applied to the simulations of the protein-surface interactions: (1) representation of the force field parameters governing the interactions of protein amino acids with the material surface; (2) cluster analysis of ensembles of adsorbed protein states obtained in protein-adsorption simulations, in which in addition to the conformation the orientation of the sampled states is also important; and (3) simulation time to ensure a significant level of conformational sampling to cover the entire rough energy landscape of such a large molecular system as protein adsorption. This study, thus, attempted to further advance protein-adsorption simulation methods using high-density polyethylene as a model materials surface

Fundamentals of chemical reaction engineering

This book is an introduction to the quantitative treatment of chemical reaction engineering. The level of the presentation is what we consider appropriate for a one-semester course. The text provides a balanced approach to the understanding of: (1) both homogeneous and heterogeneous reacting systems and (2) both chemical reaction engineering and chemical reactor engineering. We have emulated the teachings of Prof. Michel Boudart in numerous sections of this text. For example, much of Chapters 1 and 4 are modeled after his superb text that is now out of print (Kinetics a/Chemical Processes), but they have been expanded and updated. Each chapter contains numerous worked problems and vignettes. We use the vignettes to provide the reader with discussions on real, commercial processes and/or uses of the molecules and/or analyses described in the text. Thus, the vignettes relate the material presented to what happens in the world around us so that the reader gains appreciation for how chemical reaction engineering and its principles affect everyday life. Many problems in this text require numerical solution. The reader should seek appropriate software for proper solution of these problems. Since this software is abundant and continually improving, the reader should be able to easily find the necessary software. This exercise is useful for students since they will need to do this upon leaving their academic institutions. Completion of the entire text will give the reader a good introduction to the fundamentals of chemical reaction engineering and provide a basis for extensions into other nontraditional uses of these analyses, for example, behavior of biological systems, processing of electronic materials, and prediction of global atmospheric phenomena. We believe that the emphasis on chemical reaction engineering as opposed to chemical reactor engineering is the appropriate context for training future chemical engineers who will confront issues in diverse sectors of employment. We gratefully acknowledge Prof. Michel Boudart who encouraged us to write this text and who has provided intellectual guidance to both of us. MED also thanks Martha Hepworth for her efforts in converting a pile of handwritten notes into a final product. In addition, Stacey Siporin, John Murphy, and Kyle Bishop are acknowledged for their excellent assistance in compiling the solutions manual. The cover artwork was provided courtesy of Professor Ahmed Zewail's group at Caltech, and we gratefully thank them for their contribution. We acknowledge with appreciation the people who reviewed our project, especially A. Brad Anton of Cornell University, who provided extensive comments on content and accuracy. Finally, we thank and apologize to the many students who suffered through the early drafts as course notes. We dedicate this book to our wives and to our parents for their constant support

Mixed-Cell Methods for Diffusion Problems in Multiphase Systems.

We simulate diffusion in multimaterial systems with a cell-centered Eulerian mesh in two dimensions. A system with immiscible fluids contains sharp interfaces. An Eulerian mesh is fixed in space and does not move with the material. Therefore, cells with an interface contain multiple fluids; these are known as mixed cells. The treatment of mixed cells can vary in computational cost and accuracy. In some cases, the primary source of inaccuracy can be attributed to approximations made in modeling the mixed cells. This thesis focuses on the treatment of mixed cells based on the diffusion approximation of the transport equation. We introduce five subgrid, mixed-cell models. Two models have a single temperature for each cell, while the other three allow a separate temperature for each phase. The single-temperature models are implemented using the Support-Operators Method, which is derived herein. The first single-temperature model utilizes an effective tensor diffusivity that distinguishes diffusion tangent and normal to the interface. The second single-temperature model specifies a unique diffusivity in each corner of a mixed cell, which is effectively a mesh refinement of the mixed cell. The three multi-temperature models have increasingly accurate levels of approximation of the flux: (i) flux is calculated between cell-centers for each phase, (ii) flux is calculated between the centroid of each phase, and (iii) flux normal to an interface is calculated between centroids of each phase. The physical interpretations of these models are: (i) each phase occupies the entire cell, (ii) oblique flux is continuous, (iii) only normal flux is continuous. The standard approximation, using the harmonic mean of the diffusivities present in a mixed cell as an effective diffusivity, is also tested for comparison. We also derive two time-dependent analytical solutions for diffusion in a two-phase system, in both one and two dimensions. With the standard model as a reference point, the accuracy of the new models is quantified, and the convergence rates of the error are determined between pairs of spatial resolutions for the two problems with analytical solutions. Simulations of multiphysics and multimaterial phenomenon may benefit from increased mixed-cell fidelity achieved in this dissertation.PHDApplied PhysicsUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/107150/1/leftynm_1.pd

Continuum modeling of the coupled transport of mass, energy, and momentum in paperboard.

This thesis investigates the coupling between moisture, heat, and deformation in paperboard. The presented investigations are primarily conducted via macroscale continuum modeling but experimental characterisations are also made. The continuum modeling is presented in a mixture theory framework where the paperboard is considered as a porous media composed of three immiscible phases; a network of cellulose fibers, liquid water bound in or to the fibers, and moist air. The motion of each phase is described and the interactions of mass, energy, and momentum between the three phases are also considered. Emphasis in the current work is to derive a thermodynamically consistent model and all constitutive relations are derived with consideration to the Clausius-Duhem inequality. The derived continuum model is used in numerical investigations to study the response of slow, long time processes such as storing of paperboard rolls as well as rapid processes where the board is exposed to significant temperature changes and mechanical loads during a short period of time.The thesis begins with an introduction where some of the characteristic properties of paperboard are described and the basic concepts of the hybrid mixture theory framework are explained. The main part of the thesis is then composed of four papers, A, B, C, and D. In Paper A, a model describing the transport of mass and heat in paperboard is developed. The model considers slow transport processes and assumes the fiber network to be incompressible. Special focus of Paper A is to develop a model that is able to describe the static and dynamic sorption properties of paperboard. The derived model is used to predict the evolution of the moisture and heat distributions in paperboard rolls in climates with a varying relative humidity. In Papers B and C, the model derived in Paper A is further developed to handle rapid processes where significant temperature changes are expected. Furthermore, in Papers B and C, the assumption of an incompressible fiber network is abandoned and an orthotropic stress-strain response with an advanced yield surface is incorporated in a large strain setting. The model is then used to predict the response of paperboard during a transversal sealing process. In Paper D, experimental investigations are made on the in-plane permeability and on the static and dynamic sorption properties of paperboard. The results from these investigations are then used together with the model developed in Paper B and C to analyse the physics behind a blister test