Thesis: Ph. D., Massachusetts Institute of Technology, Department of Chemical Engineering, February 2015. / Cataloged from PDF version of thesis. "October 2014." / Includes bibliographical references (pages 183-189). / The development of organometallic catalysts with high activity and selectivity has transformed the way both bulk and fine chemicals are produced. When such catalysts are applied in fine chemicals production, the presence of toxic heavy metals in these catalysts (Pd, Pt, Ru, Rh, etc.) can pose significant separation challenges. Regulatory bodies (such as the FDA and EMA) require that many popular catalytic heavy metals stay below 10 ppm in pharmaceutical drugs. Organic solvent nanofiltration (OSN) membranes are an upcoming technology with the potential to solve this problem by allowing heavy metal-containing catalysts to be molecularly separated from smaller product molecules. This size-based molecular separation makes the technique general, but challenges still exist in further broadening the chemical compatibility of nanofiltration membranes. Recent efforts have succeeded in creating membranes which are compatible with strong bases, and these membranes are applied in this thesis. The work in this thesis developed continuous catalyst recycle systems for a metathesis catalyst, a hydrogenation catalyst, and a palladium Buchwald-Hartwig amination catalyst. During the initial stages of designing such small scale catalyst recycle systems, significant technology gaps were identified. These included microfluidic OSN modules, microfluidic holding tanks with level sensing, milli-scale OSN modules with integrated high-pressure holding tanks and liquid level sensing, and a milli-scale holding tank with two-phase level sensing. These small scale process blocks were designed, built, and implemented in this work. Our metathesis catalyst recycle system included a reactor, holding tank, and nanofiltration module with a total internal volume of less than 3 ml. The system was used to automatically recycle the catalyst, obtaining a catalyst turnover number (TON) of 935, and reducing the ruthenium contamination in the product stream by a factor of 100. For our hydrogenation catalyst recycle system, we built a high-pressure small-scale catalyst recycle flow process (less than 50 ml). The system improved catalyst TONs from 500 to 4750, and reduced catalyst contamination in the product stream by a factor of 200. Finally, our palladium catalyst recycle system was able to perform a liquid-liquid separation before a nanofiltration step, and improved the TON of our reaction from 125 to 550 while decreasing the palladium contamination in the product stream by almost an order of magnitude. We also discovered significant disadvantages in operating these continuous systems, including reduced throughput due to membrane fouling, reduced catalyst activity due to product inhibition, reduced substrate concentrations in the recycle loop (leading to reduced reaction rates), enantioselectivity decline, and increased process complexity. This thesis contributes to understanding the advantages/disadvantages of OSN-containing catalyst recycle systems, provides new tools for future work in many areas involving small scale process design, and generates recommendations regarding the next generation of smallscale OSN pilot processes. / by Everett John O'Neal. / Ph. D.

Thesis: Ph. D., Massachusetts Institute of Technology, Department of Chemical Engineering, 2017. / Cataloged from PDF version of thesis. / Includes bibliographical references (pages 147-170). / Lithium-ion batteries are increasingly important, both in portable electronic devices and as grid stabilization for intermittent renewable sources. The varied applications involve varying requirements for safety, lifetime, and energy/power density. The broad requirement space leads to a large design space, requiring either extensive and costly experimentation or effective models. To be predictive enough to facilitate design, models must be based on underlying physics. However, battery models commonly make assumptions known to be false, such as describing phase separating materials with Fickian diffusion. In this thesis, we build on existing battery models by modifying key parts to better capture fundamental phenomena including transport and reactions in phase separating materials. First, we introduce a model of lithium transport and surface reactions within particles of graphite, which has phase separation and is the most common anode material in lithium-ion batteries. We demonstrate key features of the model, including a sensitivity to its electrochemical reaction kinetics as well as its ability to capture both single particle and porous electrode experimental data. Second, we connect a model of electrochemical kinetics that is well-established in the chemistry community to nonequilibrium thermodynamics and apply it to materials with phase separating electrodes. We demonstrate that, although it shares some characteristics with a commonly used phenomenological model, it makes distinct predictions which agree with certain experimental results. Finally, we unify these single-particle models within a volume-averaged model to describe battery behavior at the scale of full porous electrodes. The developed model and simulation software have already been applied by other researchers to help explain behavior of batteries with phase separating materials. / by Raymond Barrett Smith. / Ph. D.

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Chemical Engineering, 2003. / Includes bibliographical references (leaves 191-202). / The ultrafiltration of plasma in the mammalian glomerulus is the first step in the processing of blood by the kidney. Proper functioning of this process is critical to the kidney's ability to effectively eliminate waste and retain desirable substances. The glomerular barrier has long been regarded as both a size and charge selective screen for plasma solutes. The origin of this selectivity is found in the unique three-layered structure of the glomerular capillary wall (GCW), consisting of a fenestrated endothelium, the interdigitating foot processes of the glomerular epithelium, and the shared glomerular basement membrane (GBM). The selectivity properties of the GCW have commonly been probed by measuring the sieving coefficients of a variety of tracers, both proteins and exogenous polymers, across the intact glomerular barrier and across isolated components of the GCW. It was found previously that the sieving coefficients of the tracers Ficoll and Ficoll sulfate across isolated GBM were greatly elevated when BSA was present at physiological levels (Bolton et al. 1998). It was suggested that most of this increase was the result of steric interactions between BSA and the tracers which increased tracer partitioning from the bulk into the GBM. Such an effect, if present, would have important implications for the interpretation of macromolecular sieving studies, both in vivo and in vitro. The goals of this thesis research were to model the effect of an abundant protein on the partitioning of a dissimilar tracer molecule, to incorporate that effect into models for glomerular sieving, and to test the partitioning model by measuring the effect of protein concentration on the partitioning of protein and Ficoll in agarose gels. The theoretical effects of solute size on partition coefficients in straight pores or randomly oriented fiber matrices have been investigated previously for very dilute solutions, where solute-solute interactions are negligible, and also for more concentrated solutions consisting of spherical solutes of uniform size. For concentrated solutions it has been found that steric and other repulsive interactions among solutes increase the partition coefficient above the dilute limit. To extend the results for porous or fibrous media to include concentrated mixtures of solutes with different sizes or shapes, we used an excluded volume approach. In this formulation, which describes steric interactions only, partition coefficients were computed by summing all volumes excluded to a solute molecule by virtue of its finite size, the finite size of other solutes, and the presence of fixed obstacles (pore walls or fibers). For a mixture of two spherical solutes, the addition of any second solute at finite concentration increased the partition coefficient of the first solute. That increase was sensitive to the size of the second solute; for a given volume fraction of the second solute, the smaller its radius, the larger the effect. When the total volume fraction of solutes was fixed, an increase in the amount of a second, smaller solute increased the partition coefficient of the first solute, whereas an increase in the amount of a second, larger solute had the opposite effect. Results were obtained also for oblate or prolate spheroidal solutes and for fibrous media with multiple fiber radii. For constant total fiber volume fraction, an increase in the amount of a second, smaller fiber decreased the partition coefficient of a spherical solute, whereas an increase in the amount of a second, larger fiber had the opposite effect. Overall, the theory suggests that the introduction of heterogeneity, whether as mixtures of solute sizes or mixtures of fiber sizes, may cause partition coefficients to differ markedly from those of uniform systems. Using the excluded volume partitioning model, the theory for the sieving of macromolecular tracers was extended to account for the presence of a second, abundant solute. Using that theory, we returned to the experimental data of Bolton et al. (1998) and attempted to model the effect of protein concentration on Ficoll sieving. The osmotic reduction in filtrate velocity caused by an abundant, mostly retained solute will also tend to elevate the tracer sieving coefficient. The osmotic effect alone explained only about one third of the observed increase in the sieving coefficients of Ficoll and Ficoll sulfate, whereas the effect of BSA on tracer partitioning was sufficient to account for the remainder. At physiological concentrations, predictions for tracer sieving in the presence of BSA were found to be insensitive to the assumed shape of the protein (sphere or prolate spheroid). The effect of plasma proteins on tracer partitioning is expected to influence sieving not only in isolated GBM, but also in intact glomerular capillaries in vivo. To test the predicted effects of solute concentration on the equilibrium partitioning of single macromolecules and macromolecule mixtures, measurements of the equilibrium partition coefficients of BSA and four narrow fractions of Ficoll were made in agarose. Solutions of each test macromolecule were equilibrated with a known volume of gel, final liquid concentrations measured, and partition coefficients calculated by applying a material balance. The partition coefficient of each molecule was measured under dilute conditions and under conditions where BSA was present at concentrated levels. All measurements were made for two different gel solid volume fractions (4 and 6%). As expected, the partition coefficients decreased with increasing gel solid volume fraction and with increasing molecular size. Increasing BSA concentration caused an increase in the partitioning of BSA itself and that of all four sizes of Ficoll. This effect was most significant for the largest molecules. A subset of the measurements repeated at a higher ionic strength demonstrated that electrostatic interactions were unimportant. The experimental results were compared with predictions generated from the excluded volume partitioning theory. Agarose was represented as a randomly oriented array of cylindrical fibers, BSA was modeled as a prolate spheroid, and Ficoll was treated as a sphere. Comparisons of the theoretical predictions with the experimental data produced generally good agreement, indicating that steric interactions among solute molecules and between solute molecules and gel fibers could explain the partitioning behavior. / by Matthew Jordan Lazzara. / Ph.D.

Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Chemical Engineering, 1924. / Includes bibliographical references. / by L. P. Elliott and Emil H. M. Lehnhardt. / M.S.

Thesis (Ph.D.)--Massachusetts Institute of Technology, Dept. of Chemical Engineering, 2000. / Includes bibliographical references (p. 306-325). / Efficient parallel computation of complex viscoelastic flows is essential to bring modem computer power to bear on fluid calculations where complicated constitutive descriptions are required. We have developed an efficient, parallel time integration scheme for calculating viscoelastic flows. The method is a synthesis of an operator splitting and time integration method that decouples the calculation of the polymer portion of the stress by solution of a hyperbolic constitutive equation from the temporal updating of the velocity and pressure fields by solution of a generalized Stokes problem. Finite element discretizations using the DEVSS-G 1 method are used; here a direct interpolation of the components of the velocity gradient is introduced. The key to the parallelization is the incorporation of iterative matrix solution for each portion of the split calculation. The linear system that results from the generalized Stokes problem is asymmetric, indefinite, and block singular. At each timestep, this system is solved using an algorithm which combines a parallel preconditioner with a Krylov subspace method. The parallel preconditioner, called the Block Complement and Additive Levels Method (BCALM) preconditioner, is based on treating pressure unknowns separately from the variables velocities and gradients. A pressure preconditioner is constructed from a factor of the Schur complement of the pressures using a Jacobi iteration. The viscous operator is treated using the additive Schwarz method. The number of Krylov iterations required per implicit step with increasing numbers of processors is stabilized using a two-level additive Schwarz method. The coarse grid is generated using addition as a restriction operator and insertion for extension. The resulting iterative method is demonstrated to have high parallel efficiency, subject to effective domain decomposition. Robustness and good performance result from using geometric partitioning of the unknowns by the nested bisection routines supplied in CHAC02. The software is implemented using MPI and the PETSc toolkit, so as to be readily portable to a variety of parallel computers. This solver is developed in the context of the natural convection problem, where in the limit of high Grashof number, the linear system that arises during solution for steady state using Newton's method is stiff, assymmetric and indefinite. With this model problem, the preconditioner's robustness is tested and its efficiency is measured. The solver's generalizability for viscous flow problems is also discussed, as the only assumption about problem physics is that the continuity equation exists. For a given velocity field, the discretized equations from a typical differential constitutive model, e.g. the Oldroyd-B model, yields an asymmetric, nonsingular system of linear equations when nonlinearities are updated explicitly. Krylov iterations preconditioned with inexact solves in a two-level additive Schwarz framework are used to solve this system at each time step. Added efficiency is introduced by using a discontinuous Galerkin spatial discretization, which allows element-by-element condensation of the linear systems and higher parallel efficiency. The effectiveness of the algorithm is demonstrated by the calculation of transient, two dimensional flow of an Oldroyd-B fluid past an isolated cylinder confined symmetrically between parallel plates and by calculation of the stability of the steady-state motion to small-amplitude, three-dimensional disturbances The resulting method is far superior to the use of serial, frontal methods. / by Anthony Edward Caola. / Ph.D.

Thesis (Sc.D.) Massachusetts Institute of Technology. Dept. of Chemical Engineering, 1947. / Vita. / Includes bibliographies. / by Edward Wilson Merrill. / Sc.D.

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Chemical Engineering, 1989. / Includes bibliographical references (leaves 276-288). / by Kevin G. Joback. / Ph.D.

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Chemical Engineering, 1997. / Includes bibliographical references (p. 143-152). / by Philip R. Kuhl. / Ph.D.

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Chemical Engineering, 2013. / Cataloged from PDF version of thesis. / Includes bibliographical references. / Graphene is a one-atom thick planar monolayer of sp2 -bonded carbon atoms organized in a hexagonal crystal lattice. A single walled carbon nanotube (SWCNT) can be thought of as a graphene sheet rolled up into a seamless hollow cylinder with extremely high length-to-diameter ratio. Their large surface area, and exceptional optical, mechanical and electronic properties make these low-dimensional carbon materials ideal candidates for (opto-)electronic and sensing applications. In this thesis I studied the charge transfer processes that occur at their interface, and developed applications based on the discovered properties. When light is incident on a semiconducting SWCNT, it can excite an electron from the valence band to the conduction band, thereby creating a Coulombically bound electron-hole pair, also known as an exciton. Excitons can decay via radiative or non-radiative recombination or by colliding with other excitons. They can diffuse along the length of a SWCNT or hop from larger band gap SWCNTs to smaller band gap SWCNTs, a process known as exciton energy transfer (EET). We studied their behavior as a function of temperature in SWCNT fibers and showed that at room temperature the rate constant for EET is more than two orders of magnitude larger than that of each of the different recombination processes. This led us to construct a core-shell SWCNT fiber, which consists of a core of smaller band gap SWCNTs, surrounded by a shell of larger band gap SWCNTs, essentially forming what is known as a type I heterojunction. In agreement with a model that describes exciton behavior in the SWCNT fibers, we found that upon illumination all the energy (in the form of excitons) was quickly transferred from the shell to the core, faster than the excitons would otherwise recombine. The SWCNT fiber proved to be an efficient optical and energetic concentrator. We showed that SWCNTs and poly(3-hexylthiophene) (P3HT) form a type II heterojunction, which implies that excitons generated in the P3HT can easily dissociate into free charge carriers at the interface with the SWCNTs. Despite this, the efficiency of a P3HT/SWCNT bulk heterojunction (BHJ) photovoltaic is subpar. We developed a P3HT/SWCNT planar heterojunction (PHJ) and achieved efficiencies that were 30 times higher, which showed that the formation of bundled aggregates in BHJs was the cause: metallic SWCNTs can quench the excitons in an entire bundle. Another interesting feature of our SWCNT/P3HT PHJ is that a maximum efficiency was reached when -60 nm of P3HT was used, which is surprising since in a planar photovoltaic a maximum is expected for ~8.5 nm of P3HT, the value of the exciton diffusion length. A Kinetic Monte Carlo simulation revealed that bulk exciton dissociation was responsible for the lower efficiencies observed in devices with low P3HT thickness. Next we created and studied a junction between SWCNTs and a monolayer of graphene, an ideal one-dimensional/two-dimensional carbon interface. We used Raman spectroscopy to probe the degree of charge transfer at the interface and based on a shift in the G peak position of the graphene Raman signal at the junction deduced that a typical metallic (semiconducting) SWCNT dopes the graphene with 1.12 x 1013 cm-2 (0.325 x 101 cm-2) electrons upon contact, in agreement with the fact that the Fermi level of the SWCNTs is more shallow than that of the graphene. A molecular dynamics simulation ruled out that the observed Raman peak shifts are due to strain, although it did show that SWCNTs are being compressed radially by the graphene sheet, resulting in a widening of their Raman peaks. We studied charge transfer between diazonium molecules and graphene, to better inform transistor and sensor design. The reaction rate depends on the degree of overlap between the filled energy levels in graphene and the unoccupied ones in the diazonium molecule. We showed that with increasing degree of functionalization the charge transfer characteristics of a graphene field effect transistor (FET) alter in the following ways: the minimum conductivity decreases, the Dirac point upshifts, the conductivity plateau at high carrier density decreases and the electronhole conduction asymmetry increases. We developed a theoretical model of charge transport in graphene FETs that takes into account the effect of both short-range and long-range scatterers. Fitting it to the charge-transport data reveals quantitative information about the number of impurities in the substrate supporting the graphene, about the number of defects created as a result of the reaction, and about the degree of electron-hole conduction asymmetry. Graphene functionalization also affects the graphene Raman signal. After reaction, the D to G intensity ratio to increases, which is a sign of covalent modification of the graphene lattice. Additionally, the G peak and 2D peak positions increase while the 2D/G intensity ratio decreases, which are signs of hole-doping. Based on a Raman analysis, we were also able to show that the end group of the diazonium salt can affect both the degree of chemisorption (covalent modification) as well as the degree of physisorption (doping). Finally, we studied the effects of charge transfer between graphene and biological cells on the graphene Raman signal and designed a fundamentally new type of biosensor. Graphene can be thought of as a continuous array of information units (sensor units). The Raman signal collected in each unit can report on its local environment. In contrast to graphene FET biosensors, the graphene Raman biosensor offers subcellular spatial resolution. The graphene Raman signal was shown to display a strong dependence on pH. Metabolically active cells acidify their local environment; therefore, pH is a proxy for cellular metabolism. We placed both human embryonic kidney (HEK) cells that were genetically engineered to produce mouse antibodies and control HEK cells that were not genetically modified onto the graphene. Based on the change in the graphene Raman signal we deduced the former have a metabolic rate that is four times higher than that of the control cells. Increased cellular adhesion allows the cells to interact more closely with the graphene monolayer and intensifies the observed Raman effects. / by Geraldine L.C. Paulus. / Ph.D.

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Chemical Engineering, 2007. / Includes bibliographical references (p. 257-276). / Genome sequencing and the subsequent development of high-throughput probing of cellular states have dramatically increased our ability to understand cellular compensation to perturbation. As such, integrating system-wide measurements (e.g. gene expression) with networks of protein-protein interactions and transcription factor binding has been proven as an effective means to help elucidate insights into cellular behavior. This very cellular behavior, however, is most closely linked to the metabolites and metabolic interactions occurring within the cell. Despite this fact, metabolic measurements are often given a secondary role in efforts to unravel the multi-tiered regulatory response of cells to perturbations. To begin to address this gap, we first report on the development the application of a novel derivatization method for metabolome analysis of yeast, coupled to data-mining software that achieve comparable throughput, effort, and cost compared with DNA arrays. Our sample workup method enables simultaneous metabolite measurements with coverage throughout central carbon metabolism and amino acid biosynthesis, using a standard Gas Chromatography Mass Spectrometry (GC-MS) platform optimized for this purpose. / (cont.) As an implementation proof-of-concept, we assayed metabolite levels across two different yeast strains and two different environmental conditions with the aim of metabolic pathway reconstruction. In doing so, we demonstrate that differential metabolite level data distinguish among sample types, such as those found in typical metabolic fingerprinting or footprinting techniques. More importantly, we demonstrate that this differential metabolite level data provides further insight into specific metabolic pathways. However, the data analysis of this GC-MS metabolomic profiling data relied upon reference libraries of metabolite mass spectra to structurally identify and track metabolites. In general, techniques to enumerate and track unidentified metabolites are non-systematic and require manual curation, thus requiring a novel method for computational mining of the spectral data for automated, exhaustive analysis. Accordingly, we developed a method and software implementation that can systematically detect components that are conserved across samples without the need for a reference library or manual curation. We validate this approach by correctly identifying the components in a known mixture and the discriminating components in a spiked mixture. / (cont.) Combining these robust capabilities to characterize metabolic state along with methods of measuring transcriptional states and protein interactions, we constructed a global network-based model of yeast amino acid biosynthesis containing 154 molecules, 37 rates, and 250 interactions to link genetic regulation and metabolic state. To interrogate this model, we created a battery of five genetic perturbations to the transcriptional regulators of amino acid biosynthesis and measured transcript levels, biomass 13C-labeling, and metabolite levels in batch culture. With this data, we designed a more detailed experiment to quantify 5764 mRNAs, 54 metabolites, and 83 experimental 13C-based reaction fluxes in continuous cultures of yeast under stress in the absence or presence of global regulator Gcn4p. While mRNA expression alone was insufficient to directly predict metabolic responses, this correlation improved through incorporating a network-based model of amino-acid biosynthesis (from r = 0.07 to 0.80 for mRNA-flux agreement). The model provides evidence of general biological principles: rewiring of metabolic flux by transcriptional regulation and metabolite-enzyme interaction density as a key biosynthetic control determinant. / by Joel Forrest Moxley. / Ph.D.