Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Chemical Engineering, 2007. / Includes bibliographical references. / Understanding the structure of materials, and how this structure affects their properties, is an important step towards the understanding that is necessary in order to apply computational methods to the end of designing materials to fit very specific needs. Such needs include specific optical and mechanical properties. In polymers, the ability to easily create orientation through a variety of processes allows the production of materials that, while chemically similar, exhibit a wide variety of optical and mechanical properties. The ability to illuminate the connections between structure and optical or mechanical properties depends on the ability to reliably interpret a wide variety of experimental measurements. I assert that thermodynamic consistency and energy minimization is an integral part of this endeavor; reliable analyses of structure and properties are built upon the foundation of a minimum-free-energy ensemble of configurations that reproduces the experimental results. This project encompasses three goals, which make up this thesis: 1) to show how sets of experimental measurements are integrated into simulations to produce thermodynamically consistent, minimum-free-energy ensembles; 2) to show how these ensembles can characterize the conformations of macromolecules, which are not available from direct simulation; 3) to show how dynamic processes, which create inhomogeneous systems can be incorporated, along with experimental structural measurements, into thermodynamically consistent, minimum-free-energy ensembles. To achieve the first of these goals, we describe the application of the Semi-Grand Canonical Monte Carlo (SGMC) method to analyze and interpret experimental data for non-equilibrium polymer melts and glasses. Experiments that provide information about atomic-level ordering, e.g. birefringence, are amenable to this approach. / (cont.) Closure of the inverse problem of determining the structural detail from limited data is achieved by selecting the lowest-free-energy ensemble of configurations that reproduces the experimental data. The free energy is calculated using the thermodynamic potential of the appropriate semi-grand canonical (SGC) ensemble ... , as defined by the experimental data. To illustrate the method we examine uniaxially oriented polyethylene melts of average chain length up to C400. The simulation results are analyzed for features not explicitly measured by birefringence, such as the density, torsion angle distribution, molecular scale orientation and free energy, to understand more fully the underlying features of these non-equilibrium states. The stress-optical rule for polyethylene is evaluated in this way. The second goal is achieved through multi-scale modeling, which requires the selection and preservation of information crucial to understanding the behavior of a system at appropriate length and time scales. For a description of processed polymers, such a model must successfully link rheological properties with atomic-level structure. We propose a method for the calculation of an important rheological state descriptor, the configuration tensor <QQ>, from atomistic simulations of oligomers. The method requires no adjustable parameters and can describe anisotropic polymer conformations at conditions of significant deformation. We establish the validity of the atomistic-to-macromolecular scaling by comparing the consistency of macromolecular predictions of <QQ> among different polyethylene (PE) oligomer systems. We use this method with the previously reported Semi-Grand Canonical Monte Carlo (SGMC) method to deduce macromolecular and atomic-level structural information interchangeably for systems with flow-induced orientation. Introducing the ability to model arbitrary points in a dynamic process fulfills the third goal elaborated above. / (cont.) Because the characteristic relaxation times of processed polymer chains often span several orders of magnitude, it is commonly the case that partial relaxation of the chains is frozen into the final product. We report results of molecular simulations by the Semi-grand Canonical Monte Carlo (SGMC) method to study the orientation-dependent elasticity of glassy polystyrene as a function of both the system-average degree of orientation and the degree of relaxation of chain ends at a constant average degree of orientation, in accord with the tube model of Doi and Edwards. Our simulations reproduce quantitatively the experimentally observed changes in the tensile modulus E33 as a function of both average orientation and inhomogeneity of the orientation due to partial relaxation. The results show that the partial relaxation of the polymer chains is sufficient to explain the observed variation of mechanical properties for samples that differ in processing history, yet have the same observed birefringence. / by Frederick E. Bernardin, III. / Ph.D.

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Chemical Engineering, 2012. / Cataloged from PDF version of thesis. / Includes bibliographical references (p. 133-149). / The pharmaceutical industry is currently shifting from batch to continuous manufacturing, and for downstream processes, this shift can reduce costs and improve quality provided the new unit operations are chosen properly. Electrospinning, a method of making nanofiber mats from solutions of an active pharmaceutical ingredient (API), polymer and solvent, has shown great promise for producing final solid dosage forms with minimal process steps. In this thesis, we explore the use of electrospinning to produce fiber mats containing either amorphous or crystalline API, aiming to develop the process such that it can be used for a wide variety of final drug products. Key to utilizing electrospinning to make these products is understanding the composition and behavior of the final fiber mats. For fibers containing amorphous API, this means it is essential to understand the level of mixing between API and polymer and the stability of the final product, and for fibers containing crystalline API, the crystal morphology and extent of dispersion within the polymer must be understood. The mixing level of amorphous API and polymer in fibers was analyzed using solid state nuclear magnetic resonance relaxation times. It was found that, for aliskiren/poly(vinyl pyrrolidone) and indomethacin/poly(vinyl pyrrolidone) formulations, the materials are intimately mixed following electrospinning, with no phase separation down to a 2-10 nm domain size. This was not the case for a 4:1 aliskiren:poly(vinyl pyrrolidone) formulation prepared by hot melt extrusion, an alternative method for co-processing API and excipients, as solid state NMR analysis showed phase separation with domains of 20-80 nm or larger. The same electrospun formulations were shown to be stable as solid solutions for 6 mo. when stored at 40°C in a desiccator, indicating that electrospinning is a viable method to produce physically stable formulations containing amorphous API. To produce fibers containing crystalline API, two methods were used. In the first, an API/polymer solution was electrospun using the same method as for producing fibers containing amorphous API. It was found that spinning with a crystalline polymer can result in crystalline API in the fibers, but the crystallinity ultimately depends on more than the polymer and API properties. Due to the complexity of using this method, we developed the second method, involving electrospinning a suspension of API crystals in the polymer/solvent solution. We demonstrated the feasibility of spinning particles of up to 10pm diameter using polystyrene beads and then applied the process to electrospin two different APIs, albendazole and famotidine. The electrospun mats contained crystalline APIs well-dispersed within the fibers and tablets prepared from the mats displayed a higher dissolution rate than fibers prepared from powder blends. / by Blair Kathryn Brettmann. / Ph.D.

Thesis (Sc.D.) Massachusetts Institute of Technology. Dept. of Chemical Engineering, 1950. / Bibliography: leaves A34-A35. / by James Henry Klein. / Sc.D.

Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Chemical Engineering, 1974. / Bibliography: leaves 95-97. / by Kwang J. Won. / M.S.

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Chemical Engineering, 1998. / Includes bibliographical references (p. 227-235). / by Peter H. Nelson. / Ph.D.

Thesis (Ph.D.)--Massachusetts Institute of Technology, Dept. of Chemical Engineering, 1999. / Electronic version available online. / "September 2000." / Includes bibliographical references. / This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections. / The environment has emerged as an important determinant of the performance of the modern chemical industry. Process engineering in the 21st century needs to evolve to include environmental issues as part of the design objectives, rather than as constraints on operations. A frequently cited objection to the use of quantitative indicators of environmental performance in product and process design is that the underlying data are too uncertain for the numbers to have any real meaning. This thesis demonstrates that explicit incorporation of uncertainties allows bounds to be established on the confidence of decisions made on the basis of uncertain indicators. The examples provided show that large uncertainties in indicators used to assess environmental performance do not necessarily imply uncertainty in decision-making. A series of computer-aided decision making tools have been developed to decrease the barriers to the use of environmental valuation functions in routine design activities. These tools include: uncertainty propagation of relative performance measures, a spreadsheet-based fate, transport and exposure model for chemicals, an information content chart for assessing the quality of uncertain indicators, a screening procedure to identify the most important structural and parametric uncertainties in multimedia exposure models, / a process by product input-output life cycle assessment method to generate correlated distributions of unit environmental indicators, an extension of the deterministic equivalent modeling method for the generation of spreadsheet based polynomial chaos expansion metamodels of process flowsheet models, and a database for managing uncertain parameters used in environmental valuation models. Case studies are presented to help the reader in learning the use of the tools. The tools are also applied to an analysis of the U.S. toxics release inventory, in which confidence bounds are developed for the trends in impacts and the contributions of industrial sectors and specific chemical compounds to overall potential impact. Although the tools were developed bearing in mind the need for methods to evaluate the environmental performance of chemical process design alternatives, the ideas can be applied to any decision context in which there are significant uncertainties in the parameters of the objective function. / by José Alejandro Cano Ruiz. / Ph.D.

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Chemical Engineering, February 2007. / Includes bibliographical references. / Poly([beta]-amino ester)s are a class of cationic, degradable polymers that have shown significant promise as gene delivery agents, more effective than the state-of-the-art, commercially available non-viral systems. The main objective of this thesis is to synthesize new poly([beta]-amino ester)s and modify existing ones to further improve their gene delivery properties for clinical applications. This has been accomplished by developing both side- and end-chain chemistries for poly([beta]-amino ester)s. A series of novel poly([beta]-amino ester)s were prepared using a new amine monomer 2-(2-pyridyldithio)-ethylamine. The polymer side chains display fast and selective reactivity towards thiol ligands, as demonstrated using mercaptoethylamine (MEA) and RGDC, a ligand that binds with high affinity to certain integrin receptors on angiogenic endothelial cells. The MEA derivatives in particular, were able to self-assemble with plasmid DNA to form nano-complexes that can partially disassemble in response to intracellular glutathione concentrations. These polymers also displayed low cellular toxicity and were able to mediate transfection at high levels in human hepatocellular carcinoma cells. It is envisioned that the PDA poly([beta]-amino ester)s can serve as cationic, degradable platforms to attach targeting ligands, viral peptides and other molecules to a single chain to improve gene delivery. / (cont.) A two-step end-modification strategy is also presented to optimize the functionality at the polymer end points. Conditions were developed so that many structurally diverse end groups could be explored, without the need for polymer purification. Using a highly efficient poly(3-amino ester), C32, optimization of the terminal amine group improved in vitro gene transfection by 30% and reduced the polymer:DNA ratio 5-fold. Differences of single carbons and functional groups at the polymer ends were shown to affect many polymer-DNA properties, including the binding affinity, complex size and surface charge, levels of endocytosis, cytotoxicity and transfection. Intraperitoneal gene delivery in mice using several end-modified C32 polymers proved an order-of-magnitude more effective than unmodified C32, as measured in whole body scans and harvested organs. The end- and side-chain modification strategies presented here have led to the discovery of improved poly([beta]-amino ester)s for gene delivery and may aid in their future development into clinically useful delivery systems. / by Gregory Thomas Zugates. / Ph.D.

Thesis (Ph.D.)--Massachusetts Institute of Technology, Dept. of Chemical Engineering, 2000. / Includes bibliographical references. / In this work, a framework and a set of modeling tools capable of describing systems with key processes occurring on widely separated length and time scales has been developed. The major focus of this work is linking atomistic and continuum descriptions of gas phase transport. This problem is of considerable practical interest, as most etching and CVD processes are run at low pressures ~ 1 torr or less. Under these conditions, the continuum diffusion models used to describe flow and transport in a typical reactor will fail below scales of a few hundred microns, and thus are not useful in describing transport in and around microscale topography. This is a serious limitation, as such topography is present in most microelectronic devices. Two methods for linking discrete particle (or feature scale) and continuum models of precursor transport are presented. The discrete and continuum models are coupled by boundary conditions at their mutual interface (just above any reactive surface with microscale detail) The first approach employs an effective reactivity function e,, which is computed through a hybrid probabilistic-deterministic MC method e. can be interpreted as a representation of the average fate of molecules entering the feature scale domain from the macroscopic model. An example of tungsten CVD over a substrate with surface topography typical of modern microelectronic devices is presented. A second, deterministic technique was also developed as an improvement on the Monte Carlo approach. The deterministic method uses the matrix of transmission probabilities, or shape kernel, to summarize all microscale events in a fashion consistent with a continuum macroscopic model. The deterministic linking algorithm is over 1,000 times faster than the previously presented MC method. The speed advantage enables simulation of detailed chemistry. Plasma etching presents a very similar multiscale problem and a strategy for linked plasma etching simulations is presented. Finally, a study of ionized physical vapor deposition of aluminum is presented as an example of atomistic-continuum linking. Molecular dynamics simulations are used to represent atomistic events. The Molecular Dynamics results are summarized in a manner that allows the combination of atomistic information with a continuum (level -set) model for evolution of the deposited metal film. / by Seth Thomas Rodgers. / Ph.D.

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Chemical Engineering, 2011. / Cataloged from PDF version of thesis. / Includes bibliographical references. / T lymphocytes are key orchestrators of the adaptive immune response in higher organisms. This thesis seeks to apply different techniques from engineering and the physical sciences to understand how T cells balance the risks of autoimmunity and infection. (1) What features of proteins do T cells search for that correlate with pathogenicity, distinguishing self from foreign? Two contrasting theories have emerged that attempt to describe T cell ligand potency, one based on the half-life (tv12) of the interaction between T cell receptors (TCR) and peptide-MHC complexes (pMHC), the second on the equilibrium affinity (KD). We study an extensive set of TCR-pMHC interactions in CD4+ T cells which have differential KD and kinetics of binding. The data indicate that ligands with short t1/2 can be highly stimulatory if they have fast on-rates. Simple models suggest these fast-kinetic ligands are stimulatory because the pMHC bind and rebind the same TCR several times. Accounting for rebinding, ligand potency is KD-based when ligands have fast on-rates and t1/2-based when they have slow on-rates, unifying previous theories. (2) How do T cells make optimal responses with the imperfect information they receive through their receptors? Recent experiments suggest that T cells sometimes make stochastic decisions. Biological systems without sensors and genetic diversity, such as some bacteria, make stochastic decisions to diversify responses in uncertain environments, thereby optimizing performance (e.g. growth). T cells, however, can draw on considerable environmental and genetic diversity to diversify their responses. Using T cell biology as a guide, we identify a new role for noise in such systems: it helps systems achieve complex goals with simple signaling machinery. With decision-theoretic techniques, we suggest necessary conditions for noise to be useful in this way. (3) How can biological systems, like T cells, maintain desired responses in the presence of molecular noise, suppressing it or exploiting it as needed? We develop a semianalytical technique to determine how small changes in the rate constants of different reactions or in the concentrations of different species affect the rate at which biological systems escape stable cellular states. A single deterministic simulation yields the sensitivities with respect to all reactions and species in the system. This helps to predict those species or interactions that are most critical for regulating molecular noise, suggesting those most promising as drug targets or most vulnerable to mutation. These projects and others discussed in this thesis recruit techniques from random walks, statistical inference, and large deviation theory to understand problems ranging in scale from individual molecular interactions to the population of T cells acting in concert. / by Christopher C. Govern. / Ph.D.

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Chemical Engineering, 1995. / Includes bibliographical references (p. 229-244). / by Kai-Chee Loh. / Ph.D.