Click to enlarge

Aquatic Plants as a Cellulosic Ethanol Feedstock

The primary goal of the research plan is to apply the principles of systems engineering to rationally analyze and design processes for conversion of aquatic plants into liquid fuels. The objective of this research is two-fold: first, to elucidate the interplay between the ecological, biological, and chemical systems parameters in a multiplex systems approach. Second, to use this approach to design a life cycle design and simulation environment for the study of biomass conversion into liquid fuel from aquatic plants. To achieve these objectives, Eichhornia crassipes has been selected as a model system to leverage its ideal feedstock characteristics.Nuissance aquatic plants, such as the water hyacinth, are one such feedstock that have rapid growth rates, low cost, and plentiful availability. Additionally, in areas currently infested with water hyacinths, thousands of dollars are spent each year to harvest and dispose of the plant. Developing a process to produce a valuable energy source from what was once considered a blight on an ecosystem will greatly help the economy of surrounding communities. The plentiful availability, low cost, and rapid growth of water hyacinths make them an ideal candidate for a biofuel, particularly in developing countries.The chosen approach to biomass generation from aquatic feedstock involves the implementation of a partial anaerobic composting step in conjunction with the development and application of computer-aided process design and simulation tools.

Click to enlarge

Process Systems Biology Approaches for Directed Production of Biomaterials

The state space framework is an established synthesis tool for the optimal design of process networks. This technique of decomposing a given network into two domains, a distribution network that controls the flow of material and an operator network that controls the transformation of material, has been successfully implemented in many chemical process applications as well documented in the literature. We are currently investigating the application of the state-space framework to biological systems. In one application, we are developing state-space models to analyze the production of monoclonal antibodies (mAbs) in mammalian cell culture (hybridomas / CHO cells). mAbs represent one of the largest growing markets of therapeutic proteins; however, widespread use of mAbs is plagued by low yield and relatively high production costs. We employ state-space as a systematic, data-driven, optimization-based synthesis tool to identify optimal metabolic networks that lead to maximum antibody production rates.
 
Collaborators: Susan Sharfstein, Jim Liao (UCLA)

Click to enlarge

Modeling Immune Response via a Systems Approach

Synapse formation is a fundamental process in biological systems for both information transfer (cell signaling) and the exchange of molecular material between cells. It is a function employed by the adaptive immune system for pathogen detection. Cell-cell interactions between a T-lymphocyte (T-cell) and an antigen-presenting cell (APC) can lead to the formation of a cluster of centrally located, stably bound molecules - commonly referred to as the immunological synapse. This clustering activity can trigger a cascade of biological events resulting in various biological outcomes, and it is believed to play a critical role in immune response. We are developing a systems approach to the modeling and analysis of immunological synapse formation.

Alternate Thermochemical Cycles for Hydrogen Production

The importance and potentially significant impact of hydrogen on the global energy economy has been underscored for several decades. Ease of storage, transportation, and energy capacitance make hydrogen an ideal alternative fuel source. The successful design and implementation of novel thermochemical schema can make hydrogen production the ideal alternative, sustainable, and renewable fuel source. Our efforts focus on the challenges of selecting a suitable thermochemical cycle of reactions, sequencing those reactions, designing a process of technologies to carry out those reactions, and integrating those processes to maximize thermodynamic efficiency and resource utilization. In-house and literature-based software is employed and developed to aid in the optimal selection, sequencing, and integration of reaction steps and other processes.

Collaborators: Prof. B. Wayne Bequette, Dr. Michele Lewis (Argonne National Laboratory)

Multiscale Models for Structure-Property Connectivity in Polymer Nanocomposite Materials

Click to enlarge

Filled biopolymers containing nanoscale (1 - 100 nm) particulates, i.e. bionanocomposites, can offer renewable alternatives to the most widely used petroleum-based polymers that may provide equal or better properties, and may enable new applications. Control over enhanced properties of bionanocomposites requires knowledge of the local (nanoscale) and global (microscale) structure of the nanofillers and the biopolymer matrix. The intellectual merit of the proposed work is that it will build basic scientific knowledge on the effects of nanoparticle size, shape, and agglomerate structure on biopolymer structure and properties. It will also provide new insight into the fundamentals of polymer crystallization and the spatial organization of polymers in the presence of nanoparticles, and will enable the advancement of multiscale models for predicting properties of bionanocomposites. Currently, it is unclear whether and how such structural and property information can be used to generate physically relevant models that describe the morphology of nanocomposite materials. Motivated by this pressing question in nanotechnology, we aim identify to a set of criteria for such multiscale connectivity information to be sufficient to solve the reverse engineering problem.

Collaborators: Yvonne Akpalu – Rensselaer Dept of Chemistry, Diana Borca-Tasciuc – Rensselaer Dept. of Mechanical, Aerospace, and Nuclear Engineering

Multiscale Design of Heterogeneous Phase Processes

Increasing domestic and international demands for vital consumables (e.g. potable drinking water) provide an impetus to develop novel, high-throughput material processing (e.g., purification and disinfection) technologies. For example, photocatalysis has received significant attention as an innovative means to purify and disinfect drinking water. Several studies have shown that titanium dioxide (TiO2), excited (or activated) via exposure to ultraviolet light, generates oxidizing chemical species that can destroy organic compounds (mineralization) and pathogens in aqueous media; however, several limitations render this approach undesirable for continuous treatment of large volumes or scenarios involving highly dynamic capacities and demands. We have developed a novel photocatalytic reactor system that allows for the continuous, high-throughput processing of chemically and biologically contaminated water. The focus of the research is to design (at the nanoscale) and test (at the macroscale) photocatalytic particles that reduce kinetics and mass transfer limitations (thereby increasing overall process efficiency); and develop a methodology to identify scaleable designs with a flexible range of stable process operating conditions.
 
Collaborators: Howard Littman, Joel Plawsky, John Paccione (NYSDOH)

Optimal Design of Heat/Mass Integrated Power Generation Processes

Recently, a new hybrid cycle that employs an ammonia-water binary mixture as working fluid, based on principles employed in absorption refrigeration cycles has been proposed for bottoming cycle applications. Given the research interest of "bottoming" cycles, using ammonia/water mixtures as working fluid, it needs to be ascertained if their improved efficiency can be exceeded by another novel cycle using working fluids with better thermodynamics. Recent developments on this front have shown that such improvements are possible. Therefore, it is necessary to develop tools for the systematic synthesis of optimal and efficient power cycles for applications in clean technology. The development of such a systematic methodology to create optimal power cycle flow sheets will undoubtedly have a major impact on more efficient and environmentally friendly power generation.
 
Collaborators: Ilya Hicks (Texas A&M)