Research Interests of Dr. Babu Joseph.

Abstracts are provided. For more detailed information please contact me.

1. Synthesis and Kinetics of Nanoscale Co/SiO₂ Catalysts for Fischer-Tropsch Processes

F-T Synthesis (FTS) using Co catalysts is a promising technology for producing clean burning liquid fuels with minimum aromatics and optimum blend of olefins/paraffins to achieve high combustion efficiency while minimizing pollutant emissions. The overall objective of this research is to investigate the design of catalysts tailored to optimize process and product design.

FTS activity of Co catalysts primarily depends on the number of active-sites located on the surface of the crystalline metal. The number of cobalt metal sites in the catalysts is a function of the size of cobalt metal particles and extent of cobalt reduction. We will use a novel approach for Co catalyst synthesis based on exploiting colloidal chemistry and molecular self-assembly in tandem to create Co nanoparticles supported on SiO₂. We will prepare monolayer protected clusters (MPCs) wherein the nanoparticles are stabilized with protective layer of organic ligands. A direct consequence of this strategy will be better control of size below the ~10nm range and higher catalytic performance. The catalyst surface will be characterized using modern analytical tools such as TEM/SEM, XPS, EDX, BET and TGA. The reaction mechanisms will be investigated using in-situ, large angle near gracing (LARI) IR spectra to study elementary reaction steps, particularly the adsorption and decomposition of CO on the active sites. Overall kinetics will be studied using a micro reactor. These experimental efforts will be guided by theoretical calculations including molecular dynamics simulations to study structure and morphology of these nanoparticles, density functional theory to study energetics and surface activity and kinetic modeling to validate reaction mechanisms. We will develop a model providing a quantitative relationship between yield, selectivity and physico-chemical structure and properties of the catalyst. The synergistic interplay of the computational and experimental tools provide an opportunity to develop a deeper understanding of the complex reaction mechanisms occurring on surface active sites on the catalyst and hence achieve breakthroughs in integrated catalyst/reactor/process design tailored to meet product requirements.

Using the synergy of basic electronic structure calculations and molecular dynamic simulations combined with fundamental studies of catalyst synthesis, characterization and performance evaluation we hope to achieve a clearer understanding of the relationship between catalyst size, support structure and reaction mechanisms and hence achieve breakthroughs in yield and selectivity. In the synthesis step, novel techniques for surface deposition of metal on support will be developed. The electronic and molecular level studies will broaden or understanding of the reaction mechanisms and role of surface morphology and support interactions on reaction kinetics. In-situ studies of elementary reaction steps would lead to better understanding of the reaction steps involved and hence improved predictive models for use with reactor design for optimizing process performance while minimizing environmental impact.

2. Monitoring Heart Valve Disease Progression using Coupled Fluid Flow/Structural Simulation Models

Valvular heart disease accounts for 5-10% of cardiac surgical cases in the United States (approximately 80,000 surgical valve procedures in 1999). Doppler echocardiography (pulsed wave and continuous) is now recognized as the primary diagnostic tool for detecting valve disease and valve progression. Progression of the disease is insidious and nonlinear. Because of the difficulty of pinpointing the extent of the valve disease, valve replacement surgery is not recommended until after symptoms (angina, congestive heart failure and syncope, etc.) appear. It is highly desirable to develop more sophisticated diagnostic tools to assist the physician in the decision making process. Specifically, it addresses the need for the development of analytical/simulation models to enhance diagnostic power of currently available diagnostic instruments and tools for monitoring heart valve disease

The specific aims are: (i) develop a comprehensive 3-D, combined fluid flow/structural interaction model of the valvular dynamics and its interaction with the hemodynamics of the left ventricle and the aortic artery entry region; (ii) to validate the model through carefully designed in vitro experiments in a fully instrumented pulse-flow duplicator set up at the USF Cardiovascular Fluid Dynamics laboratory using prosthetic valves of varying stiffness indicative of progressive stenosis. The aims during the R33 phase are: (i) validate the model using Doppler data from clinical patients, (ii) study the wall shear stress, Reynolds shear stress, pressure drop variability, valve movement dynamics, flow velocity profiles and extract information regarding the progression of the disease and externally measured Doppler data; and, (iii) to conduct a prospective clinical study of patients in various stages of valve disease in order to verify the main hypothesis that the main valve disease characteristics (valve calcification, valve stiffness, valve movement) can be identified using Doppler derived quantities (velocity, anatomy) coupled with a fluid flow/valve structure simulation model of the valvular hemodynamics.

3. Development of a Spiral Undergraduate Curriculum for Chemical Engineering

The objective of this project is to transform the educational experience of undergraduate students in Chemical Engineering by the development and implementation of a “multi-dimensional spiral curriculum”. The central thesis underlying the proposed initiative is a recognition that an engineering curriculum needs to be more than simply an aggregate sum of individual courses but rather a coherent and continuous program of study that transforms a student into a professional capable of integrating core concepts in a specific discipline for the synthesis, analysis, and design of a product or process of societal value. For students who transfer from two-year community colleges this outcome is particularly difficult via the predominant, traditional sequential model with its emphasis on a linear sequence of courses and gradual spacing over a four year program. Therefore, this implementation focuses on chemical engineering transfer students with the intention of extending it on a wider basis in future.

The proposed project adapts the “spiral curriculum model” (sometimes called incremental learning approach) where a set of interlinked and basic ideas are presented in a repetitive manner exposing the student to higher level of sophistication and greater depth in each of the interlinked concepts. The spiral curriculum focuses on introducing higher cognitive content with progress along the upward spiral path of learning the subject. The iterative revisiting of concepts at increasing levels of complexity promotes curricular integration in a structured, yet simple manner. It also provides an alternative approach to a traditional sequential curriculum taught in most engineering departments where courses delineated by content areas and individual examinations or assessments make vertical and horizontal integration of core concepts difficult and can lead to fragmented learning.

The novel model proposed here uses three interlocking spiral paths to deliver a pedagogically sound, student-centered curriculum that allows integration of core chemical engineering courses, incorporation of traditional and new technological applications, and threading of process and product design concepts over the complete curriculum.

4. Molecular Simulations of Pd Based Hydrogen Sensing Materials

Hydrogen sensor technology is a crucial component for safety and many other practical concerns in the hydrogen economy. To achieve a desired sensor performance, a proper choice of sensing material is critical, because it directly affects the main features of a sensor, such as response time, sensitivity, and selectivity. Palladium is a well known for the ability to adsorb large amount of hydrogen. Most hydrogen sensors use Pd based sensing materials. Since hydrogen sensing is based on surface and interface interactions between the sensing material and hydrogen molecules, nanomaterials, a group of low dimensional systems with large surface to volume ratio, have become the focus of extensive studies in the potential application of hydrogen sensors. Pd nanowires and Pd coated carbon nanotubes have been successfully used in hydrogen sensors and excellent results have been achieved.

The philosophy of the molecular modeling is that the simple knowledge of the molecular structure is all the needed information to predict the behavior and equilibrium properties of any system. Molecular dynamic simulations are applied to comparatively study the thermodynamic, structural and dynamic properties of Pd nanowire and nanocluster. A lower melting temperature of Pd nanowire than the bulk value but higher than that of the cluster is found. x Surface pre-melting at much lower temperature is observed in both Pd systems. The surface melting in nanowires manifests itself as large amplitude vibrations followed by free movement of atoms in the plane perpendicular to the nanowire axis, with axial movement arising at temperatures closer to the transition temperature. The structural analysis indicates that although nanocluster retained the initial fcc structure at low temperatures, the nanowire is stable at a hcp-like structure. Furthermore, melting point depressions in both systems agree better with a liquid-drop model than with Pawlow’s thermodynamic model. The graphite support effect is also studied, where a smaller melting point depression and different structural evolution are noticed. In the second part of this dissertation, ab initio density functional theory is employed to study the Pd and Pd/Ni functionalized single walled carbon nanotubes (SWNTs) and their interactions with hydrogen molecules. The geometries and electronic properties have been determined for both monatomic chains and functionalized SWNTs. Significant electronic property changes of functionalized SWNTs have been observed from band structure and electron density of states analysis upon hydrogen adsorption. The metallized semiconducting SWNT(10,0) by metallic monatomic chain is converted back to semiconductor, implying a dramatic decrease of conductance and therefore a possible significant response as a sensor. Our exploratory studies indicate that a stable, evenly distributed Pd coating can be achieved on a SWNT. Similar results of conductance decrease are expected under exposure to hydrogen. The studies show the applications of computational simulations in the area of hydrogen sensors. It is hoped that this work will lead to a better understanding and design of molecular sensor devices.

5. Modeling and simulation to support design of SAW sensors and sensing layers

Surface acoustic wave sensors detect chemical and biological species by monitoring the shifts in frequency of surface acoustic waves generated on piezoelectric substrates. These devices are conveniently small, relatively inexpensive and quite sensitive. Selectivity, sensitivity and speed of response are the three primary aspects for any type of sensor. Understanding the above three for designing efficient sensors requires modeling across different length and time scales.

Considerable attention has been focused on the development of response models to understand the characteristics of surface acoustic waves generated in SAW devices. Recent advances in sensors and wireless communication systems indicate the need for high performance SAW devices often operating in high frequency (GHz) range. Most of the analytical techniques require simplification of second order effects such as backscattering, charge distribution, diffraction and mechanical loading. However, these effects become significant for SAW devices operating in the high frequency range. Finite element approach has proven to be a viable option to model wave propagation in SAW devices operating in MHz-GHz range.

The use of SAW devices in gas sensors involves various novel sensing layers such as metal nanowires, nanotubes and carbon nanotubes for detection of target analytes. With the incorporation of such sensing layers, the frequency response of the SAW devices becomes dramatically different. A priori knowledge of the frequency response can lead to improved designs and considerable time reduction in fabricating efficient devices. Modification of the delay path to include different arrangements of arrays of nanowires/nanotubes indicates a shift in frequency response of the SAW device. Optimizing the arrangements of the same can result in higher frequency shifts leading to improved sensor response. Similarly, using different arrangements of IDT’s (eg. hexagonally placed IDT’s) to generate waves simultaneously along different delay paths can lead to superposition/amplitude change, the magnitude of which depends on the exact IDT location and the number of finger pairs in each IDT. 3-D and simplified 2-D finite element models involving manipulation of the design parameters can be used to maximize the sensor response.

The changes in the material properties and morphologies of the sensing layer resulting from gas-nanomaterial interaction can also affect the frequency response. Investigations of the gas-metal interactions involve molecular scale modeling with proper potential functions derived from density functional calculations. Knowledge of the gas-metal interactions for varying compositions, sizes and type of the bimetallic sensing layer could throw light on the selectivity and sensitivity of the sensors.