Steinar Hauan - US grants

ABSTRACT

PI: David S. Sholl, Lorenz T. Biegler and Steinar Hauan
Institution: Carnegie Mellon University
Proposal Number: 0094407

This is an equipment grant to provide funds to purchase a 32 node Beowulf cluster to support research in advanced computing to be used by three research groups at Carnegie Mellon University. Beowulf clusters represent an advantageous architecture for advanced computing: they are inexpensive to construct, flexible to configure, and provide a powerful computing environment for a broad variety of scientific computing tasks. The three research groups that will share the cluster will be conducting research on molecular dynamics and computational chemistry, modeling and visualization to support process synthesis and large-scale discrete and continuous process optimization. The cluster will thus serve computations that require high peak performance on time scales of minutes and hours, along with sustained computational performance on time scales of days. These complementary profiles mean that by sharing the cluster, its capabilities will be used more fully than they would be by any group individually. The cluster can also easily be operated in a way that distributes resources between different usage modes without significant computational overhead. The cluster will initially increase the PIs' computational capabilities by about a factor of three and will be expandable over succeeding years and will increase their computing power by over an order of magnitude within the next five years, without rendering existing nodes obsolete.

Specifically, the research of the three groups consists of the development of new algorithms for:
Calculation in computational chemistry, particularly in molecular dynamics and Monte Carlo simulations to determine macroscopic material properties from details of atomic-scale structure;
Accurate process modeling for process design and synthesis that includes phase equilibrium, representation and evaluation of process alternatives and visualization of design insights; and
Optimization of large-scale steady state and dynamic processes that involve both discrete and continuous decisions along with advanced decomposition strategies.

The advent of large scale integrated (LSI) circuits in the 70s set the foundations for today's information technologies. Similarly, recent advances in the monolithic integration of biochemical fluid-based processing technologies is likely to lead to the development of tomorrow's advances in biotechnology and medicine. As with integrated circuits, such very large scale integrated biofluidic chips (VLSIBC) will need software tools to acquire design specifications, investigate the applicability of alternative design architectures, and then automatically design a target chip. Furthermore, tools for quantitatively predicting and optimizing the chip's performance will be needed.

This cross-disciplinary project involving investigators from four departments at Carnegie Mellon and one at the University of Illinois is developing algorithms, languages, models and methodologies for the design of biofluidic chips. The envisoned automated design and verification capabilities will be able to handle the tremendous growth in biofluidic design complexity arising from microfluidic integration and will shorten the current design-fabricate-test loop to reduce the lead time and make biofluidic processors commercially viable.

Research:

The goal of this Information Technology (IT) Research - Small project is to develop a framework for distributed modeling, simulation and agent based optimization. Such a system will permit the integration of classical process systems engineering tools, like process modeling, numerical integration, optimization and predictive evaluation with the distributed data base capabilities of ERP systems. The focus will be on solution strategies that take advantage of distributed computing and information exchange across a network of connected computational units. The approach achieves speed, quality flexibility, and robustness that scales favorably with problem size. Two specific problems will be addressed:
1. How to develop methods for dynamic simulation of distributed process networks, and
2. How to use agent based methods for solving large scale, stochastic control problems that have dynamics distributed in time and space.

A key issue in the research will be how to interface the modeling and agent-based optimization frameworks in such a way that the performance of the process network is optimized.

Broader Impact:

Enterprise Resource Planning (ERP) systems and other IT tools allow companies to access, analyze and disseminate vast amounts of distributed information almost instantaneously over the web. This project could help interface business IT with classical tools for process modeling and optimization which in turn could be of great commercial benefit to US industry.

ABSTRACT

Proposal No. CTS-0320548
Principal Investigator: J. Schneider, Carnegie Mellon University

This grant is to develop a fluorescence-based instrument for the visualization of flow and adsorption in microfluidic systems. The instrument consists of an inverted epifluorescence microscope, a solid-state laser, a high-speed CCD camera, a low-noise DC power supply, and some smaller equipment. Measurement of adsorption will be accomplished by total internal reflection fluorescence (TIRF). Microfluidic devices will be constructed using standard soft lithography methods, allowing for control of microchannel geometry and surface chemistry. Fluid flow will be induced either by electroosmosis or a syringe pump, depending on the application.

Three research projects, representative of those to be supported by this equipment, are as follows: The first is an assessment of the contribution of lateral diffusion to the kinetics of DNA hybridization to surface-bound probes as means to improve the performance of biosensors. The second is the development of a microscale chromatography system that utilizes DNA-binding surfactants to isolate target DNA from complex mixtures. The third is the development and validation of numerical algorithms for improved computer-aided design of lab-on-a-chip systems.

The impact of the instrumentation will be on many fronts. This is perhaps the first microfluidic visualization instrument that includes on-line TIRF, supplying surface adsorption information critical to the above research. In addition, the many groups on campus involved with microfluidics and MEMS would have this instrument as a shared resource. We will also perform a series of microfluidics experiments (available as a web-based resource) to serve as examples and problem sets for transport courses. We will also develop hands on projects for high school students participating in the Summer Academy for Minority Students at Carnegie Mellon University. This would serve as an introduction to an exciting field and familiarize students with state-of-the-art lab equipment.