Sandia LabNews

Homeland Security scholars work on key projects at Sandia

Homeland Security scholar

Sandia’s Homeland Security Strategic Management Unit got a boost in its research programs this summer from various Department of Homeland Security (DHS) scholars and fellows from throughout the country.

At Sandia/New Mexico the projects ranged from fueling bio-micro sensors with tree sap, to a computer simulation to study the effects of a terrorist event in a major city, to assessing the performance of airport explosive detectors.

Sandia/California Homeland Security scholars focused on DNA-based forensic methods for early detection and characterization of bio-terrorist attacks.

T.J. Allard, Homeland Security director, says he is pleased with the outcome of the work each scholar brought and continues to bring to Sandia.

"These scholars are some of the brightest and smartest in the country," he says. "Through the Homeland Security Scholar program, Sandia was fortunate to bring 10 scholars to both New Mexico and California. They were able to gain real-world experience while working in their research area."

Three Homeland Security scholars were placed at Sandia/New Mexico and seven at Sandia/California.

The New Mexico fellows were Ed Matteo, Akinbayowa "Bayo" Falase, and Jonathan Brown. Sandia/California DHS students were George Chamales, Allyson Fisher, Jason Franklin, Kimberly LeBlanc, Clinton Leysath, Brent Satterfield, and Tristan Weir.

Sugar power

Ed Matteo’s research focuses on running a micro fuel cell with glucose, which could lead to fuel cells powered by a biological source like tree sap. This summer he was able to extend the life of a micro fuel cell to last up to 400 hours powered by glucose, a sugar chemically similar to the sucrose found in tree sap.

"There was no decay in performance," says Ed. "This was the longest we’ve been able to run one of our fuel cells using glucose as the fuel.

Our previous attempts didn’t even last a full 24 hours."

A fuel cell converts a fuel, typically hydrogen or methanol, into electricity. In this project, the fuel for the bio-micro fuel cell is glucose, which would be harvested from a living source like a tree. Micro fuel cells could be used to power portable electronics, sensors, and perhaps even small biomedical devices.

The overall goal is to create a fuel cell that can offer a viable alternative to batteries. A bio fuel cell could theoretically be preferable due to its ability to harvest fuel locally; a battery would need to be recharged.

The challenge has been to run the fuel cell using glucose as a fuel and to prevent decay in the fuel cell power caused by the byproducts of the glucose reaction. These byproducts build up in the fuel cell and literally poison it. Once enough poisons accumulate, the fuel cell can no longer produce useful power.

The team Ed is working with has come up with a novel technique to overcome this poisoning.

"We hold the fuel cell at zero voltage," says Ed, "which is the equivalent of short-circuiting the cell. This, in turn, burns off the products of the glucose reaction and allows the cell to continue to perform without decay."

Ed, an undergraduate chemical engineering student at UNM, is mentored by Chris Apblett (1763), principal investigator of the Bio-Micro Fuel Cell Project. Kent Schubert (1763) is Ed’s manager.

Airport explosive detectors

Bayo Falase’s (6115) project focused on the performance of trace-explosives detectors. He assessed factors that affect the performance of IONSCAN machines, used at airports and high security areas to detect explosives.

"Explosives detection is an integral part of homeland security," Bayo says. "The ability to protect people and information has been a focal point since the events of 9/11."

Bayo conducted field tests with the Albuquerque Police Department bomb squad and did laboratory tests to study the impacts of variability of a thumbprint application of explosives to a surface. This was to help answer questions such as if an adversary were to handle explosives and touch a vehicle, would we get similar results every time? Results showed that there was two to five times more variability than when using a syringe to apply the explosives.

Bayo says the second part of the research is ongoing and is testing factors in the field such as sampling location, explosive type, method used, and high mass versus low mass.

"This research will benefit homeland security because the purpose is to be able to help security forces know what to do to increase the effectiveness of the IONSCAN machine, so that they can detect explosives and prevent terrorist attacks
better," Bayo says.

Bayo is an undergraduate student at the University of New Mexico and is mentored by Clifford Ho (6115).

Parallel programming models

Jonathan Brown conducted research on parallel programming models in the Scalable Computing Systems Department. These models are an abstraction for programmers and algorithm designers used to hide unnecessary details of the hardware while capturing sufficient details to be useful in actual parallel systems.

Parallel programming models, and the languages, libraries, and tools that implement them, should be expressive, intuitive, robust, and predictive, Jonathan says.

"The idea is to maximize both programmer productivity and utilization of hardware resources," he says. "Simulation is useful in understanding a terrorist event in a major city, what its repercussions would be in an ‘urban canyon’ environment, and how to best respond."

To achieve the resolution needed by today’s large-scale simulations in a reasonable time, parallel supercomputing must be used, he says. As these assets are applied to new problems, new codes must be written.

"Using message passing for parallel applications is not the easiest programming environment. It requires software developers to write algorithms to the machine, not to the problem," he says. "A better model would achieve the performance of message passing at lower cost in terms of programmer time, and this would lead to better turn-around on solutions to these

His initial work this summer was in virtual shared-memory models. A virtual shared-memory model is an attempt to bridge shared-memory-style programming to modern multiprocessor systems. Shared memory is known to be a reasonably natural programming paradigm, but shared-memory hardware is expensive and does not scale well.

Building on his work during the summer, Jonathan, a graduate student at the University of Michigan, will continue to work with Zhaofang Wen (9223) at Sandia and two researchers from Notre Dame.