Faculty Spotlights

Jim Schmiedeler

Department of Aerospace and Mechanical Engineering

Associate Professor

According to the American Heart Association, stroke is the No. 3 killer in the United States. It is also a leading cause of long-term disabilities, particularly motor deficiencies in arm movement. An interdisciplinary team led by James Schmiedeler, associate professor of aerospace and mechanical engineering; Aaron Striegel, associate professor of computer science and engineering,and Charles Crowell, associate professor of psychology, is working to extend the capabilities of "game" devices such as the Nintendo® WiiTM and multi-touch devices like the Surface to enhance rehabilitationactivities after a stroke or traumatic injury. They have partneredwith Johan Kuitse, the director of Rehabilitation Services, and his staff at Memorial Hospital in South Bend.

Although the Surface has received attention for rehabilitation (by virtue of its games) in the past, the team is exploring novel applications. They are also working to identify how the devices can be used to better diagnose motor and cognitive impairments, to quantifiably measure the recovery of
motor and cognitive function, and to speed and enhance that recovery in stroke rehabilitation patients.

Undergraduates have also been able to take advantage of a one-of-a-kind programming course that Striegel has been teaching using the Surface, learning how to program the device and developing their own applications.

Click here for more information about Jim Schmiedeler’s research.

Edward J. Maginn

Department of Chemical and Biomolecular Engineering

Professor

A cheap and plentiful resource, coal fuels more than 40 percent of the world’s electricity. It is a major player in the energy industry. But coal-fired power plants emit climate-altering greenhouse gases into the environment daily. To minimize the amount of carbon dioxide (CO₂) released from coal-fired power plants, Professor Edward J. Maginn and a team of Notre Dame faculty are developing ionic liquids that can effectively and economically separate CO₂ from flue gases, so it can be stored underground instead of being released into the atmosphere.

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Current separation technology is an energy-intensive process, taking more than 30 percent of the energy produced to capture the CO₂. Working with ionic liquids (ILs), salts that are liquid at room temperature, the Notre Dame team can tailor specific properties of an IL so that it grabs the CO₂ and chemically binds to it. Then, as the separation continues, the CO₂ flows with the liquid to a high-temperature chamber, where it is released and diverted to a high-pressure pipeline for storage underground, while the benign gases — steam and nitrogen — are released into the atmosphere. This process is more effective and less expensive.

To date the team has created several ILs and filed invention disclosures on each of them. They are installing a test unit in the Notre Dame Energy Center in 2011 to run bench-scale tests on the ILs they have developed. Over the next three years, they expect to run large-scale tests in a pilot plant.

“The complex nature of the simulations, and the computational power required to run them, have made the difference in this fundamental research,” says Maginn, “allowing us to make some tremendous strides that would not have been possible even a few years ago.”

Jeremy Fein

Department of Civil Engineering and Geological Sciences

Professor

As a professor in the Department of Civil Engineering and Geological Sciences and director of the Center for Environmental Science and Technology, Jeremy Fein has long studied the interactions between bacteria, minerals, and heavy metal and radionuclide contaminants in the environment. He is currently conducting experiments focusing on remediation strategies for uranium-contaminated groundwater.

For more information on Fein’s research and other faculty highlights, click here.

The contamination legacies of nuclear weapons and fuel production represent serious problems at a number of sites across the country and the industrialized world. A possible remediation strategy for these sites involves injection of phosphate into contaminated aquifers, immobilizing the uranium by precipitating it as a uranyl phosphate solid. Fein and his students are investigating the effect that bacteria exert on the extent and nature of uranyl phosphate precipitation, finding that bacteria can have a profound impact on the process.

Specifically, bacteria can cause the uranyl phosphate to precipitate as nanoparticles within the bacterial cell wall, and these nanoparticles can enhance uranium mobility not only because they have a higher solubility than abiotic uranyl phosphate precipitates, but also because these nanoparticles, due to their size, can be just as mobile in the environment as dissolved uranium. The results of Fein’s work suggest that subsurface bacteria and their effects on uranyl phosphate formation must be accounted for in order to accurately model the mobility of uranium in these phosphate-amended contaminated groundwater systems.

Nitesh Chawla

Department of Computer Science and Engineering

Assistant Professor

Diseases do not occur in isolation; there are often common genetic, molecular, environmental, and lifestyle based risk factors that can be tracked. Nitesh Chawla’s research seeks to integrate and exploit these types of interconnections and the experience of millions of doctors and patients for the greater good by creating a Brain-Google called CARE (Collaborative Assessment and Recommendation Engine) that relies on a patient’s medical history and the history of individuals with similar symptoms, body types, and lifestyles, etc., in order to predict diseases risks.

For more information about Nitesh’s research, click here.

CARE uses collaborative filtering to suggest a more personalized approach to health care assessment. Imagine going into your doctor’s office and in addition to pulling up your personal information, your doctor can access similar symptoms and body types of millions of people just like you. CARE then works as an additional tool for your doctor. So he or she can essentially pool his or her expertise with the expertise of millions of other physicians and experiences of millions of other patients in a matter of seconds for diagnoses and preventative treatments to keep you healthier. You and your physician can then create a more personalized health care plan using literally generations of pertinent data. You can make lifestyle adjustments and/or schedule treatments to minimize risk or elevate healthy outcomes … saving millions of lives and millions of dollars.

Ken Sauer

Department of Electrical Engineering

Associate Professor

X-rays, CT scans, MRIs, and ultrasound scans are all imaging techniques physicians use to form their diagnoses. “Image reconstruction — developing an accurate picture from the indirect measurements created by these types of scans,” says Associate Professor Ken Sauer, “increasingly focuses on three-dimensional data. Using any of a variety of medical imaging modalities, we create the algorithms that transform non-invasive measurements into a three-dimensional map of a particular section of the body.”

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Sauer’s tomographic research, supported by the Indiana 21st Century Research and Technology Fund and the General Electric Corporation (GE) and in collaboration with researchers from Indiana University and Purdue University, focuses on two types of imaging: emission and transmission. In transmission imaging, such as an X-ray or CT scan, the image is constructed from the amount of radioactivity that transmits through the patient. In emission imaging, such as positron emission tomography (PET), the patient either inhales or is injected with a radioactive isotope whose subsequent emissions can be measured by medical personnel using the scanning equipment. For example, some tumors absorb certain types of glucose at higher rates than healthy tissue. When this glucose is tagged with radioactive tracers, the signals sent back during the scan can help identify the location and size of the tumor, as well as how active it is.

“What is different about the methods we use” says Sauer, “is that they’re based directly on the statistics of the data. We assume the data received from imaging techniques has problems. For instance, since only a limited amount of radioactive material can be injected into a patient, the signals from those isotopes can be relatively weak. So we explicitly include those limitations of quality in our inverse problem solutions to create more accurate images using less radiation (reducing a patient’s exposure to radiation).”