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Post-doc Mohammadreza Khani is spending his summer building computational fluid dynamics models of cerebrospinal fluid motion around the brain to improve drug delivery for central nervous system diseases.

His cutting-edge research is shedding new light on how to treat devastating central nervous system (CNS) diseases.

Since 2016, Khani has worked in the Neurophysiological Imaging and Modeling Laboratory under Chemical and Biological Engineering Associate Professor Bryn Martin.

Research in the lab focuses on using medical imaging and advanced modeling to help diagnose and treat CNS diseases, such as ALS (Lou Gehrig’s disease), brain and spinal cord cancers, Alzheimer’s, spinal muscular atrophy, structural defects of the skull, hydrocephalus and others.

Testing drugs used to treat these diseases in human trials is not only risky but expensive, with some drugs costing more than $2 million per treatment.

Khani has developed computational models of the entire central nervous system including extremely detailed and complex anatomic and physiological detail of the cerebrospinal fluid in a human.

This type of modeling is aimed to help medical doctors better design medical devices, drug delivery protocols and drugs specifically tailored for a particular patient. The modeling approach also helps reveal never before seen details about how the cerebrospinal fluid system works and its role to help maintain brain heath.

Using advanced computational modeling approaches, researchers can track a drug’s rate of dispersion around the spinal cord and brain to optimize drug delivery protocols and devices. Khani’s research has also helped identify what injection locations along the spinal cord or within the ventricles of the brain allow for the best dispersion to bring a patient quick relief.

Khani, who also earned his doctorate from U of I, has published 10 papers in leading journals within the field.

Despite challenges added by the COVID-19 pandemic, our students are staying safe and active through remote and on-campus internships and research this summer. Read more at uidaho.edu/engr-summer.

“For me, engineering is a way I provide a service. The core of engineering is to solve problems efficiently. I have changed my career paths throughout these four years, but my goal to serve through engineering projects has never changed.” – Archana Dahal, Biological Engineering Class of 2020 (ME minor)

This summer, Archana Dahal worked as a quality assurance intern for Glanbia Nutritionals in Clovis, New Mexico, learning about quality control and cheese processing.

While at U of I, Dahal attended the 2018 Annual Conference of the Society of Women Engineers in Minneapolis, Minnesota. She was part of a team that earned second place in the PepsiCo-SWE engineering challenge

“It was a surreal experience to represent U of I on a national platform,” she said. “This experience would not have been possible with the support from the Society of Women Engineers chapter at U of I.”

Dahal came to U of I from Dharan, Nepal.

“I wouldn’t have been able to afford to finish college without the scholarships that I received from the U of I International Programs Office,” she said.

Dahal also served as the vice president of the U of I Nepali Student Association and as a resident assistant for Housing & Residence Life.

“I have learned to be more empathetic, assertive and a caring leader through my experience,” she said.

Dahal will start graduate school this fall at the University of Utah.

Chemical engineering senior Sara Murphy is improving lead-acid battery performance this summer using an innovative and useful form of carbon.

The highly conductive Graphite from ÐÒÔË¿ìÈý Thermolyzed Asphalt Reaction, or GUITAR, burns like carbon. In addition to its use in battery additives, it has been tested for a variety of research applications, including the purification of saltwater as well as electrodes for hydrogen-powered vehicles.

Using a rotary kiln, Murphy is heating various types of particles to 900 degrees Celsius and vaporizing diesel over them, coating them in GUITAR. The GUITAR provides conductivity and other benefits to produce effective battery additives.

The goal is to use these additives to improve a battery’s max utilization, or its ability to use lead material inside the battery toward the chemical processes that power it. The more material used, the better the battery life and performance.

One problem with GUITAR coating is it makes the particles hydrophobic, or adverse to water, a standard agent in lead-acid batteries. In order to get chemicals to mix and react properly, Murphy is working to troubleshoot new ways to make the particles hydrophilic so they mix well with water.

“In engineering, everything has to be about scaling up,” she said. “No matter how innovative, if it’s not easy and convenient, people won’t use it.”

Murphy is currently experimenting with heating up the GUITAR-coated particles again while maintaining a constant airflow over them. This process alters the GUITAR coating without burning it off. The alterations helps particles better submerge in water.

“Computer science is a field that has applications in nearly every industry and is becoming a necessary skill in today's world. It is an exciting field that is expanding by the year and is only limited by your imagination to try.” – Blakely Frechette, Computer Science Class of 2020

Blakely Frechette is now working for Micron USA in their Boise branch as an IT software engineer.

She also interned for Micron during college, prototyping a mobile application to enable access to existing on-site applications.

“The internship allowed me the freedom to research and learn as well as work in and be supported by a team of individuals,” she said.

Frechette said the internship also prepared her for her senior capstone project, designing a web application to manage equipment reservations and machine access for the Department of Mechanical Engineering's Machine Shop on the Moscow campus.

Computer science graduate student Joel Oduro-Afriyie is spending the summer developing the conversational AI system, Omniscient.

Oduro-Afriyie’s system would help AI-powered virtual assistants better understand paragraphs of natural language and use that information to deduce concepts that are not explicitly stated. A user can ask a random number of questi