The University of Utah’s College of Engineering is dedicated to researching solutions to fight the COVID-19 coronavirus that has plagued most of the world.
The University of Utah’s Office of the Vice President for Research, in partnership with the Immunology, Inflammation and Infectious Disease (3i) Initiative, has awarded $1.3 million in seed grants to 56 cross-campus research projects that will examine a host of issues arising out of the pandemic. Of those, ten are going to projects initiated by College of Engineering researchers. Here is a list of the ten engineering proposals being funded. Click here to see a full list of all 56 projects funded by the seed grants.
Chemical free inactivation of coronavirus via electroactive nanostructured cupric oxide (ENCO) (Chemical Engineering Assistant Professor Swomitra Mohanty)
Mohanty and his team have developed a nanostructure from a form of copper (Cu2+) that can deactivate the virus by interacting with the nucleic acids that make up the virus and their outer protein membrane. Copper normally disarms viruses over time, but it is a slow process. But this material, with a unique method, can immediately deactivate the virus in tiny droplets. This material, which is chemical free, could be used in N95 masks to neutralize the virus as it is drawn into the mask or in hospital air filtration systems. It also could be built into a device like a wand or mop that could deactivate the virus on a table surface or floor.
Disinfecting nanobubble shield against COVID-19 in hospital ER/ICU environments (Civil and Environmental Engineering Professor P.K. Andy Hong)
This technology creates an air defense shield in hospital emergency rooms and ICU rooms with invisible microdroplets of mist that carry smaller nanobubbles of air with a virucide – benzalkonium chloride – to disinfect the air. This mist can prevent viral cough droplets from traveling in the air by killing the virus with the disinfectant. The technology also can be used to disinfect hospital water that is commonly invaded by pathogens. The project will result in a new defense to reduce transmission risks by air and water and increase protection for healthcare workers as well as patients.
Municipal wastewater monitoring based surveillance and prediction tools for community level occurrence and spread of COVID-19 (Civil and Environmental Engineering Associate Professor Jennifer Weidhaas and Civil and Environmental Engineering Professor Ramesh Goel)
Weidhaas and Goel are researching whether if studying concentrations of COVID-19 in samples from city wastewater sewage facilities can give them an accurate reading of how many people have the virus in a particular area served by each facility. The virus, much like prescription drugs and illicit drugs, is excreted from people through their feces and urine that eventually is flushed into sewage plants. With this kind of information, health officials could get a better idea of where hotspots of the virus are in communities, even with carriers of the virus who have not exhibited symptoms.
Enabling the in-situ real-time detection of COVID-19 viruses via a quantum tunneling-based nanogap sensor (Electrical and Computer Engineering Associate Professor Hanseup Kim)
Currently, the only way to detect the COVID-19 virus is through the testing of carriers. On-spot and real-time detection of COVID viruses as they are being carried in droplets in air could be a game changer to minimize the time delay between the outbreak and a confirmed diagnosis. Kim’s research involves using quantum tunneling phenomena to create a real-time sensor that detects COVID-19 viruses in the field, with a sensitivity enhancement greater than a thousand times compared to the most recent sensor technology.
Multiplexed detection of COVID-19/SARS-CoV-2 biomarkers for diagnosis and surveillance (Electrical and Computer Engineering Research Assistant Professor Lars Laurentius and Chemical Engineering Professor Marc Porter)
Healthcare researchers stress that nationwide testing is one of the most important factors in helping contain the COVID-19 coronavirus. Laurentius and Porter are developing a point-of-care diagnostic test for the simultaneous detection of virus biomarkers and immune response antibodies in patients to capture different stages of the infection. They believe they can adapt their current testing platforms, which were developed for detecting infectious disease and health markers, to be used for COVID-19. This could lead to a rapid, inexpensive, and potentially more accurate test than what is currently being used nationwide.
Rapid Microfluidic Synthesis of Novel SARS-CoV-2 Entry Inhibitor Antiviral Drugs (Electrical and Computer Engineering Professor Carlos Mastrangelo)
It is crucial that researchers develop as quickly and safely as possible a drug to treat the COVID-19 coronavirus infection. But finding the right drug compound in a pharmaceutical company’s vast library to work against the virus can be a lengthy process. Mastrangelo is developing a rapid system for the synthesis of new antiviral drugs with a new process involving a microfluidic device. Unlike conventional drug development cycles that require long, random search experiments, his new synthesis system could rapidly produce new antivirals in a deterministic manner from existing information about the virus avoiding the random search entirely.
Detection of Airborne COVID-19 Using Capsid Protein Aptamers in Exhaled Air (Electrical and Computer Engineering, USTAR Professor Massood Tabib-Azar)
Testing is one of the most important functions to help mitigate the spread of COVID-19, but lack of testing supplies have currently hindered the U.S. in its goal of conducting five million tests per day. Tabib-Azar is developing a reusable, portable sensor about the size of a quarter that can detect the presence of the virus in people or the environment. The sensor can either be a standalone device or work with a cellphone and can produce results in about a minute.
AI/CXR early warning system for infectious respiratory disease outbreaks (Electrical and Computer Engineering Professor Tolga Tasdizen)
Tasdizen is developing an early warning system for respiratory infection outbreaks using Artificial Intelligence analysis of routine chest x-rays. By using software and machine learning – specifically convolutional neural networks – healthcare systems could analyze chest x-rays in databases (without knowing patient identities) to look for certain deviations related to a virus. That in turn creates an AI model in which future x-rays input into the system would automatically search for those deviations and determine seasonal and local patterns. This could help national and local governments to determine early where a virus breakout might happen.
COVID: Understanding the capturing and evolution behavior of wetting and non-wetting aerosols on nanofibers matrix (Mechanical Engineering Assistant Professor Jiyoung Chang)
Recent studies show that the COVID-19 virus can easily exist as an aerosol and be detected as a viable form over three hours, which greatly increases the levels of transmissions. The most effective way, at least for now, to prevent the contraction of coronavirus in aerosol is wearing face masks. A nanoscale fiber membrane could provide an effective and affordable solution for the filtration of a virus aerosol. Chang’s research aims to investigate the nanoscale capture and evolution of aerosols on polyimide nanofibers, which can serve as an important foundation for the development of advanced filters and masks.
Synthesis of easily sterilizable and reusable xerogel filters for N95 respirators (Metallurgical Engineering Assistant Professor Krista Carlson)
Single-use N95 respirator masks are in great demand at hospitals nationwide due to the COVID-19 pandemic, but manufacturers cannot keep up. Carlson, who is also under the U’s College of Mines and Earth Sciences, is developing a silica xerogel filter that provides the same efficiency as a N95 filter, but unlike the single-use respirators or current filters for reusable respirators, these xerogel filters can be repeatedly sterilized for reuse. Filters will be made by drying silica-based gels to obtain crack-free xerogel filters that fit into reusable respirators. Data collected from this study will also be used in future proposals to study filtration efficacy with viruses.