The Office of the Vice President for Research (OVPR) recently announced the recipients of the 2022-23 SPARK Technology Commercialization Fund Program. Five recipients were selected for internal funding through the program. They include researchers from UConn and UConn Health.
SPARK supports innovative proof-of-concept studies seeking to translate research discoveries into products, processes, and other commercial applications. The program’s primary goal is advancing primary faculty inventions toward the market, where they can have a positive impact for UConn, society, and Connecticut’s economy.
The 2022-23 awardees competed for funding in a highly selective process. Congratulations to the following:
LaijunLai, UConn, Department of Allied Health Sciences Targeting TAPBPL in antitumor immune therapy
RamanBahal, UConn, Department of Pharmaceutical Science Liver- and Kidney-targeted delivery of next generation miRNA inhibitors using carbohydrate-based conjugates
EugenePinkhassik, UConn, Department of Chemistry/Institute of Materials Science Integration of palladium-catalyzed reactions in continuous manufacturing
AliTamayol, UConn Health, Department of Biomedical Engineering Engineering a Handheld One-step Foaming and Printing Device for the Treatment of Soft Tissue Injuries
LuyiSun, UConn, Department of Chemical and Biomolecular Engineering/Institute of Materials Science High Performance Nanocoatings for Packaging Applications
For more information about SPARK, visit the program website.
Arash Esmaili Zaghi, left, associate professor of civil and environmental engineering, left, Fabiana Cardetti, professor of mathematics, and Jie Luo, a graduate student, with the fMRI, and Fumiko Hoeft, professor of psychological sciences, Nicole Landi, associate professor of psychological sciences, are in the control room at the UConn Brain Imaging Research Center on March 7, 2022. (Peter Morenus/UConn Photo)
An ambitious team of researchers from across the University has won $3mn from the National Science Foundation to pursue a project in the neuroscience of learning.
The program, known as TRANSCEND: TRANSdisciplinary Convergence in Educational Neuroscience Doctoral training, aims to get graduate students from both classic and atypical backgrounds into educational neuroscience research.
“We will take an innovative approach and truly break the silos in educational neuroscience between lab research, research in the schools and the community. We also have a particularly strong focus not only on neurodiverse learners as the topic of research but also to involve them as graduate students. Neurodiverse learners are one of the most underrepresented groups in higher ed and the STEM workforce despite their tremendous talent,” says Fumiko Hoeft, interim director of the Waterbury campus, director of UConn’s Brain Imaging Research Center (BIRC) and the principal investigator on the project.
The team also includes co-principal investigators Assistant Professor of Educational Psychology Ido Davidesco, Associate Professor of Developmental Psychology Nicole Landi, Associate Professor of Civil and Environmental Engineering and IMS faculty member, Arash Esmaili Zaghi, and Professor of Clinical Psychology Inge-Marie Eigsti; and co-investigators Professor of Psychology James Magnuson, Professor of Mathematics Fabiana Cardetti, Professor of Computer Science and Engineering Jinbo Bi, and Vice Provost for Graduate Education Kent Holsinger. Hoeft and Landi will co-direct TRANSCEND.
TRANSCEND will use the grant to allow second year graduate students to spend a full year researching convergent questions in educational neuroscience, with an emphasis on virtuous cycles between school and lab-based research, interdisciplinary team science, and in all areas of learning such as STEM and reading as well as developing the next generation of learning technologies using artificial intelligence (AI), with an underlying theme of neurodiversity.
The hope is that the students will then stay in the program and continue research on their topic of choice for their dissertation. Graduate students can be from any field of cognitive science, neuroscience, educational psychology, mathematics, computer science, and engineering. All graduate students in the program will have the opportunity to collect data in classrooms and in UConn labs, including the BIRC, the Cognitive Sciences Shared Electrophysiology Resource Lab, and the new mobile neuroscience lab by the College of Liberal Arts and Sciences that is planned to come online by this winter.
Community engagement will be key for generating project ideas and at every step of the process; graduate students will research questions that communities and teachers want answered. Leveraging Hoeft’s new position at
Researchers from Dr. Landi’s lab training high school student interns to place an EEG cap on a younger student’s head at the AIM Academy. (Landi Lab Photo, with permission from AIM Academy).
UConn Waterbury and this grant, she hopes to engage the Waterbury students and the community to bring new programs and collaboration to the campus.
For example, a team of students from computer science, educational psychology and cognitive neuroscience may develop a learning technology leveraging AI and natural language processing models, using accessible neuroimaging technologies such as portable electroencephalography, in partnership with an education technology company and a school.
“We want every STEM and Education grad student in the University to know they can join this. The funding is for their second year, but we want the graduate students to stay involved in the program throughout graduate school,” says Arash Zaghi, a structural engineering professor.
Zaghi began researching neurodiversity when he was diagnosed with ADHD early in his career as an engineer. He found that there was a lot of research showing great creative potential from neurodiverse people, but also great difficulties that lead them to drop out of university settings. Part of the motivation behind this collaboration is to generate strategies that both teachers and students can use to create strength and success from neurodiversity.
Hoeft and Zaghi also emphasize that neurodiverse students are strongly encouraged to apply. The team has partnership with universities in the NSF INCLUDES national network such as Landmark College, a college for students with learning disabilities. They hope to attract their students into graduate school at UConn through this grant. There are also almost 40 other partners, including schools, the Connecticut Department of Education, advocacy groups, and technology companies, all of whom are interested in gaining interns from the program and participating in research through partnership with UConn. Through this program, their hope is that neuroscience can help design and deliver education that helps all students reach their full potential, and at the same time enhance the STEM workforce.
Three new grants totaling $7.5 million from ARPA-E and the U.S. Department of Energy (DOE) are enabling UConn researchers to conduct ground-breaking work on some of the nation’s most pressing energy problems.
Advanced Research Projects Agency-Energy (ARPA-E) grants provide funding for the development of transformational technologies that provide new ways of generating, storing, and using energy.
Shrinking Substations for Green Energy Integration
Yang Cao, a professor in the School of Engineering, is working on a three-year ARPA-E project to create a new technology that will help stabilize the power grid and integrate renewable energy sources into the existing energy infrastructure.
Substations are sprawling networks of wires, towers, and transformers. Substations change the high voltage that comes directly from energy generation stations into low voltage that can safely be delivered to homes or businesses.
The century-old energy infrastructure in the United States is prone to power outages, especially during increasingly common severe weather.
This infrastructure is also poorly suited to renewable energy sources as they were designed for fossil fuels.
With something like wind or solar energy, the energy sources are spread out across a huge expanse rather than coming from a neatly packaged oil barrel. Solar panels or wind turbines also tend to be in remote areas far from major cities that have massive electrical needs. This means we need more efficient technologies that can link distributed energy generators to urban areas.
Cao will work with Virginia Tech on the project, titled Substation in a Cable for Adaptable, Low-cost Electrical Distribution (SCALED), to develop high-voltage cables to replace bulky substations.
“We need a more versatile and compact conversion and integration solution for distributed renewable energies,” Cao says. “This overall project is targeting that.”
Making something this compact will be highly advantageous as they can be placed almost anywhere, whereas current substations require a tremendous amount of open space.
The goal of the project is to greatly reduce the footprint of substation technologies without compromising its effectiveness.
“We could really have a very compact substation that helps to convert and integrate the distributed energy generation into a grid instead of having really large, bulky substations,” Cao says.
A Better Path for New Materials
Dr. J. Nathan Hohman
Nate Hohman, assistant professor of chemistry, is working on a new DOE grant to develop artificial intelligence (AI) tools to improve the synthesis of new materials.
While scientists are constantly innovating new materials for energy, biotechnology, and many other applications, currently, the best tool they have at their disposal for this process is trial and error.
“Engineering a new hypothetical material today requires guesswork at every step,” Hohman says. “We guess what compounds might crystallize into a structure that may have a property of interest, hope we get the material we expected, and pray it has the properties we imagined. This is inefficient, labor intensive, and has a low likelihood of success.”
Hohman will combine nano-crystallographic characterization with Euclidean neural networks to develop a better technique for real-time characterization of materials using a continuously variable model material system.
Crystal characterization allows scientists to see how the atoms that make up a molecule are arranged. This information is critical for designing new materials as this structure is what determines what the material can do.
Hohman recently found a way to study crystal structure using an X-ray beam. This allowed his team to capture a crystal’s single diffraction pattern and merged them into a data set they can use to determine the atomic structure. This speeds up the process of characterizing new materials from months or even years to just hours.
Euclidean neural networks are artificial neural networks inspired by the human brain. A set of artificial neurons transmits signals to other neurons in the system in order to classify objects. Hohman’s collaborator Tess Smidt at MIT developed Euclidean neural networks that can handle 3-D geometries, like those of molecules.
Hohman in collaboration with other synthetic materials scientists, computational crystallographers, and deep learning researchers will use these networks to train machine learning algorithms to predict new phases of materials. This will help eliminate guesswork from materials development.
Hohman will have the neural networks will help scientists design and generate novel atomic geometries with desirable properties based on what the scientists want the material to do.
Designing for High Heat
Dr. Julián Norato
Julián Norato, associate professor of mechanical engineering, is working on an ARPA-E grant to develop computational techniques to design highly efficient and compact heat exchangers.
Heat exchangers are mechanical devices that transfer heat from a hot to a cold fluid. They are found in everything from air conditioners to space heaters to chemical plants to airplanes.
The heat exchangers Norato’s group will focus on operate at temperatures above 1100 degrees Celsius (approximately 2000 degrees Fahrenheit). These high-temperature heat exchangers are used in many applications, including gas turbine engines, waste heat recovery and hydrogen production.
The grant will focus on plate-and-frame heat exchangers, which consist of stacks of plates bolted together to a frame. The hot and cold fluids flow between alternate plates. Each plate has a pattern of obstacles to the flow embossed on one side. This helps increase the amount of heat transferred from the hot fluid to the plates, and to the cold fluid flowing through the adjacent plates.
“The fluid is forced to go through the flow structures inside the plates,” Norato says. “Essentially, you’re putting obstacles to the fluid to force it to mix and spend more time going from the inlet to the outlet of the plate.”
What these obstacles look like will determine how efficient the heat transfer is. The computational techniques that Norato’s group will formulate will determine the optimal shape and pattern of these obstacles to maximize the heat transfer. At the same time, the design must ensure the pressure drop the fluid experiences as it flows through a plate is kept to a minimum, and that the plates can sustain the pressure the fluid exerts at the high operating temperatures.
The researchers are also interested in making the device as small and light as possible, which is especially important in aerospace applications that have space and weight restrictions.
The project will be conducted in collaboration with Altair Engineering, whose computational fluid dynamics software the researchers will use to simulate the heat transfer and the mechanical behavior of the heat exchanger.
Norato will also collaborate with researchers from Michigan State University, who have developed an additive manufacturing technique to efficiently 3D print the heat exchanger plates out of a metal alloy that can operate at high temperatures. They will 3D print the plate designs obtained by the computational techniques developed by Norato and test the performance and integrity of the heat exchanger in an experimental setup.
Dr. Cato T. Laurencin is now added to the AOA Award Hall of Fame (AOA Photo/Kyle Klein).
Dr. Cato T. Laurencin, University Professor at the University of Connecticut, has been honored by the American Orthopaedic Association (AOA) with its Distinguished Contributions to Orthopaedics Award adding him to its AOA Award Hall of Fame.
Laurencin, the Albert and Wilda Van Dusen Distinguished Professor of Orthopaedic Surgery at UConn School of Medicine, was selected for the special recognition by his AOA member peers for his remarkable personal achievement and contributions to orthopaedic surgery.
He accepted the award the evening of June 15 at the AOA’s Annual Leadership Meeting at the Rhode Island Convention Center in Providence. “I am so honored to accept the American Orthopaedic Association Distinguished Contributions to Orthopaedics Award and be recognized in the AOA Awards Hall of Fame. I feel so fortunate to be an orthopaedic surgeon.”
The AOA Distinguished Contributions to Orthopaedics (DCO) Award recognizes Laurencin for his personal achievement and broad contribution to the orthopaedic specialty, leadership, impact on patient care, and clinical and basic science research. The mission of the AOA is engaging the orthopaedic community to develop leaders, strategies and resources to guide the future of musculoskeletal care.
In addition to being a practicing sports medicine and shoulder surgeon consistently named to America’s Top Doctors list, Laurencin is a world-renowned surgeon-engineer-scientist and a pioneer of the field of regenerative engineering.
In fact, Laurencin is leading the first international effort ever for knee and limb engineering with his Hartford Engineering a Limb (HEAL) project which aims at regenerating a human limb by 2030. The National Institutes of Health and the National Science Foundation currently fund this research work through Laurencin’s large grant awards including the NIH Director’s Pioneer Grant Award and the National Science Foundation’s Emerging Frontiers in Research and Innovation Grant Award.
In orthopaedic surgery, Laurencin has been the first to win the “trifecta” of orthopaedic research lifetime awards: the Nicolas Andry Award from the Association of Bone and Joint Surgeons, the Marshall R. Urist Award from the Orthopaedic Research Society, and the Kappa Delta Award from the American Academy of Orthopaedic Surgeons.
Nationally, Laurencin is the first surgeon in history to be elected to all four national academies: the National Academy of Sciences, the National Academy of Engineering, the National Academy of Medicine, and the National Academy of Inventors. He is an elected fellow of the American Academy of Arts and Sciences and an elected fellow of the American Association for the Advancement of Science.
Laurencin is a laureate of the National Medal of Technology and Innovation, America’s highest honor for technological achievement, awarded by President Barack Obama at the White House. He is the recipient of the prestigious Spingarn Medal, the highest honor of the NAACP bestowed upon such Americans as Martin Luther King Jr., Maya Angelou, George Washington Carver, Jackie Robinson, and Duke Ellington.
At UConn Laurencin is also a professor of chemical engineering, materials science and engineering, and biomedical engineering and serves as CEO of The Connecticut Convergence Institute for Translation in Regenerative Engineering. He has received the highest honors in engineering, medicine and science, including the Philip Hauge Abelson Prize given for “signal contributions to the advancement of science in the United States.” The American Institute of Chemical Engineers recently established the Cato T. Laurencin Regenerative Engineering Founder’s Award in honor of his breakthrough achievements in that field.
Laurencin received his BSE in chemical engineering from Princeton University, his MD, magna cum laude from the Harvard Medical School, and his Ph.D. in biochemical engineering/biotechnology from the Massachusetts Institute of Technology.
Mechanical engineering professor Anna Tarakanova listens during the 2020 Women in STEM Frontiers in Research Expo, which she co-organized. (Contributed photo)
Anna Tarakanova has long had an interest in how objects and bodies work. Her chosen specialty in the field of Mechanical Engineering – studying the structure, function, and mechanics of biological systems and materials, especially fibrous protein materials such as elastin and collagen – merges the two.
The assistant professor of mechanical engineering and her team are working to establish a high-fidelity modeling framework for both healthy and degenerated elastins for use as a tool to resolve different pathological stressors affecting how elastin functions from a nanoscale.
During aging and with chronic, often age-related illnesses such as diabetes, cardiovascular disease, and osteoarthritis, elastin can degenerate, causing a decline in normal function. Elastin is an essential structural protein that gives the skin, heart, blood vessels, and other elastic tissues in the body the stretchy quality they need to function.
“At the molecular scale, there are a number of physical-chemical modifications that occur that drive this mechanical degeneration over time,” Tarakanova says. “Because they are quite numerous and act in parallel, it’s difficult to deconstruct which triggers impact mechanics and to what degree. If we can understand the mechanism, we can think about novel therapies to target aging and aging-associated diseases.”
Tarakanova’s work has earned her a 2022 Early Career Development (CAREER) Award from the National Science Foundation. She is one of 11 junior faculty members at UConn this year to receive the coveted award, which recognizes the recipient’s potential as a role model in education and research.
CAREER Awards come with five years of funding intended to provide a foundation for a young professor’s research program. Beyond advancing her research, Tarakanova plans to use the funding to create activities and events to engage and support undergraduate and graduate students, especially those from underrepresented groups. The effort will include a reboot of a Women In STEM Frontiers in Research Expo she co-organized with a colleague in January 2020.
“For me, it was kind of a natural extension of what I wanted to do as a professor, being a woman in STEM and being a minority for most of my education career,” Tarakanova says.
Elastin and collagen are not the only protein materials getting her attention. Early in the pandemic, Tarakanova and two of her graduate students began exploring the spike protein associated with SARS-CoV-2 to figure out how it moved when it interacted with the immune system. She is now working with Paulo Verardi, a pathobiologist in UConn’s College of Agriculture, Health and Natural Resources, and UConn biochemist Simon White to develop new and potentially better ways to stabilize spike proteins for use in COVID-19 vaccines, particularly in relation to emerging new variants of the virus.
“Some of the methods we are using to study the spike protein are related to the methods that we’ve used and continue to use to look at elastin,” she says. “It’s a different project, but it does broadly fall under this fusing of computing and computational models, physics, biomechanics, and biochemistry to understand the dynamic behavior of the COVID spike protein, the protein that sits on part of the corona.”
(from left to right) Guangfu Wu, Huijie Li, and Zhengyan Weng, advised by Professor Yi Zhang, are checking an array of graphene field-effect transistors.
In recent years, from H1N1 and now to SARS-CoV-2, global pandemics caused by highly contagious viral species have been threatening human life and putting tremendous pressure on healthcare services as well as the economy. Rapid testing and timely interventions for asymptomatic or mild infections caused by SARS-CoV-2, for example, would enable efficient quarantine of infected patients, thus significantly reducing the spread rate of the virus. Importantly, SARS-CoV-2 is expected to continue in the future fall/winter seasons, when it will coincide with the seasonal outbreak of other infectious respiratory diseases, including those caused by influenza virus and respiratory syncytial virus, which have similar signs and symptoms in the early stages. Considering the overlap in the seasonal peaks, symptoms, and underlying risk factors of these illnesses, having a rapid test to detect and differentiate SARS-CoV-2 from other infectious respiratory viruses will be clinically important.
In response to this clinical need, the Institute of Materials Science and Biomedical Engineering Assistant Professor Yi Zhang led the development of the most sensitive amplification-free SARS-CoV-2 diagnostic platform, the CRISPR Cas13a graphene field-effect transistor. This study, entitled “Amplification-Free Detection of SARS-CoV-2 and Respiratory Syncytial Virus Using CRISPR Cas13a and Graphene Field-Effect Transistors,” was published online on May 12, 2022, in the journal Angewandte Chemie International Edition.
“The key features of viral diagnostics are rapidness and sensitivity,” said Zhang. According to Zhang, most virus detection techniques, including the gold-standard RT-PCR, relies on viral sequence amplification, which can dramatically complicate the detection process and increase the risk of cross-contamination, therefore subject to elevated false-positive rates. However, current amplification-free methods are still limited by compromised sensitivity. “Our work revolutionized the field of amplification-free nucleic acid diagnostics by introducing a biosensing platform with sensitivity comparable with RT-PCR,” he said.
Dr. Yi Zhang
Derived from adaptive immunity in prokaryotes, Nobel-winning clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated (Cas) technology leverages nucleic acid base pair complementarity between a guide RNA and targeted nucleic acid sequence and affords high target specificity capable of discriminating single mismatches. Recently, several CRISPR/Cas systems, including Cas13a, were found to perform cleavage of nonspecific bystander nucleic acid probes triggered by target detection, known as “collateral cleavage.” Such collateral cleavage demonstrates a multi-turnover behavior, turning a single target recognition event into multiple probe cleavage events, and therefore leads to signal amplification.
“The idea of our biosensor design originates from exploiting the signal amplification by translating CRISPR technology onto an ultrasensitive detection platform,” said Huijie Li, a Ph.D. student in Zhang’s lab; she is also the leading first author of the study. Graphene, as a two-dimensional material, exhibits extraordinary charge carrier mobility and thus high electrical conductivity. Thanks to its atomic thickness, graphene, when constructed into biosensors as a sensing material, is highly sensitive to the interaction with biological analytes. In this study, by immobilizing probes on graphene-based field-effect transistors and allowing Cas13a collateral cleavage of these probes activated by target detection, SARS-CoV-2 down to 1 aM level in both spiked and clinical samples, was successfully detected within a 30 min detection time.
Simply by changing the guide RNA design, CRISPR Cas13a graphene field-effect transistor platform was reconfigured to target respiratory syncytial virus with the same attomolar sensitivity. “As the COVID-19 pandemic wanes, our virus diagnostic tool can be easily adapted to combat the future outbreak of unknown viral species,” Guangfu Wu, a Postdoc in Zhang’s lab; he is the co-first author of this work, said.
This study marks a significant milestone towards our goal of developing an integrated point-of-care biosensing platform for viral diagnostics. “We are aiming to offer patients a fast, ultrasensitive all-in-one tool that can streamline sample treatment and analysis and deliver results without any specialized training,” said Zhengyan Weng, a Ph.D. student in Zhang’s lab; he is also the co-first author of this study.
This research is supported by the University of Connecticut start-up and the National Science Foundation under the award number CBET-2103025. The collaborators of this work include Dr. Xue Gao at Rice University (co-corresponding author), Drs. Kevin D. Dieckhaus and Lori Avery at UConn Health, and Dr. Yupeng Chen in the Department of Biomedical Engineering at UConn.
Professor Yao Lin has been awarded a five-year NSF grant (DMR #2210590, $719,664), for his research project, “Advancing Processability and Material Performance of Synthetic Polyamino Acids with Transformable Secondary Structures.”
Dynamic transition from helices to sheets in fibrous proteins facilitates a remarkable increase in the strength, stiffness, and energy dissipation capacity. Polyamino acids (PAAs), also known as synthetic polypeptides, can adopt analogous secondary structures. However, inducing the structural transitions in the solid PAA of high molecular weights (MWs) is a largely unmet challenge. As a result, many of the PAA materials either have poor thermomechanical properties or are incompatible with polymer processing techniques such as extrusion and compression molding. This project aims to develop a general strategy to significantly improve the thermomechanical properties and processability of synthetic PAAs by taking advantage of metastable, transformable structures of PAAs and control over their in-situ transition and hierarchical organization.
The findings from this project may enable the generation of polymeric systems that will approach the level of sophistication and versatility found in some of nature’s biomaterials. The research also provides a model system of synthetic polymers with intrinsic secondary structures in which the different partitioning of intramolecular and intermolecular networks determines the macroscopic properties of materials, enabling comparison of the experimental results with predictions from simulations and modeling.
Graduate and undergraduate students will be trained on bioinspired polymeric materials and acquire skills in polymer synthesis, material characterization, mechanics, and computer simulations.
(l-r) Drs. Farhad Imani, Jasna Jankovic, Tomoyasu Mani, and Luyi Sun
The Scholarship Facilitation Fund program provides up to $2,000 to UConn faculty across all disciplines. The OVPR offers the competitive awards to promote, support, and enhance research, scholarship, and creative endeavors across UConn Storrs and regional campuses.
Four IMS faculty members were among the 67 faculty named as recipient of the award for Spring 2022:
Nate Hohman is the feature of the Materials Research Society (MRS) podcast, MRS Bulletin. Laura Leay interviews Hohman about the structure of two chalcogenolates his group uncovered. By combining serial femtosecond crystallography —usually used to characterize large molecules—and a clique algorithm, Hohman’s group was able to analyze the structure of small molecules. With serial femtosecond crystallography, large molecules like proteins produce thousands of spots on the detector; in contrast, small molecule crystals only a produce a few spots. The algorithm uses the pattern that the spots make on the detector to determine the orientation of as many crystals in the liquid jet as possible. The data from each crystal can then be merged together to find the structure. Nate’s research is featured in the 2022 IMS Annual Newsletter.
On February 14, 2022, ARPA-E announced $175 million for 68 OPEN 2021 research and development projects aimed at developing disruptive technologies to strengthen the nation’s advanced energy enterprise. These high-impact, high-risk technologies support novel approaches to clean energy challenges.
Associate Professor and Electrical Insulation Resource Center (EIRC) Director Yang Cao and fellow researchers from Virginia Polytechnic Institute and State University (Virginia Tech) will combine the functionality benefits of power electronics with the power density benefits of high-voltage cables to create a cohesive, all-in-one structure to replace bulky, inflexible power substations in today’s electrical grid. This “substation within a cable” design uses a cascade of coaxial power conversion cells to gradually step-down voltage to levels required by the loads. Virginia Tech’s module can achieve high power density and a form factor that enables seamless integration with the cable by mimicking a coaxial geometry design. This could eliminate the need for large and expensive power substations and enable simple integration of renewable energy sources, an electric vehicle fast-charging infrastructure, energy storage, and efficient direct current distribution lines.
The research project, Substation in a Cable for Adaptable, Low-cost Electrical Distribution (SCALED) has received $2,953,389 in funding support through the ARPA-E OPEN 2021 initiative.
