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2nd Industrial Workshop on Separations Technology at UConn Tech Park
The Connecticut Center for Advanced Separations Technology (CCAST) hosted its 2nd Industrial Workshop on Separations Technology at UConn Tech Park on October 5-6th.
CCAST Center Director Jeff McCutcheon was thrilled with the success of this year’s event and explains that his vision is “for the workshop to become a premier event on industrially relevant separations that features talks from prominent speakers from industry.” The 1 ½ day event drew over 110 registrants from more than 60 companies and featured 16 speakers, 19 panelists, and over 20 poster presenters focused on separations technology innovation, financing, startups, and technology needs across different industries.
The dynamic workshop was well attended by a range of separations technologies stakeholders, including end users, established providers, start-ups, public/private funding entities, researchers, and experienced industry experts, providing an excellent networking opportunity for guests.
Speakers and panelists discussed the importance and value propositions for new separations technologies, with a range of topics including challenges that require new separations technologies, business opportunities for new separations technologies, how separation technologies impact industry and businesses, innovations in separation technologies, and perspectives and trends on the separations field that may guide future R&D efforts.
McCutcheon expressed his thanks to all who helped make the event happen. “This year’s workshop would not have been possible without help from my co-organizer Dr. Shan Yong,” he says. “It really does take a village to run a workshop, and I’m grateful to UConn, CCAST and C2E2 staff, faculty, and students for lending so much support for this event. I greatly appreciate all the panelists, speakers, and company representatives who shared their research and insights at this far-reaching workshop. Special thanks goes to all our sponsors for helping make this a free event for all who attended!”
The 2023 workshop company sponsors are Connecticut Department of Economic and Community Development, Mott Corporation, and the Athletic Brewing Co. Planning is already underway for the 3rd Industrial Workshop on Separations Technology at UConn Tech Park! Click here to share your agenda suggestions and join the mailing list for the 2024 workshop, or email jeffrey.mccutcheon@uconn.edu
Connecticut Center for Applied Separations Technologies serves the State of Connecticut, greater New England, and the U.S. by identifying opportunities to implement membrane and other advanced separation technology into various industrial and manufacturing processes in order to lower energy use, reduce carbon footprint, limit waste, and prevent adverse environmental and health impacts.
New Center at UConn Tech Park Teams Up Nurses and Engineers to Develop Innovative Healthcare Solutions
Tech Park is delighted to welcome the recently established Nursing and Engineering Innovation Center, co-directed by Tiffany Kelley, UConn School of Nursing and Leila Daneshmandi, UConn College of Engineering. The new center, one of the first of its kind in the nation, focuses on advancing healthcare and promoting workforce and economic development by fostering interdisciplinary collaborations between nursing and engineering.
Patient healthcare greatly benefits from and is influenced by new technologies, but implementing new technology effectively can be a challenge. Engineers are expert problem solvers and builders but may lack clinical insights that are essential for application. Nurses, on the other hand, are ground-floor experts for how a product “should” work and often find themselves improvising solutions for technologies that are complex or less practical.
The Nursing and Engineering Innovation Center aims to bridge this gap by involving nurses and engineers early in the design phase, addressing real-world issues before a product reaches the clinic. User-centered design is a critical first step in overcoming these technology design barriers and holds significant potential to enhance patient care and amplify the impact of healthcare innovations.
The Center will focus its first two to three years on the creation of seed grants for collaborative research among faculty along with joint educational programs for students through Senior Design, coursework, and fellowship programs.
The Center recently announced its NursEng Healthcare Innovation Seed Grant and is currently accepting proposals through November 15, 2023, 5:00 pm. This seed grant was established to promote and support interdisciplinary and innovative research, scholarship, and creative collaborations among faculty from the Schools of Nursing and Engineering that will advance innovation in healthcare technology and have strong potential as a foundation for extramural funding for larger-scale innovation and research activities in the future.
Innovation research, scholarship, and creative collaborations funded by this grant are expected to lead to significant long-term outcomes, such as publications, intellectual property, academic symposia, and future research, scholarship, or collaborations. Click here for more details.
In another initiative, the Center launched the NursEng Innovation Fellowship in April that teams up nursing and engineering undergraduates and empowers them to tackle unmet needs in equitable healthcare quality and to design innovative healthcare technology solutions.
Daneshmandi, a seasoned entrepreneur, explains, “this new program is designed to foster creativity, collaboration, and user-driven innovation and entrepreneurial thinking in healthcare.”
Students are selected for the Fellowship through a proposal process to collaborate as part of an interdisciplinary team to address a healthcare challenge in need of a technological solution. Throughout the academic year, Fellows are trained in user-driven innovation, prototype development, and entrepreneurial skills. Students also benefit from mentoring sessions and access to prototyping centers and receive up to $1750 in seed funding to support prototype development. At the culmination of the Fellowship year, each student team will present their project achievements and upon successful completion of the program, Fellows will receive a certificate of completion. This initiative is currently funded by an awarded Courses and Programs grant from VentureWell.
The Nursing and Engineering Innovation Center’s longer-term strategy is to expand its scope to create a shared state-of-the-art research and teaching facility, which will require major University, state, federal, or donor investment.
Kelley is enthusiastic about the potential offered by the new Center, saying, “By partnering our students and workforce in the nursing and engineering fields and advancing their education with the appropriate knowledge, skills, and attitudes toward innovative behaviors and culture, we hold the potential to drive significant positive change in the profession of nursing and health care at large.”
Visit the Nursing and Engineering Innovation Center web site to learn more about the Center, meet this year’s seven Fellows, and find out about other opportunities at the Nursing and Engineering Innovation Center.
Tiffany Kelley, Ph.D., MBA, RN-BC, is Visiting Professor and Director of the UConn School of Nursing’s Healthcare Innovation Online Graduate Certificate Program. Leila Daneshmandi, Ph.D., is Assistant Professor in Residence in Innovation and Entrepreneurship and Director of the entrepreneurship Hub (eHub) in the UConn School of Engineering.
Opportunity Lights Up UConn Sustainable Energy Summit
The Sustainable Clean Energy Summit
Registration is now open for The Sustainable Clean Energy Summit: Decarbonizing Society and the Grid on October 4, 2023.
Co-hosted by the University of Connecticut and Eversource, the summit will take place at UConn, Storrs and will bring together academic, utility, industry, municipal and legislative experts to discuss the shifting energy landscape and will feature final presentations from six student-led research teams as part of the Eversource-sponsored Clean Energy and Sustainability Innovation Program (CESIP). As part of this program, students are researching possible solutions (technical, social, and political) to address different aspects of the grand challenge of decarbonization at the local (UConn campuses), state and regional (New England) levels.
The student teams will be presenting their work at the summit. Based on their presentations and the future potential of their work, a winning team will be selected for funding. It is our hope that highlighting the important work of these students on real challenges will open the door for engaging conversations throughout the summit. We anticipate many students will attend.
The summit will open with the keynote speaker Gina McCarthy, White House National Climate Advisor and Former Administrator, U.S. Environmental Protection Agency, and include two panels with leaders from industry, government (state and national), and community organizations: one on the decarbonization of the grid and the second on the technologies of geothermal and hydrogen. The closing Clean Energy Engagement Fair will begin with a brief student panel representing groups from across the University, sharing their motivation and approach to involvement. Afterwards, there will be booths and resources providing information about how to get involved in the clean energy space at UConn and in the industry. We are proud of the work that every UConn student undertakes during their education to increase their citizenship and their interest in the social, economic, cultural, and natural environments of the state and beyond.
We hope you can participate. Learn more and register here!
DATE CHANGE – Register Today: AI Workshop hosted by UConn’s CT Advanced Computing Center
Future Climate Venture Studio Launches Second Cohort
UConn School of Engineering announces the new Engineering Center for Advanced Engineering Education
The center allows engineering students of all backgrounds to improve their skills in cutting-edge subject areas and develop in-depth knowledge tailored to their specific professional goals. Offered through the UConn School of Engineering, the Center for Advanced Engineering Education (CAEE) offers top-tier teaching that’s relevant, accessible, interactive, convenient, and affordable.
For more information on the Center, contact Center Director Nora Sutton at nora.sutton@uconn.edu or visit advancededucation.engineering.uconn.edu. The Center can also be reached at engrcaee@uconn.edu.
Pamir Alpay Appointed Vice President for Research, Innovation, and Entrepreneurship
Leveraging Active Machine Learning to Optimize 3D Printing Autonomously
Inkjet printing has evolved from a graphics and marking technology to a broader variety of additive manufacturing and 3D printing processes for electronic, optical, pharmaceutical, and biological applications. The success of adopting inkjet technology for these newer applications is contingent on whether the ink materials can be consistently and reliably jetted by the print systems. Currently, each printer-and-ink combination requires calibration by trial and error, which consumes a considerable amount of time and materials. IPB researcher, Prof. Anson Ma, Site Director of SHAP3D, teamed up with UConn machine learning expert, Prof. Qian Yang, to demonstrate a new concept of “autonomous 3D printing”, leveraging an active machine learning method they developed to efficiently create a jettability diagram that predicts the best conditions for jetting an ink from a printhead.
Briefly, a camera is used to image the printhead and capture the behavior of ink jetted from a printhead. Starting with a few randomly chosen conditions, a machine learning algorithm predicts the optimal jetting conditions and then “cleverly decides” on the next set of experiments that can further improve prediction accuracy. After performing those experiments, the algorithm analyzes the newly acquired images, updates the prediction for the desired jetting conditions, and iteratively selects the next experiments, continuing autonomously until a small experimental budget is reached. This approach has achieved a prediction accuracy of more than 95% while considerably reducing the number of experiments required by 80% compared to a typical grid-search approach. This novel approach is especially powerful for optimizing complex print systems with many tunable process parameters.
This work was recently published in the journal 3D Printing and Additive Manufacturing (http://doi.org/10.1089/3dp.2023.0023) and led to a pending patent application (WO 2023/2788542).