Cornell University SPROUT Awards Back 6 Innovative Research Collaborations
From 3D-printing walls that protect against rising sea levels to leveraging machine learning to understand connections that lead to post-traumatic osteoarthritis, the latest of Cornell Engineering’s SPROUT Awards are enabling cross-disciplinary collaborators to pursue novel and impactful research at the intersections of multiple fields.
SPROUT – which stands for Support for Promising Research Opportunities and Unconventional Teams – launched in 2022. The annual program aims to fill a funding gap and provide encouragement for emerging collaborations, especially those that involve unexpected combinations of people and ideas, that have demonstrated early success but have yet to mature to the point of gaining meaningful external support.
“Novel and unconventional ideas can be among the most rewarding and impactful to pursue, and sometimes they require a little more time and support in their early stages,” said Lois Pollack, associate dean for research and graduate studies at Cornell Engineering. “SPROUT Awards are a testament to Cornell Engineering’s commitment to cross-disciplinary collaboration and research that truly makes a difference.”
This year’s winning projects are:
Integrating machine learning, materials modeling, and high-throughput experiments for the discovery of ultra-stable metal-organic frameworks for water purification
The goal of this project by Nicole Benedek, associate professor in the Department of Materials Science and Engineering; Julia Dshemuchadse, assistant professor in the Department of Materials Science and Engineering; Michael Thompson, the Dwight C. Baum Professor of Engineering in the Department of Materials Science and Engineering; and Phillip Milner, associate professor in the Department of Chemistry and Chemical Biology, is to integrate machine learning, first-principles atomistic and coarse-grained modeling, and autonomous experimentation for the rapid discovery of ultra-stable metal-organic frameworks for water purification.
Machine learning to understand the connection between cartilage mechanics, chondrocyte signaling and post-traumatic osteoarthritis
Post-traumatic osteoarthritis frequently develops secondary to joint injury, with clinical manifestations of pain and dysfunction lagging months to years after the injury. Effective therapies for treating the condition require in-depth understanding of signaling cascades and the spatial and temporal patterns of cellular phenotypes that result from joint injuries.
This project, led by Lawrence Bonassar, the Daljit S. and Elaine Sarkaria Professor in Biomedical Engineering in the Meinig School of Biomedical Engineering and the Sibley School of Mechanical and Aerospace Engineering, aims to determine how altering bioenergetics pathways in human articular cartilage affects the distribution of cellular phenotypes that develop in response to impact injury. Co-investigators include Itai Cohen, professor in the Department of Physics; Michelle Delco, the Harry M. Zweig Assistant Research Professor in the College of Veterinary Medicine; Sabrina Strickland, associate professor at the Hospital for Special Surgery at Weill Cornell Medical College; and Andreas Gomoll, professor at the Hospital for Special Surgery at Weill Cornell Medical College.
Ion transport through semiconducting mesocrystal membranes
Communication in biological systems relies on transporting ions and small molecules across nanoscale channels. Conversely, modern technology predominantly relies on electronic or photonic signals for communication. The longer-term vision is to bridge this divide by developing artificial synaptic membranes that enable programmable ion transport in the context of neuromorphic computing. Recent advances in the fabrication of epitaxially connected semiconducting quantum dot mesocrystal membranes present as a unique opportunity to explore this bold vision.
This project integrates the complementary areas of expertise of Tobias Hanrath, the Marjorie L. Hart ’50 Professor in Engineering in the Smith School of Chemical and Biomolecular Engineering, and Yu Zhong, assistant professor in the Department of Materials Science and Engineering.
3D-printed concrete walls for enhanced protection of shorelines against sea level rise
With nearly 10% of the world population living in areas less than 10 meters above sea level, the protection of shorelines against flooding and erosion is of paramount importance in coastal communities. Furthermore, the increased frequency of extreme weather events caused by climate change presents a looming risk in these areas.
This overarching goal of this work proposed by Sriramya Nair, assistant professor in the School of Civil and Environmental Engineering; Maha Haji, assistant professor in the Sibley School of Mechanical and Aerospace Engineering and the Systems Engineering Program; Todd Cowen, professor in the School of Civil and Environmental Engineering; and Sasa Zivkovic, assistant professor in the Department of Architecture in the College of Architecture, Art, and Planning, is to investigate the potential of additively constructed or 3D printed low-CO2e green concrete for developing resilient infrastructure to be adaptive to changing climate, specifically due to sea level rise.
Collective comb building in constrained geometries
Nature is rich with examples of swarms coordinating to create large complex adaptive structures – bacteria forming biofilms, termites building towering mounds, mole-rats building underground cities to name a few. While it is generally accepted that stigmergy, the process of indirect coordination via environmental modifications, plays a vital role in these systems, we lack an understanding of the extent of local cues required to build highly functional, adaptive structures.
This project, led by Nils Napp, assistant professor in the School of Electrical and Computer Engineering, and Kirstin Petersen, associate professor in the School of Electrical and Computer Engineering, will investigate comb-building in honeybees. Unlike other social insects, honeybees construct regular hexagonal lattices in the absence of obstacles, which make them an ideal model system where the base-line behavior before adaptation is known. The team will investigate how random – but biased – modifications of the structure can lead to these highly optimized combs.
The road to optical semiconductor devices travels through chiral polaritons
The interaction between light and matter is familiar through fundamental processes such as absorption and stimulated emission. It is typically assumed that the oscillating electromagnetic field doesn’t significantly alter the states of the atoms involved – in other words, that they are weakly coupled. But in certain materials, the interaction is strong enough that this assumption breaks down. In these cases, the mixture of the photon and matter components form hybrid states known as “polaritons” with properties from unique both light and matter.
One of the objects of this research, headed by Richard Robinson, associate professor in the Department of Materials Science and Engineering, and Andrew Musser, assistant professor in the Department of Chemistry and Chemical Biology, is to understand the photophysics of quantum dot polaritons. These polaritons could provide optimal conditions for photon-to-matter quantum transduction and hold promise for next-generation applications such as chiral lasing.