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University of Virginia School of Engineering and Applied Science


Collaborations inspired early-career NIH grant that could lead to treatment breakthroughs for a range of medical conditions

A University of Virginia researcher has received a $1.8 million NIH grant to develop polymers that can deliver peptides as medicine, overcoming limitations such as short duration and toxicity. The project aims to create new therapeutic formulations using polymer biomaterials, which have endless design possibilities.

UVA researchers harness the power of a new solid-state thermal technology

Researchers at UVA School of Engineering and Applied Science have discovered a way to make a versatile thermal conductor that can be controlled on demand. This advancement has promise for managing heating and cooling in electronic devices, green buildings and space exploration, with potential applications including the Mars Rover.

SourceUniversity of Virginia School of Engineering and Applied Science·JournalNature Communications·TypeExperimental study·DateJun 21, 2022

New technology could help doctors improve COVID-19 patient outcomes

Researchers at the University of Tokyo and University of Virginia developed a new diagnostic technology that can identify patients at risk of microvascular thrombosis. The technology analyzes blood samples to detect excessive platelet aggregation, an early indicator of blood clotting, in nearly 90% of COVID-19 patients.

SourceUniversity of Virginia School of Engineering and Applied Science·JournalNature Communications·TypeExperimental study·DateDec 13, 2021

UVA research group opens a path toward quantum computing in real-world conditions

A UVA research group has developed a scalable quantum computing platform using photonic devices, reducing the number of devices needed to achieve quantum speed. The team created a quantum source in an optical microresonator on a chip, generating 40 qumodes and verifying the generation of multiplexed quantum modes.

SourceUniversity of Virginia School of Engineering and Applied Science·JournalNature Communications·TypeExperimental study·DateAug 20, 2021

UVA materials science engineers strive to reduce emissions from aircraft engines

Researchers created a duplex bond coat approach that extends the life of engine components, protecting them from chemical reactions and water vapor. The new coating system uses ytterbium disilicate and hafnium oxide to create a stable and durable barrier against high temperatures.

SourceUniversity of Virginia School of Engineering and Applied Science·JournalActa Materialia·TypeExperimental study·DateAug 12, 2021

A robotic fish tail and an elegant math ratio could inform the design of next- generation underwater drones

University of Virginia researchers design a simple way to implement a tunable stiffness strategy in robots, enabling efficient swimming at varying speeds. The approach, inspired by the natural adaptability of fish, uses a programmable artificial tendon to adjust tail stiffness in real-time.

SourceUniversity of Virginia School of Engineering and Applied Science·JournalScience Robotics·TypeExperimental study·DateAug 11, 2021

A better informed society can prevent lead poisoning disasters

Researchers suggest using scientific data and predictive frameworks to identify risks of lead release, improving testing strategies and anticipating problems. Citizen scientists can aid in data gathering with mobile test kits, while AI and machine learning help identify relationships between water conditions and lead levels.

SourceUniversity of Virginia School of Engineering and Applied Science·JournalProceedings of the National Academy of Sciences·DateSep 18, 2020

UVA engineering-led team unveils 'Tunabot,' first robotic fish to keep pace with a tuna

Researchers developed Tunabot to better understand fish propulsion, which could lead to faster, more efficient propulsion systems for underwater vehicles. The robot's design was informed by studies of yellowfin tuna and mackerel, and its performance data sets a high standard for the field of fish robotics.

UVA scientists use machine learning to improve gut disease diagnosis

Researchers at UVA are using machine learning algorithms on biopsy images to diagnose environmental enteric dysfunction, a disease that affects hundreds of thousands of children worldwide. The technology has the potential to provide insights that evade human eyes, validate pathologists' diagnoses and shorten treatment times.