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Dartmouth Engineering Student Team Is NASA Competition Finalist
A team of engineering undergrads is a finalist in NASA's Revolutionary Aerospace Systems Concepts—Academic Linkage Competition to design innovations that could further human life and work on the Moon, Mars, and beyond.
Thayer Announces $5 Million Engineering Scholarship Gift
Endowed fund will support students who want to explore the full Dartmouth experience.
Dartmouth Engineering PhD Students Help Expand Generative AI Teaching Kit with NVIDIA
A collaboration between Dartmouth and the NVIDIA Deep Learning Institute, the kit has been expanded to include instructional videos by engineering PhD candidates Bruno Miranda Henrique and Anthony Ragazzi.
Dartmouth Engineering Study Presents Simple, Affordable Tool to Measure Tissue Oxygen and Health
The tool, developed in Professor Brian Pogue's lab, could provide a simple, affordable method far superior to blood oxygen measures for detecting disease and making treatment decisions.
Dartmouth Ranks Among Top 100 Universities for Patents
The National Academy of Inventors recognizes innovation by faculty and researchers, including professors Hui Fang and Margie Ackerman.
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Research Quick Takes
Mar 26, 2026
Custom Crystallization for Flexible Transparent Electronics
PhD students Samuel Ong and Simon Agnew '22, Md Saifur Rahman Th'25, and Professor Will Scheideler—with NIST physicist Lee Richter—co-authored "Tailoring Solid Phase Crystallization for Tunable Electronic Transport in Liquid Metal Printed 2D Oxides" published in Advanced Materials Technologies. The study showed highly-aligned, single-orientation grains which yield high-mobility devices, outperforming almost all other vacuum-free metal-oxide semiconductors reported to date. "We've always seen unique grain morphologies in our liquid metal printed metal oxides, so we probed the solid phase crystallization through highly-sensitive x-ray scattering techniques thanks to our collaborator, Dr. Richter. These results mark a critical step towards scalable manufacturing of transparent, high-performance electronics for next-generation flexible displays and sensors," said Ong.
Mar 26, 2026
Engineering Silk for the Bone-Tendon Interface
PhD candidates Amritha Anup (first-author, pictured) and Afton Limberg, Mika Bok '27, and Professor Katie Hixon co-authored "Silk cryogel and electrospun scaffold characterization for bone-tendon interface applications" published in Frontiers in Bioengineering and Biotechnology. In this work, tissue engineered silk cryogels and electrospun fibers were combined to model aspects of the mechanical, structural, and biochemical gradients found at the bone-tendon interface. "Injuries to the hard-soft tissue interfaces, such as the bone-tendon interface, affect approximately 32 million people in the US annually. Limitations in surgical repair and the natural healing process emphasizes the need for tissue engineering approaches that restore tissue continuity while supporting the spatial heterogeneity of the native bone-tendon insertion," said Anup.
Mar 26, 2026
Award for Alloys
Professor Ian Baker was awarded the Oleg D. Sherby Award at last week's annual meeting of The Minerals, Metals & Materials Society (TMS) in San Diego. The award was for "contributions to understanding the elevated temperature behavior and processing of metallic alloys as well as snow and ice using advanced characterization methods." "I very much appreciate receiving the Oleg Sherby Award from TMS in recognition of my work on elevated temperature mechanical properties. I joined TMS in 1983 and consider it a key institution for materials research both in the US and worldwide," said Baker.
Mar 19, 2026
Early Detection of Hidden Internal Bleeding
Professors Ryan Halter, Jonathan Elliott, Vikrant Vaze, and Ethan Murphy—with Geisel Professor Norman Paradis—were issued a US patent for "System and method to detect the presence and progression of diseases characterized by systemic changes in the state of the vasculature." The invention uses a novel technique to obtain multiple tissue measurements which are then "transformed by a multivariate algorithm to outputs that convey the diagnostic and prognostic risk of the disease of interest," according to the patent. "We show that by effectively combining signals from multiple sensors using advanced machine learning algorithms, we can save lives through early detection of hidden internal bleeding," said Vaze.
