Matt Davenport

2 months ago | phys.org | Matt Davenport

Anyone who's ever tried tiling a floor, a backsplash or even an arts-and-crafts project probably knows the emotional frustration of working with pieces whose shapes don't perfectly complement each other. It turns out, though, that some creatures may actually rely on similar mismatches to create geometric frustrations that result in complex natural structures with remarkable properties, such as protective shells and sturdy yet flexible bones.

Mar 10, 2025 | techxplore.com | Matt Davenport

Researchers from the University of Michigan are hoping their new study will inspire some Americans to rethink their relationship with laundry. Because, no matter how you spin it, clothes dryers use a lot of comparatively costly energy when air works for free. Household dryers in the U.S. consume about 3% of our residential energy budget, about six times that used by washing machines.

Feb 20, 2025 | copernical.com | Matt Davenport

U-M astronomy will lead its first satellite mission with NASA grantby Matt Davenport for UM NewsAnn Arbor, MI (SPX) Feb 20, 2025 The first space mission led by the University of Michigan Department of Astronomy is scheduled to launch in 2029 with the support of a NASA grant worth $10 million. The mission is called STARI-STarlight Acquisition and Reflection toward Interferometry-and will showcase the viability of a new technique for studying exoplanets, or planets outside of our solar system.

Feb 19, 2025 | phys.org | Matt Davenport

Humanity can farm more food from the seas to help feed the planet while shrinking mariculture's negative impacts on biodiversity, according to new research led by the University of Michigan. There is a catch, though: We need to be strategic about it. The findings are published in the journal Nature Ecology & Evolution.

Jan 24, 2025 | michigantoday.umich.edu | Matt Davenport

Date Written By Going analogIt’s easy to think that machine learning is a completely digital phenomenon, made possible by computers and algorithms that can mimic brain-like behaviors. Study: Training all-mechanical neural networks for task learning through in situ backpropagation (DOI:10.1038/s41467-024-54849-z)But the first machines were analog and now, a small but growing body of research is showing that mechanical systems are capable of learning, too.