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Bitcoin mining yields climate chaos, faculty tell NYS Assembly

Four Cornell faculty testified to the NYS Assembly Oct. 27 on how firing up once-shuttered carbon-based power plants – to process cryptocurrency – could pause environmental progress.

Students win NASA challenge grant with 3D-printed sensor

A team of Cornell students has won a grant from NASA’s University Student Research Challenge for a proposed sensor that can help 3D printers build better, more reliable products. To collect the prize, the team is now crowdfunding a cost-share required by NASA.

When bad makes good: Defects strengthen 3D-printed material

Cornell researchers found that by deliberately introducing more defects into a 3D-printed metal alloy, followed by a post-processing treatment, they could create a stronger, more ductile material.

NSF grant aims to optimize future cyberinfrastructure

Researchers at the Cornell University Center for Advanced Computing (CAC), Texas Tech University, and Indiana University are engaged in a $298,000 NSF-funded EAGER grant designed to optimize future cyberinfrastructure projects.

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Juno craft provides first 3D view of Jupiter’s deep storms

After gazing at Jupiter’s Great Red Spot and its cloudy realm, NASA’s Juno spacecraft has given humanity a 3D, turbulent sense of what lies far below its swirling surface.

Scientists bring efficiency to expanding offshore wind energy

Cornell research shows how to make offshore wind farms more efficient in the face of impending rapid expansion, as the U.S. Department of the Interior plans leasing federal waters.

2021 ADW-PAL Call for Nominations announcement

Cornell faculty members have until Monday, Dec. 6, to submit nominations of distinguished scholars in the areas of humanities and physical sciences for the A.D. White Professors-at-Large Program.

Around Cornell

New A&S program expands undergrad research opportunities

The Nexus Scholars program, funded by nearly $5 million in philanthropic support, will help undergraduates working on research projects with faculty members over the summer.

Machine learning predicts antibiotic resistance spread

Cornell researchers used machine learning to predict with near-perfect accuracy how genes are transferred between bacteria, an approach that could potentially be used to stop the spread of antibiotic resistance.