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Flat Pasta Developed That Morphs Into Shape When Cooked - SciTechDaily

Flat Pasta Developed That Morphs Into Shape When Cooked - SciTechDaily

Flat Pasta Developed That Morphs Into Shape When Cooked - SciTechDaily
May 06, 2021 1 min, 40 secs

A research team led by the Morphing Matter Lab at Carnegie Mellon University is developing flat pasta that forms into familiar shapes when cooked.

The morphed pasta looks, feels and, most importantly, tastes like traditional pasta, while opening new possibilities for food design and allowing for flat-packed pasta that would cut back on packaging, save space in storage and transportation, and possibly reduce the time and energy needed for cooking.

“We were inspired by flat-packed furniture and how it saved space, made storage easier, and reduced the carbon footprint associated with transportation,” said Lining Yao, director of the Morphing Matter Lab in the Human-Computer Interaction Institute at CMU’s School of Computer Science.

“We decided to look at how the morphing matter technology we were developing in the lab could create flat-packed pastas that offered similar sustainability outcomes.”.

The team published their understanding of the morphing mechanism and design principles in the paper “Morphing Pasta and Beyond,” which is the cover story of the May 2021 issue of Science Advances.

“This could potentially be used in soft robotics and biomedical devices,” said Wen Wang, a former researcher affiliated with the Morphing Matter Lab.

Flat-packed pasta would cut back on the packaging required while saving space in shipping and storage.

Ye Tao, a former visiting postdoctoral researcher at the Morphing Matter Lab and the study’s lead author, tested the flat-packed pasta in the wild by packing it for a hiking trip.

The morphing pasta builds on years of research by Yao and the Morphing Matter Lab on morphing mechanisms and applications with different materials ranging from plastic and rubber to fabric and food.

Reference: “Morphing pasta and beyond” by Ye Tao, Yi-Chin Lee, Haolin Liu, Xiaoxiao Zhang, Jianxun Cui, Catherine Mondoa, Mahnoush Babaei, Jasio Santillan, Guanyun Wang, Danli Luo, Di Liu, Humphrey Yang, Youngwook Do, Lingyun Sun, Wen Wang, Teng Zhang and Lining Yao, 5 May 2021, Science Advances.

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