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Applying machine learning to materials science
Rendering of 2D graphene molecules

Applying machine learning to materials science

Machine learning and artificial intelligence are applied to an increasing number of tasks, But using machine learning in materials science, which attempts to design and make materials for use in future technologies, has proven to be more difficult.

Penn Today Staff

Making complex 3-D surfaces with 2-D sheets
faces

Making complex 3-D surfaces with 2-D sheets

Using liquid crystal elastomer, researchers are able to transform 2-dimensional rubber-like sheets into malleable, three-dimensional shapes, with a precise amount of control for various shape sequences.

Ali Sundermier

Paving the way for safer smaller batteries and fuel cells
3d model

The researchers’ new structure self-assembles into hairpin shapes, resulting in acid-lined channels that allow for efficient transport of protons across the electrolyte.

Paving the way for safer smaller batteries and fuel cells

A new solid polymer electrolyte may be the key to making energy storage devices like lithium-ion and sodium-ion batteries more efficient.

Evan Lerner

An innovative approach to better energy storage
self assembly

Atomically thin nanosheets stand up to store more energy. Image credit: Ella Maru Studio

An innovative approach to better energy storage

A Penn/Drexel research team has engineered a way to manipulate nanomaterials to stand up vertically on a scale that has potential for industrial applications.

Ali Sundermier

Researchers show that cells’ perception of stiffness is a matter of time
Cell Stiffness

A cell can spread out more on a stiffer surface, making it easier for it to move, but the stiffness of its natural biological environment also changes in response. More realistic models of that interplay are necessary.

Researchers show that cells’ perception of stiffness is a matter of time

The relative stiffness of a cell’s environment is known to have a large effect on that cell’s behavior, including how well the cell can stick or move. Now, a new study by University of Pennsylvania researchers demonstrates the role timing plays in how cells perceive this stiffness.