Computation and theory news, August 2020

New method predicts how 2D materials stack together

Researchers have developed a method for predicting the interaction between layers of 2D materials such as graphene in a stack.

Fins add speed to zeolite catalysts

Researchers have developed a way to induce large zeolite catalyst particles to behave like nanoparticles by growing fins on their surfaces.

Manganese improves sensitivity of 2D dopamine detector

Adding a small amount of manganese to 2D molybdenum disulfide improves its sensitivity as a dopamine detector by many orders of magnitude.

How does soft hair damage sharp steel blades?

By studying shaving with a scanning electron microscope, engineers have determined how a razor blade can be damaged as it cuts human hair.

Prof. Boccaccini marks 10 years as Editor-in-Chief of Materials Letters

Nanoreactor Strategy Generates Superior Supported Bimetallic Catalysts

Absorbing findings on how sorbent materials capture and release carbon

Researchers have determined exactly how some sorbent materials capture and release carbon dioxide from the atmosphere.

Elsevier and SPIE Launch New Book Series for the Photonics Community

We are excited to announce that Elsevier in collaboration with SPIE, titled Photonic Materials and Applications.

Electric shock turns fool’s gold magnetic

Researchers have electrically transformed the low-cost non-magnetic material iron sulfide, also known as ‘fool's gold’, into a magnetic material.

Temperature rises when superconductor layered with 2D material

Adding layers of the 2D material molybdenum sulfide to molybdenum carbide allows superconductivity to occur at 50% higher temperatures.

Snowflakes inspire effort to map 2D crystal shapes

Inspired by work on snowflakes, researchers are mapping the shapes of the 2D crystals produced by chemical vapor deposition under specific conditions.

Novel topological magnet exhibits quantum effects

Researchers have uncovered a new class of topological magnet exhibiting novel quantum effects that extend to room temperature.

Taking the trial-and-error out of crystal growth

systematic approach to growing 2D crystals using CVD based on large-scale databases and machine learning