Computation and theory news, June 2018

New double perovskites show potential for water splitting

Computer simulations have revealed that certain halide double perovskites could make effective photocatalysts for splitting water.

New iron-based cathode can triple energy density of lithium-ion batteries

A new cathode material comprising iron trifluoride nanorods with added cobalt and oxygen could triple the energy density of lithium-ion batteries.

Applied Materials Today achieves CiteScore of 9.9

Elsevier releases 2017 CiteScore values.

Chiral magnetism raises possibility of spintronics in amorphous materials

Scientists have confirmed a magnetic property known as ‘chirality’ in nanometer-thick samples of amorphous, multilayered metal-based materials.

New way to probe quantum properties of perovskite materials

Using novel analytical techniques, scientists have been able to study the behavior of excitons trapped in quantum wells made of perovskite compounds.

Elsevier 3D Printing Grand Challenge winners announced

Neural networks can be trained to design multi-layered nanoparticles

Neural networks can predict the light-scattering properties of layered nanoparticles and design nanoparticles for a desired light-scattering behavior.

Nanowires can make highly effective thermoelectric materials

Scientists have found that the most effective thermoelectric materials can be realized by shaping substances such as tin telluride into 1D nanowires.

Facial-recognition technology identifies material features

Scientists have trained a neural network to recognize features in a material's x-ray absorption spectrum that are sensitive to the arrangement of atoms.

Scientists develop blueprint for fabricating 2D heterostructures

Scientists have developed a blueprint for fabricating new heterostructures from different types of two-dimensional materials.

Listening to the health of granular materials

Scientists have shown they can predict the failure of granular materials such as gravel by monitoring naturally arising acoustic vibrations.

Model predicts impressive thermoelectric ability for topological material

Physicists have calculated that exposing a topological semimetal to a magnetic field could turn it into a highly efficient thermoelectric material.