Machine learning method accurately predicts metallic defects

For the first time, researchers at the Lawrence Berkeley National Laboratory (Berkeley Lab) have built and trained machine learning algorithms to predict defect behavior in certain intermetallic compounds with high accuracy. ...

Microscopy reveals 'atomic antenna' behavior in graphene

Atomic-level defects in graphene could be a path forward to smaller and faster electronic devices, according to a study led by researchers at the Department of Energy's Oak Ridge National Laboratory.

Imperfections may improve graphene sensors

Although they found that graphene makes very good chemical sensors, researchers at the University of Illinois at Urbana-Champaign have discovered an unexpected "twist"—that the sensors are better when the graphene is ...

Phosphorus a promising semiconductor

(Phys.org) —Defects damage the ideal properties of many two-dimensional materials, like carbon-based graphene. Phosphorus just shrugs.

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