In a Nature Communications article, a team led by Center for Nanoscale Materials researchers introduces a machine learning workflow of models for water transformations that increases accuracy at lower computational cost.
Using a single actuation signal, a frequency comb is generated in a micromechanical resonator from two vibrational modes, flexural and torsional, whose interactions are responsible for the unique response.
In a study published in Nano Letters, researchers experimentally show that excitations or defects carrying magnetic charge in artificial spin ices introduce a topological defect in incident coherent electron waves.
In a study published in Science, researchers’ findings enable a broad exploration of synthetic 2D polymer structures and properties. This work was a multidisciplinary team effort including DOE’s CNM and APS user facilities at Argonne.