In a Computational Materials Science article, scientists descrive a model combining phase-field modeling and machine learning, which was used to assess the importance of five parameters for grain coarsening of a polycrystalline material.
In an ACS Energy Letters paper, the authors summarize feedback from invited speakers at the Nanomaterials and Sustainability Workshop that was held on May 4, 2023, as part of the annual Advanced Photon Source/Center for Nanoscale Materials Users Meeting.
In a Journal of the American Chemical Society paper, scientists report a novel molten-salt cation exchange method with which to synthesize In1-ₓGaₓP quantum dot emitters with desirable optoelectronic traits.
In a npj Computational Materials paper, scientists report having developed a reinforcement learning-based model that captures the structure, energetics, density, equation of state, and elastic constants of silica polymorphs.
In a Journal of the American Chemical Society paper, scientists report that cyclic spacers offer more desirable properties compared to linear ones when designing 2D lead iodide perovskites with thermally-demanding optoelectronic applications.
In a Computational Materials Science paper, scientists describe an automated workflow, Elastemp, to predict the temperature dependence of the thermal expansion coefficients and elastic constants for materials.