2019/06/17 by Gianluca Prandini, Gian-Marco Rignanese, Nicola Marzari
Chemistry · Computer Science · Materials Science · Physics and Astronomy · #Binary number #Computer Graphics and Visualization Techniques #Machine Learning in Materials Science #Numerical models #Pigment Synthesis and Properties #Reflectivity #Rendering (computer graphics) #cond-mat.mtrl-sci
paper · pdf · doi:10.1038/s41524-019-0266-0
published as npj Computational Materials 5, 129 (2019)
arxiv created 2019/06/17 · openalex created_date 2019/06/27 · openalex publication_date 2019/12/20 · arxiv updated 2020/01/01 · openalex updated_date 2026/08/05
Abstract The colours of metals have attracted the attention of humanity since ancient times, and coloured metals, in particular gold compounds, have been employed for tools and objects symbolizing the aesthetics of power. In this work, we develop a comprehensive framework to obtain the reflectivity and colour of metals, and show that the trends in optical properties and the colours can be predicted by straightforward first-principles techniques based on standard approximations. We apply this to predict reflectivity and colour of several elemental metals and of different types of metallic compounds (intermetallics, solid solutions and heterogeneous alloys), considering mainly binary alloys based on noble metals. We validate the numerical approach through an extensive comparison with experimental data and the photorealistic rendering of known coloured metals.