The Inorganic Crystal Structure Database (ICSD)—Present and Future

By M. Hellenbrandt. 2004

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A universal graph deep learning interatomic potential for the periodic table (2022, methodology): “…Materials Project performs a sequence of two relaxation calculations 19 with the PBE 43 generalized gradient approximation (GGA) functional or the GGA + U method 44 for every unique input crystal, typically obtained from an experimental database such as the Inorganic Crystal Structure Database 45 .”
Recent advances and applications of deep learning methods in materials science (2021, methodology): “[199] calculated 150000 XRD patterns from the Inorganic Crystal Structure Database (ICSD) structural database [200] and then used CNN models to predict structural information from the simulated XRD patterns.”
Metrological characterization of X-ray diffraction methods at different acquisition geometries for determination of crystallite size in nano-scale materials (2013, background): “for example, from the Inorganic Crystal Structure Database [40].”
Scaling deep learning for materials discovery (2023, methodology): “In the main part of this paper, we refer to experimentally validated crystal structures with the ICSD.”