Last week I showed you some results obtained with an Artificial Neural Network (ANN). The ANN classified the crystal compounds into perovskite or non-perovskite. The input data (features) fed to the ANN contained information about atomic radii, electronegativities, electronegativity differences and quotients of the atomic radii. All the features were constructed considering the number ofSigue leyendo «Modelling perovskite materials with ANNs beyond their composition: feature construction using their atomic arrangements.»
Archivo de categoría: Artificial Neural Networks
Symmetry-site based feature construction to characterize the crystal compounds. Part III.
I will explain some of the features used to characterize the crystal compounds into perovskite or non-perovskite structures. The constructed features were fed to different Artificial Neural Networks, which classify the crystal compounds in a binary fashion. These features are constructed using the different atom-environments in a crystal compound. These environments are known as WyckoffSigue leyendo «Symmetry-site based feature construction to characterize the crystal compounds. Part III.»
Symmetry-site based feature construction to characterize the crystal compounds. Part II.
Let me show you what you can find with the approach I told you in the last post. 1629 vertex-shared perovskite compounds were found in Crystallography Open Database (COD) (Figure 1). As I told you, all crystal structures (such as the perovskite structure) are defined by the occupation of certain Wyckoff sites. In the lastSigue leyendo «Symmetry-site based feature construction to characterize the crystal compounds. Part II.»
Symmetry-site based feature construction to characterize the crystal compounds. Part I.
My Ph. D. work was about the inference of new perovskite compounds with Artificial Intelligence and quantum chemical calculations. More concretely, I used Artificial Neural Networks (ANNs) to predict compounds having the perovskite crystal structure. The ANNs I worked with were full-connected and feed-forward (also known as multilayer perceptrons). The developed ANNs classified the crystalSigue leyendo «Symmetry-site based feature construction to characterize the crystal compounds. Part I.»
Artificial Intelligence in our life
Interview done at the Institute of Physics of National Autonomous University of Mexico (UNAM) during the Doors Open Day, on November 2019 (in spanish).
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