"title":"Materials genes of heterogeneous catalysis from clean experiments and artificial intelligence",
"description":"This tutorial explores the application of SISSO to a consistent experimental data set in order to identify the key parameters correlated with the catalyst selectivity in propane oxidation.",
"title":"Predicting the metal-insulator classification of elements and binary systems",
"description":"This tutorial shows how to find descriptive parameters (short formulas) for the classification of materials properties. As an example, we address the classification of elemental and binary systems Ax\u200b\u200bBy\u200b\u200b into metals and non metals using experimental data extracted from the SpringerMaterials data base. The method is based on the algorithm sure independence screening and sparsifying operator (SISSO), which enables to search for optimal descriptors by scanning huge feature spaces. ",
"title":"Proto- and Archetype Clustering-based SISSO",
"description":"In this tutorial two clustering methods, namely unsupervised k-means and supervised deep-aa, will be used to extract proto- and archetypes, respectively, along with corresponding clusters. The set of proto- or archetypes can be used as a substantially reduced training set for Single-Task SISSO, which outperforms random selection, while the corresponding clusters allow for an educated material2task-assignment of all training and test materials for Multi-Task SISSO, whose training on the whole training set outperforms corresponding training of Single-Task SISSO.",