Thermodynamics of ionic materials (AFLOW-CCE)

Autonomous computational frameworks such as AFLOW are generating large databases that
power materials discovery workflows. The AFLOW.org repository is the largest of its kind,
containing more than 3 million compounds each characterized by 180+ different properties. The
data has been employed for the discovery of two magnets – the first discovered by computational
approaches – and six new high-entropy, high-hardness metal carbides. Join us for an online weeklong
hands-on workshop on AFLOW. Topics covered include database structure and generation,
structure prototypes and crystal symmetry, thermal and elastic properties analysis, thermodynamic
stability analysis, and integration of machine learning models for property prediction and
descriptor development.