Melting Temperature Predictor Version 2.1

ensemble of 30 GNN models, accepts up to 6 elements

Try La_2Zr_2O_7, or La_2O_3(ZrO_2)_2, or ZrO_2, or HfC_0.93

Cite this model:

Qi-Jun Hong, A melting temperature database and a neural network model for melting temperature prediction, arXiv, 2021. Download.

Qi-Jun Hong, Sergey V Ushakov, Axel van de Walle, and Alexandra Navrotsky, Melting temperature prediction using a graph neural network model: From ancient minerals to new materials, PNAS, 2022. Download.

This model is currently deployed on Microsoft Azure and the Research Computing facilities at ASU. Due to network limit, computation may take up to 10 seconds.

Metrics

R2 training score: 0.993

R2 testing score: 0.97

Root mean square error, training: 64K

Root mean square error, testing: 113K

What is new

Version 2.1: increase number of elements from 4 to 6. high entropy alloys!

Version 2: add uncertainty. ensemble of 30 deep learning models.

Version 1: melting temperature. GNN model.

About this model

This model is based on Graph Neural Network (GNN) and Residual Neural Network (ResNet).

Video Introduction