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Ira A. Fulton Schools of Engineering
Hong Research Group
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  • Materials Properties Prediction (MAPP)
    • Overview
    • MAPP Consortium Model
    • Melting Temperature
    • Formation Energy Model
    • Band Gap Predictor
    • Bulk Modulus Predictor Version 2
    • Volume predictor
    • CALPHAD Excess Parameter L(A,B;0)
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MAPP Consortium Model

Consortium, an ensemble of 30 GNN models, accepts up to 4 elements

Try La_2Zr_2O_7, or La_2O_3(ZrO_2)_2, or ZrO_2, or HfC_0.93, or Ni_10Fe_72Cr_18
MAPP-scal

Cite this model:

Si-Da Xue and Qi-Jun Hong, Materials Properties Prediction (MAPP): Empowering the Prediction of Material Properties Solely Based on Chemical Formulas, Materials, 2024. 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.

About this model

This model is based on Graph Neural Network (GNN) and Residual Neural Network (ResNet).
This ensemble model is based on bootstrap aggregating (bagging).

Video Introduction

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