Quantum Graph Neural Network Models for Materials Search

Inspired by classical graph neural networks, we discuss a novel quantum graph neural network (QGNN) model to predict the chemical and physical properties of molecules and materials. QGNNs were investigated to predict the energy gap between the highest occupied and lowest unoccupied molecular orbital...

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Detalles Bibliográficos
Autores principales: Ryu, Ju-Young, Elala, Eyuel, Rhee, June-Koo Kevin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10304445/
https://www.ncbi.nlm.nih.gov/pubmed/37374486
http://dx.doi.org/10.3390/ma16124300

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10304445/
https://www.ncbi.nlm.nih.gov/pubmed/37374486
http://dx.doi.org/10.3390/ma16124300

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