4 papers
UNATE: UNsupervised ATomic Embedding for crystal structures property prediction
Laura Solà -Garcia, Ãlex Solé, Javier Ruiz-Hidalgo
Accurately predicting crystal properties is critical for accelerating materials discovery, but it is often limited by scarce labeled data and costly theoretical calculations. To al…
Machine Learning Multiscale Interactions
Ãlex Solé, Sergio Suárez-Dou, Albert Mosella-Montoro +4
Realistic physical systems are characterised by emergent interactions across multiple length and time scales, posing a significant challenge for predictive machine learning (ML) mo…
PRISM: Periodic Representation with multIscale and Similarity graph Modelling for enhanced crystal structure property prediction
Ãlex Solé, Albert Mosella-Montoro, Joan Cardona +4
Crystal structures are characterised by repeating atomic patterns within unit cells across three-dimensional space, posing unique challenges for graph-based representation learning…
A Cartesian Encoding Graph Neural Network for Crystal Structures Property Prediction: Application to Thermal Ellipsoid Estimation
Ãlex Solé, Albert Mosella-Montoro, Joan Cardona +4
In diffraction-based crystal structure analysis, thermal ellipsoids, quantified via Anisotropic Displacement Parameters (ADPs), are critical yet challenging to determine. ADPs capt…