@article {aSole26, title = {PRISM: periodic representation with multiscale and similarity graph modelling for enhanced crystal structure property prediction}, journal = {npj Computational Materials}, year = {2026}, month = {04/2026}, abstract = {

Crystal structures are characterised by repeating atomic patterns within unit cells across three-dimensional space, posing unique challenges for graph-based representation learning. Current methods often overlook essential periodic boundary conditions and multiscale interactions inherent to crystalline structures. In this paper, we introduce PRISM, a graph neural network framework that explicitly integrates multiscale representations and periodic feature encoding by employing a set of expert modules, each specialised in encoding distinct structural and chemical aspects of periodic systems. Extensive experiments across crystal structure-based benchmarks demonstrate that PRISM improves state-of-the-art predictive accuracy, significantly enhancing crystal property prediction. The project page can be found at: https://imatge-upc.github.io/PRISM/.

}, doi = {https://doi.org/10.1038/s41524-026-02074-1}, author = {Sol{\'e}, A. and Mosella-Montoro, Albert and Cardona, J. and Aravena, D. and G{\'o}mez-Coca, S. and Ruiz, E. and Ruiz-Hidalgo, J.} } @article {aSole25, title = {A Cartesian Encoding Graph Neural Network for Crystal Structures Property Prediction: Application to Thermal Ellipsoid Estimation}, journal = {Digital Discovery}, year = {2025}, month = {01/2025}, doi = {10.1039/D4DD00352G}, author = {Sol{\'e}, A. and Mosella-Montoro, Albert and Cardona, J. and G{\'o}mez-Coca, S. and Aravena, D. and Ruiz, E. and Ruiz-Hidalgo, J.} } @article {aCardona25, title = {Exploring Hyperfine Coupling in Molecular Qubits}, journal = {Chemical Science}, year = {2025}, month = {05/2025}, pages = {11291 - 11303}, abstract = {

Molecular qubits represent a promising avenue for advancing quantum sensing and computing technologies, yet significant challenges remain in optimising their performance. Hyperfine coupling has a critical influence on molecular qubit properties. While previous studies have exhaustively investigated this phenomenon, a comprehensive understanding of the underlying mechanisms across different systems remains elusive. A benchmark test was performed using DFT to assess which methodology worked best to accurately predict hyperfine coupling constants in molecular qubits predominantly composed of VIV and CuII. We systematically analysed the decomposition of hyperfine coupling and examined how variations in coordination sphere and molecular geometry impact dipolar, isotropic and spin-orbit contributions. By modelling diverse systems, we demonstrate how molecular design can fine-tune hyperfine coupling contributions, either minimising overall interaction or enhancing coupling along specific axes. This study provides useful insights into the structure-property relationships governing hyperfine coupling mechanisms and assesses the accuracy of different choices of density functional, basis sets and relativistic corrections in the prediction of hyperfine coupling constants.

}, doi = {https://doi.org/10.1039/D5SC02500A}, author = {Cardona, J. and Sol{\'e}, A. and Mella, P. and Aravena, D. and Ruiz-Hidalgo, J. and G{\'o}mez-Coca, S. and Ruiz, E.} }