publications

2026

  1. damage.jpg
    Insights Into Radiation Damage in YBa_2Cu_3O_7-δ From Machine-Learned Interatomic Potentials
    Ashley Dickson, Niccolò Di Eugenio, Federico Ledda, Daniele Torsello, and 9 more authors
    Superconductivity, 2026
  2. dpa.jpg
    Beyond DPA: An Atomistic Framework for a Quantitative Description of Radiation Damage in YBa_2Cu_3O_7
    Federico Ledda, Daniele Torsello, Davide Gambino, Flyura Djurabekova, and 7 more authors
    Small Science, 2026
  3. diff.jpg
    The diffusion-driven orthorhombic to tetragonal transition in YBa_2Cu_3O_7 derived with a machine learning interatomic potential
    Davide Gambino, Niccolò Di Eugenio, Jesper Byggmästar, Johan Klarbring, and 3 more authors
    npj Quantum Materials, 2026
  4. spinodal.jpg
    A parametrically-Conditioned Deep Learning Surrogate for Coherent Spinodal Decomposition
    Andrea Fantasia, Daniele Lanzoni, Niccolò Di Eugenio, Angelo Monteleone, and 2 more authors
    Advanced Theory and Simulations, 2026

2025

  1. mlp.jpg
    Machine-Learned Interatomic Potentials for Structural and Defect Properties of YBa_2Cu_3O_7-δ
    Niccolò Di Eugenio, Ashley Dickson, Flyura Djurabekova, Francesco Laviano, and 8 more authors
    2025
  2. shield.jpg
    Systematic Monte Carlo Analysis of Binary Compounds for Neutron Shielding in a Compact Nuclear Fusion Reactor
    Fabio Calzavara, Niccolò Di Eugenio, Federico Ledda, Daniele Torsello, and 3 more authors
    Applied Sciences, 2025
  3. rad_env.jpg
    Radiation Environment and Damage of HTS Magnets in an ARC-Like Reactor
    Daniele Torsello, Federico Ledda, Simone Sparacio, Niccolò Di Eugenio, and 5 more authors
    IEEE Transactions on Applied Superconductivity, 2025