Botti, Silvana

1. Universal Machine Learning Interatomic Potentials are Ready for Phonons
   2024/12/21 by Antoine Loew, Loew, Antoine, Dewen Sun +8 · 1 voice · 37 citations
   Materials Science · #Machine Learning in Materials Science
2. Transfer learning on large datasets for the accurate prediction of material properties
   2023/03/06 by Noah Hoffmann, Jonathan Schmidt, Hoffmann, Noah +5 · 7 citations
   Materials Science · Computer Science · #Machine Learning in Materials Science #Computational Drug Discovery Methods #X-ray Diffraction in Crystallography
3. Large-scale machine-learning-assisted exploration of the whole materials space
   2022/10/02 by Schmidt, Jonathan, Hoffmann, Noah, Wang, Hai-Chen +5 · 6 citations
   #Computational Physics (physics.comp-ph) #FOS: Computer and information sciences #FOS: Physical sciences #Machine Learning (cs.LG) #Materials Science (cond-mat.mtrl-sci)
4. Ensemble averages of ab initio optical, transport, and thermoelectric properties of hexagonal Si_xGe_1-x alloys
   2022/05/25 by Pedro Borlido, Borlido, Pedro, F. Bechstedt +5 · 2 citations
   Physics and Astronomy · Engineering · Materials Science · #Semiconductor materials and interfaces #Chalcogenide Semiconductor Thin Films #Quantum Dots Synthesis And Properties
5. Validation of pseudopotential calculations for the electronic band gap of solids
   2020/03/23 by Borlido, Pedro, Doumont, Jan, Tran, Fabien +2 · 1 citation
   #Computational Physics (physics.comp-ph) #FOS: Physical sciences #Materials Science (cond-mat.mtrl-sci)
6. Generative AI for Crystal Structures: A Review
   2025/09/02 by Pierre-Paul De Breuck, De Breuck, Pierre-Paul, Hai‐Chen Wang +7 · 7 citations
   Chemical Engineering · Chemistry · Materials Science · #Catalysis and Oxidation Reactions #FOS: Physical sciences #Inorganic Chemistry and Materials #Machine Learning in Materials Science #Materials Science (cond-mat.mtrl-sci)
7. The Maximum T_c of Conventional Superconductors at Ambient Pressure
   2025/02/25 by Gao, Kun, Cerqueira, Tiago F. T., Sanna, Antonio +6 · 6 citations
   #FOS: Physical sciences #Superconductivity (cond-mat.supr-con)
8. From pseudo-direct hexagonal germanium to direct silicon-germanium alloys
   2021/05/05 by Borlido, Pedro, Suckert, Jens Renè, Furthmüller, Jürgen +3 · 1 citation
   #FOS: Physical sciences #Materials Science (cond-mat.mtrl-sci)
9. Prediction of high-Tc superconductivity in ternary actinium beryllium hydrides at low pressure
   2024/11/28 by Gao, Kun, Cui, Wenwen, Shi, Jingming +5 · 2 citations
   #FOS: Physical sciences #Superconductivity (cond-mat.supr-con)
10. Universal Machine Learning Potential for Systems with Reduced Dimensionality
    2025/08/21 by Giulio Benedini, Antoine Loew, Benedini, Giulio +8 · 1 voice · 3 citations
    Materials Science · Physics and Astronomy · #2D Materials and Applications #Machine Learning in Materials Science #Quantum many-body systems #cond-mat.mtrl-sci #physics.comp-ph
11. Enhanced superconductivity in X4H15compounds via hole-doping at ambient pressure
    2025/04/29 by Gao, Kun, Cui, Wenwen, Cerqueira, Tiago F. T. +3 · 2 citations
    #FOS: Physical sciences #Superconductivity (cond-mat.supr-con)
12. Real-time simulations of laser-induced electron excitations in crystalline ZnO
    2025/03/20 by Thomas Lettau, Chen, Xiao, Lettau, Thomas +5 · 2 citations
    Engineering · Materials Science · #Electron and X-Ray Spectroscopy Techniques #FOS: Physical sciences #Laser Material Processing Techniques #Laser-induced spectroscopy and plasma #Materials Science (cond-mat.mtrl-sci) #Optics (physics.optics)
13. AI-Driven Expansion and Application of the Alexandria Database
    2025/12/09 by Cavignac, Théo, Schmidt, Jonathan, De Breuck, Pierre-Paul +9 · 2 citations
    #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #FOS: Physical sciences #Materials Science (cond-mat.mtrl-sci)