Education
Bachelor's degree in Physics University of Bologna — Bologna, Italy | 2018–2021 Dissertation: "Effects of ionizing radiation on hybrid perovskite single crystals." Final grade: 110/110 cum laude.
Master's degree in Physics University of Bologna — Bologna, Italy | 2021–2023 Dissertation: "Designing compounds for friction reduction: from software development to application in conjunction with experiments." Final grade: 110/110 cum laude.
Ph.D. student in Physics University of Bologna — Bologna, Italy | 2023–present Topic: Computational tribology studies related to the experimental activity at ARCNL.
Other Experiences
2022 — Summer School "Quantum sensing, information processing and computing" at University of Bologna. Consisted of 12h of lectures and seminars, along with 10h of project-oriented activities related to storytelling in science, including a final presentation.
2022 — MANO Winter Workshop and Spring Workshop University of Bologna. Included preparation of a scientific poster and a presentation, respectively, with two days of lectures and seminars given by professors of foreign universities.
2023 — Machine Learning Interatomic Potentials School (ML-IP 2023) Aalto University, Espoo, Finland. Focused on current state-of-the-art methods for generating accurate interatomic potentials for atomistic molecular dynamics simulations.
2024 — Machine Learning Modalities for Materials Science Workshop Jožef Stefan Institute, Ljubljana, Slovenia. Focused on improving research in computational and experimental material science with machine learning methods, from large language models to machine learning potentials.
2023–2024 — Educational Tutor Computational laboratory of the bachelor course "Scienza dei Materiali 1" at University of Bologna.
2025 — European Solid Contact Mechanics Conference (ESMC 2025) Lyon, France. Presented the talk: "Synergistic effects of functionalized copolymers and doped DLC for friction and wear reduction."
Publications
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Pedretti E., Restuccia P., Righi M.C. (2023). Xsorb: a software for identifying the most stable adsorption configuration and energy of a molecule on a crystal surface. Computer Physics Communications, 108827. https://doi.org/10.1016/j.cpc.2023.108827
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Omiya T., Pedretti E., Evaristo M., Cavaleiro A., Serra A.C., Coelho J.F.J., Ferreira F., Righi M.C. (2024). Synergistic effects of nitrogen-containing functionalized copolymer and silicon-doped DLC for friction and wear reduction. Tribology International 200, 110183. https://doi.org/10.1016/j.triboint.2024.110183
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Omiya T., Pedretti E., et al. (2025). Elucidating the composition and formation mechanism of slippery films from block copolymers on doped diamond-like carbon surfaces. Applied Surface Science, 163599. https://doi.org/10.1016/j.apsusc.2025.163599
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Omiya T., Pedretti E., et al. (2025). Amine- and hydroxyl-functionalized copolymers as lubricant additives on Si-doped DLC: A comparative experimental and computational study of their tribological performance. Applied Surface Science, 164586. https://doi.org/10.1016/j.apsusc.2025.164586
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Benini F., Restuccia P., Pedretti E., Righi M.C. (2025). Ab Initio Insights into Zinc Dialkyldithiophosphate Linkage Isomers and Oxidative Degradation: Implications for Tribology. ACS Applied Nano Materials 8(28), 14103–14112. https://doi.org/10.1021/acsanm.5c01971
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Muthuperiyanayagam A., Pedretti E., Righi M.C., Di Tommaso D. (2025). Optimized selectivity in CO2 electrochemical reduction using amorphous CuNi catalysts: insights from density functional theory and machine learning simulations. Journal of Energy Chemistry. https://doi.org/10.1016/j.jechem.2025.08.089
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Leriche C., Pedretti E., Sahin O., Kang D., Righi M.C., Weber B. (2025). Passivation Species Suppress Atom-by-Atom Wear of Microcrystalline Diamond. ACS Applied Materials & Interfaces. https://doi.org/10.1021/acsami.5c08647
Knowledge & Skills
General Physics General knowledge of classical mechanics, thermodynamics, electromagnetism, nuclear and subnuclear physics, quantum mechanics, relativity, algebra and calculus, acquired during my Bachelor's degree in Physics at the University of Bologna.
Materials Physics Good knowledge of condensed matter physics, including semiconductor physics, charge transport and optical properties, magnetism and superconductivity, statistical mechanics, microscopic kinetics and thermodynamics, and in particular computational material physics (DFT calculations, machine learning interatomic potentials), acquired during the Material Physics and Nanoscience (MANO) Master course at the University of Bologna and expanded during my thesis and PhD program on ab initio computational tribology. Regarding DFT calculations, I have experience in calculating DOS, band structure, cohesive energy, surface and adsorption energy, activation energy of transitions (Nudged Elastic Band method), and molecular dynamics. For machine learning interatomic potentials, I am experienced in dataset generation, training, inference and molecular dynamics using various architectures (MACE, DeePMD, GRACE, NequIP, Allegro, SevenNet).
Software
- Quantum Espresso — Advanced (SCF calculations, structural optimizations, NEB, molecular dynamics)
- VASP — Intermediate (SCF calculations, structural optimizations)
- MACE and DeePMD MLIPs — Advanced
- LAMMPS — Advanced (MD simulations with machine learning force fields: MACE, DeePMD; and classical force fields: ReaxFF; for tribological systems)
- Ovito, XCrysden, VESTA, VMD, Avogadro — Experienced (atomic structure visualization and editing)
Programming
- Python — Intermediate
- C++ — Intermediate
- Bash — Intermediate
Office & Documentation
- Microsoft Office (Word, Excel, PowerPoint) — Intermediate
- LaTeX — Intermediate
Language Certificates
- Cambridge English Level 1 Certificate in ESOL International (First) — B2
