DT
Davide Tisi
cond-mat.mtrl-sciphysics.chem-phcond-mat.dis-nncs.LGphysics.comp-phargyrodite solid electrolytecond-mat.softcond-mat.stat-mechinterfacial stabilityorganic coatings
On Valency
published · living versionsW_f6nx38av·v1 · currentpublished
Combining Simulations and Spectroscopy to Design Protective Coatings on Sulfide Solid Electrolytes
with Zhiyi Wang, Leonie Braks, Michele Ceriotti, Ali Coskun +1
1 version
Preprints & journals
16 papers in the corpus · 2021–2026Machine Learning Potentials for Electrified Interfaces10.26434/chemrxiv.15002895/v1 · Adem R. N. Aouichaoui, Davide Tisi, Ivano E. Castelli et al.2026 · 1 citationChemRxiv
Tracking the Lithiation State of LiSi from Machine-Learned XPS Binding Energies2602.23028v1 · Michael Alejandro Hernandez Bertran, Davide Tisi, Federico Grasselli et al.2026 · 0 citationsarXiv
Molecular Surface Engineering of Sulfide Electrolytes with Enhanced Humidity Tolerance for Robust Lithium Metal All-Solid-State Batteries.41399952 · Fadillah, Laras, Braks, Leonie, Oh, Jihoon et al.2026 · 24 citationsAdvanced materials (Deerfield Beach, Fla.). 2026;38(9):e15013
Comparing the latent features of universal machine-learning interatomic potentials2512.05717v3 · Sofiia Chorna, Davide Tisi, Cesare Malosso et al.2025 · 2 citationsarXiv
PET-MAD as a lightweight universal interatomic potential for advanced materials modeling.41309557 · Mazitov, Arslan, Bigi, Filippo, Kellner, Matthias et al.2026 · 59 citationsNature communications. 2025;16(1):10653
Metatensor and metatomic: foundational libraries for interoperable atomistic machine learning2508.15704v3 · Filippo Bigi, Joseph W. Abbott, Philip Loche et al.2025 · 10 citationsarXiv
Is there a future for 43Ca nuclear magnetic resonance in cement science?40231348 · Casar, Ziga, Tisi, Davide, Page, Samuel J et al.2025 · 4 citationsPhysical chemistry chemical physics : PCCP. 2025;27(17):9159-9168
Reconstructions and Dynamics of -Lithium Thiophosphate Surfaces2504.11553v1 · Hanna Turk, Davide Tisi, Michele Ceriotti2025 · 6 citationsPRX Energy 4(3), 033010 (2025)
PET-MAD, a lightweight universal interatomic potential for advanced materials modeling2503.14118v2 · Arslan Mazitov, Filippo Bigi, Matthias Kellner et al.2025 · 11 citationsarXiv
i-PI 3.0: A flexible and efficient framework for advanced atomistic simulations.39140447 · Litman, Yair, Kapil, Venkat, Feldman, Yotam M Y et al.2024 · 72 citationsThe Journal of chemical physics. 2024;161(6)
Mechanism of Charge Transport in Lithium Thiophosphate.38370276 · Gigli, Lorenzo, Tisi, Davide, Grasselli, Federico et al.2026 · 27 citationsChemistry of materials : a publication of the American Chemical Society. 2024;36(3):1482-1496
Thermal conductivity of LiPS solid electrolytes with ab initio accuracy2401.12936v3 · Davide Tisi, Federico Grasselli, Lorenzo Gigli et al.2024 · 18 citationsPhys. Rev. Materials 8 (2024) 065403
DeePMD-kit v2: A software package for deep potential models.37526163 · Zeng, Jinzhe, Zhang, Duo, Lu, Denghui et al.2024 · 619 citationsThe Journal of chemical physics. 2023;159(5)
Viscosity in water from first-principles and deep-neural-network simulations2203.01262v3 · Cesare Malosso, Linfeng Zhang, Roberto Car et al.2022 · 56 citationsnpj Comput Mater 8, 139 (2022)
Heat transport in liquid water from first-principles and deep-neural-network simulations2108.10850v3 · Davide Tisi, Linfeng Zhang, Riccardo Bertossa et al.2021 · 64 citationsPhys. Rev. B 104 (2021), 224202
QEHeat: An open-source energy flux calculator for the computation of heat-transport coefficients from first principles2104.06383v3 · Aris Marcolongo, Riccardo Bertossa, Davide Tisi et al.2021 · 11 citationsarXiv
Career total: 36 works. 16 are in this corpus.
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