Pablo M. Piaggi

Princeton University — United States

Earth and Planetary Sciences · Physical Sciences

21h-index3.0kcitations72works4.12yr avg
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Research Topics

nanoparticles nucleation surface interactions(17), Machine Learning in Materials Science(14), Spectroscopy and Quantum Chemical Studies(13), Material Dynamics and Properties(11), Theoretical and Computational Physics(10)

Publications72 total

Data from "Hybrid ab initio and empirical machine learning models for the potential energy surface"
Zenodo (CERN European Organization for Nuclear Research)·2026Open Access
Water Phase Diagram from a General-Purpose Atomic Cluster Expansion Potential
arXiv (Cornell University)·2026Open Access
Water Phase Diagram from a General-Purpose Atomic Cluster Expansion Potential
ArXiv.org·2026Open Access
Water Phase Diagram from a General-Purpose Atomic Cluster Expansion Potential: Dataset
Zenodo (CERN European Organization for Nuclear Research)·2026Open Access
Water Phase Diagram from a General-Purpose Atomic Cluster Expansion Potential: Dataset
Zenodo (CERN European Organization for Nuclear Research)·2026Open Access
Data from "Ab initio machine-learning simulation of calcium carbonate from aqueous solutions to the solid state"
Zenodo (CERN European Organization for Nuclear Research)·2026Open Access
Assessment of First-Principles Methods in Modeling the Melting Properties of Water
ArXiv.org·2025Open Access
Ab Initio Melting Properties of Water and Ice from Machine Learning Potentials
ArXiv.org·2025Open Access
Assessment of First-Principles Methods in Modeling the Melting Properties of Water
arXiv (Cornell University)·2025Open Access
Ab Initio Melting Properties of Water and Ice from Machine Learning Potentials
arXiv (Cornell University)·2025Open Access
Molecular mechanism of heterogeneous ice nucleation in the atmosphere
ArXiv.org·2025Open Access
Coverage–Dependent Structural Evolution of CoBr <sub>2</sub> at the Au(111) Interface
Advanced Science·2025Open Access
Early stages of self-healing at tungsten grain boundaries from ab initio machine learning simulations
Communications Materials·2025· 2 citedOpen Access
Ab initio machine-learning simulation of calcium carbonate from aqueous solutions to the solid state
Proceedings of the National Academy of Sciences·2025· 4 citedOpen Access
Early Stages of Self-Healing at Tungsten Grain Boundaries from Ab Initio Machine Learning Simulations
arXiv (Cornell University)·2025Open Access
On the Possibility of Chiral Symmetry Breaking in Liquid Hydrogen Peroxide
The Journal of Physical Chemistry B·2025Open Access
PLUMED Tutorials: A collaborative, community-driven learning ecosystem
The Journal of Chemical Physics·2025· 24 citedOpen Access
PLUMED Tutorials: a collaborative, community-driven learning ecosystem
Research Portal (Queen's University Belfast)·2024· 2 citedOpen Access
Molecular-scale insights into the electrical double layer at oxide-electrolyte interfaces
Nature Communications·2024· 53 citedOpen Access
Advanced simulations with PLUMED: OPES and Machine Learning Collective Variables
arXiv (Cornell University)·2024· 8 citedOpen Access
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Frequent Co-authors

Michele Parrinello(21), Roberto Car(16), Pablo G. Debenedetti(11), Michele Invernizzi(6), Ómar Valsson(6), Athanassios Z. Panagiotopoulos(6), Thomas E. Gartner(5), Paolo Raiteri(4), Luigi Bonati(4), R. González-Arrabal(4), Annabella Selloni(4), Tarak Karmakar(4), Massimiliano Bonomi(3), Giovanni Bussi(3), Carlo Camilloni(3), Gareth A. Tribello(3), Mattia Bernetti(3), Riccardo Capelli(3), Michele Ceriotti(3), Davide Donadio(3)