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Journal of Chemical Theory and Computation
|
June 10, 2024
Seebeck Coefficient of Ionic Conductors from Bayesian Regression Analysis
Enrico Drigo, Stefano Baroni, Paolo Pegolo
The Journal of Chemical Physics
|
September 7, 2023
Self-interaction and transport of solvated electrons in molten salts
Paolo Pegolo, Stefano Baroni, Federico Grasselli
The Journal of Chemical Physics
|
February 13, 2025
Transport coefficients from equilibrium molecular dynamics
Paolo Pegolo, Enrico Drigo, Federico Grasselli, et al.
Journal of Chemical Theory and Computation
|
June 25, 2025
Exploring the Design Space of Machine Learning Models for Quantum Chemistry with a Fully Differentiable Framework
Divya Suman, Jigyasa Nigam, Sandra Saade, et al.
Nature Communications
|
November 27, 2025
PET-MAD as a lightweight universal interatomic potential for advanced materials modeling
Arslan Mazitov, Filippo Bigi, Matthias Kellner, et al.
The Journal of Chemical Physics
|
February 11, 2026
metatensor and metatomic: Foundational libraries for interoperable atomistic machine learning
Filippo Bigi, Joseph W Abbott, Philip Loche, et al.
Digital Discovery
|
June 17, 2026
Journal research data policies in materials science
Lukas Hörmann, Hemanadhan Myneni, Rwayda Kh S Al-Hamd, et al.
Page
of 1
Search research articles
Search
Showing results (1-10 of 7) with videos related to
Sort By:
Page
of 1
Journal of Chemical Theory and Computation
|
June 10, 2024
Seebeck Coefficient of Ionic Conductors from Bayesian Regression Analysis
Enrico Drigo, Stefano Baroni, Paolo Pegolo
The Journal of Chemical Physics
|
September 7, 2023
Self-interaction and transport of solvated electrons in molten salts
Paolo Pegolo, Stefano Baroni, Federico Grasselli
The Journal of Chemical Physics
|
February 13, 2025
Transport coefficients from equilibrium molecular dynamics
Paolo Pegolo, Enrico Drigo, Federico Grasselli, et al.
Journal of Chemical Theory and Computation
|
June 25, 2025
Exploring the Design Space of Machine Learning Models for Quantum Chemistry with a Fully Differentiable Framework
Divya Suman, Jigyasa Nigam, Sandra Saade, et al.
Nature Communications
|
November 27, 2025
PET-MAD as a lightweight universal interatomic potential for advanced materials modeling
Arslan Mazitov, Filippo Bigi, Matthias Kellner, et al.
The Journal of Chemical Physics
|
February 11, 2026
metatensor and metatomic: Foundational libraries for interoperable atomistic machine learning
Filippo Bigi, Joseph W Abbott, Philip Loche, et al.
Digital Discovery
|
June 17, 2026
Journal research data policies in materials science
Lukas Hörmann, Hemanadhan Myneni, Rwayda Kh S Al-Hamd, et al.
Page
of 1