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exercises:common:reading_list [2023/12/05 13:23] fnunesexercises:common:reading_list [2025/12/29 04:44] (current) – [Papers] jglan
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   * CPMD: Unified Approach for Molecular Dynamics and Density-Functional Theory, Roberto Car and Michele Parrinello (DOI: https://doi.org/10.1103/PhysRevLett.55.2471)   * CPMD: Unified Approach for Molecular Dynamics and Density-Functional Theory, Roberto Car and Michele Parrinello (DOI: https://doi.org/10.1103/PhysRevLett.55.2471)
  
-  * Metadynamics: Escaping free-energy minima, Alessandro Laio and Michele Parrinello (DOI: https://doi.org/10.1073/pnas.202427399)+  * MetadynamicsEscaping free-energy minima, Alessandro Laio and Michele Parrinello (DOI: https://doi.org/10.1073/pnas.202427399)
  
   * Real-time methods: Real-Time Time-Dependent Electronic Structure Theory, Xiaosong Li, Niranjan Govind, Christine Isborn, A. Eugene DePrince III, and Kenneth Lopata (DOI: https://doi.org/10.1021/acs.chemrev.0c00223); Real-time time-dependent electronic structure theory, Joshua J. Goings, Patrick J. Lestrange, and Xiaosong Li (DOI: https://doi.org/10.1002/wcms.1341)   * Real-time methods: Real-Time Time-Dependent Electronic Structure Theory, Xiaosong Li, Niranjan Govind, Christine Isborn, A. Eugene DePrince III, and Kenneth Lopata (DOI: https://doi.org/10.1021/acs.chemrev.0c00223); Real-time time-dependent electronic structure theory, Joshua J. Goings, Patrick J. Lestrange, and Xiaosong Li (DOI: https://doi.org/10.1002/wcms.1341)
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   * DeepMD: Deep Potential Molecular Dynamics: A Scalable Model with the Accuracy of Quantum Mechanics, Linfeng Zhang, Jiequn Han, Han Wang, Roberto Car, and Weinan E (DOI: https://doi.org/10.1103/PhysRevLett.120.143001)   * DeepMD: Deep Potential Molecular Dynamics: A Scalable Model with the Accuracy of Quantum Mechanics, Linfeng Zhang, Jiequn Han, Han Wang, Roberto Car, and Weinan E (DOI: https://doi.org/10.1103/PhysRevLett.120.143001)
  
 +  * MACE: A foundation model for atomistic materials chemistry, Ilyes Batatia et al. (DOI: https://doi.org/10.1063/5.0297006)
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 +  * E3NN: e3nn: Euclidean Neural Networks, Mario Geiger, Tess Smidt (DOI: https://arxiv.org/abs/2207.09453)
  
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