Publications

Please write to the maintainers to suggest additions to the publications list.

Focus on ACE

  • Performant implementation of ACE in the PACE code

[Lysogorskiy21] Yury Lysogorskiy, Matteo Rinaldi, Sarath Menon, Cas van der Oord, Thomas Hammerschmidt, Matous Mrovec, Aidan Thompson, Gábor Csányi, Christoph Ortner, and Ralf Drautz, [Performant implementation of the atomic cluster expansion](https://doi.org/10.1038/s41524-021-00559-9), Npj Comput. Mater. 7, 97 (2021)

  • ACE for organic molecules

[Kovacs21] David Peter Kovacs, Cas van der Oord, Jiri Kucera, Alice Allen, Daniel Cole, Christoph Ortner, and Gabor Csanyi, [Linear Atomic Cluster Expansion Force Fields for Organic Molecules: beyond RMSE](https://doi.org/10.33774/chemrxiv-2021-7qlf5-v3), ChemRxiv (2021)

  • Three-body ACE with ridge regression

[Zeni21] Claudio Zeni, Kevin Rossi, Aldo Glielmo, and Stefano de Gironcoli, [Compact atomic descriptors enable accurate predictions via linear models](https://doi.org/10.1063/5.0052961), The Journal of Chemical Physics 154, 224112 (2021)

  • Rigorous mathematical and numerical analysis of ACE

[Dusson20] Geneviève Dusson, Markus Bachmayr, Gábor Csányi, Ralf Drautz, Simon Etter, Cas van der Oord, and Christoph Ortner, [Atomic Cluster Expansion: Completeness, Efficiency and Stability](https://arxiv.org/abs/1911.03550), arXiv (2020)

  • Equivariant ACE including additional degrees of freedom

[Drautz20] Ralf Drautz, [Atomic cluster expansion of scalar, vectorial, and tensorial properties including magnetism and charge transfer](https://doi.org/10.1103/PhysRevB.102.024104), Phys. Rev. B 102, 024104 (2020)

  • Development of the Atomic Cluster Expansion (ACE)

[Drautz19] Ralf Drautz, [Atomic cluster expansion for accurate and transferable interatomic potentials](https://doi.org/10.1103/PhysRevB.99.014104), Phys. Rev. B 99, 014104 (2019)

  • Atomic environment descriptor with close connection to ACE

[Uhrin21] Martin Uhrin, [Through the eyes of a descriptor: Constructing complete, invertible, descriptions of atomic environments](https://arxiv.org/abs/2104.09319), arXiv (2021)

  • Review machine learning for alloys

[Hart21] Gus L. W. Hart, Tim Mueller, Cormac Toher, and Stefano Curtarolo, [Machine learning for alloys](https://doi.org/10.1038/s41578-021-00340-w), Nature Review Materials 6, 730 (2021)

  • Free energy calculation with ACE

[Menon21] Sarath Menon, Yury Lysogorskiy, Jutta Rogal, and Ralf Drautz, [Automated free energy calculation from atomistic simulations](https://arxiv.org/abs/2107.08980), arXiv (2021)

  • Development of APIPs - Atomic body-ordered Permutation Invariant Polynomials

[Oord20] Cas van der Oord, Geneviève Dusson, Gábor Csányi, and Christoph Ortner, [Regularised atomic body-ordered permutation-invariant polynomials for the construction of interatomic potentials](https://doi.org/10.1088/2632-2153/ab527c), Mach. Learn.: Sci. Technol. 1 (2020)

  • Recursive evaluation of equivariant ACE basis functions

[Nigam20] Jigyasa Nigam, Sergey Pozdnyakov, and Michele Ceriotti, [Recursive evaluation and iterative contraction of N-body equivariant features](https://doi.org/10.1063/5.0021116), J. Chem. Phys. 53, 121101 (2020)

  • Analysis and comparison of different atomic environment representations

[Onat20] Berk Onat, Christoph Ortner, and James R. Kermode, [Sensitivity and dimensionality of atomic environment representations used for machine learning interatomic potentials](https://doi.org/10.1063/5.0016005), The Journal of Chemical Physics 153, 144106 (2020)

  • Linear machine learning potential with close relation to ACE

[Seko19] Atsuto Seko, Atsushi Togo, and Isao Tanaka, [Group-theoretical high-order rotational invariants for structural representations: Application to linearized machine learning interatomic potential](https://doi.org/10.1103/PhysRevB.99.214108), Phys. Rev. B 99, 214108 (2019)

  • Atomic density representations for machine learning

[Willatt19] Michael J. Willatt, Félix Musil, and Michele Ceriotti, [Atom-density representations for machine learning](https://doi.org/10.1063/1.5090481), The Journal of Chemical Physics 150, 154110 (2019)

  • Development of Moment Tensor Potentials (MTPs)

[Shapeev16] Alexander V. Shapeev, [Moment tensor potentials: a class of systematically improvable interatomic potentials](https://doi.org/10.1137/15M1054183), Mult. Model. Simul. 14, 1153--1173 (2016)

  • Development of Spectral Neighbor Analysis method Potential (SNAP)

[Thompson15] A.P. Thompson, L.P. Swiler, C.R. Trott, S.M. Foiles, and G.J. Tucker, [Spectral neighbor analysis method for automated generation of quantum-accurate interatomic potentials](https://doi.org/10.1016/j.jcp.2014.12.018), J. Comp. Phys. 285, 316--330 (2015)

  • Development of the Smooth Overlap of Atomic Positions (SOAP) descriptor

[Bartok13] Albert P. Bartók, Risi Kondor, and Gábor Csányi, [On representing chemical environments](https://doi.org/10.1103/PhysRevB.87.184115), Phys. Rev. B 87, 184115 (2013)

  • Cluster expansion for magnetic spins

[Drautz04] R. Drautz, and M. Fähnle, [Spin-cluster expansion: Parametrization of the general adiabatic magnetic energy surface with ab initio accuracy](https://doi.org/10.1103/PhysRevB.69.104404), Phys. Rev. B 69, 104404 (2004)

  • Cluster expansion for lattice occupation in alloys

[Sanchez84] J. M. Sanchez, F. Ducastelle, and D. Gratias, [Generalized Cluster Description of Multicomponent Systems](https://doi.org/0.1016/0378-4371(84)90096-7), Physica A 128, 334 (1984)

Last modified: June 16, 2022. Built with Franklin.jl. [Page source]