Beta-testers

  • Olaia Anton, Zakarya Benayad, Miguel de la Puente, Axel Gomez
  • Oscar Gayraud, Pierre Girard, Anne Milet
  • Meritxell Malagarriga Perez, Adrián García
  • Ashley Borkowski, Pauf Neupane, Ward Thompson
  • Hadi Dinpajooh

Atomsk

VMD

DeePMD-kit

  • Zeng, J.; Zhang, D.; Lu, D.; Mo, P.; Li, Z.; Chen, Y.; Rynik, M.; Huang, L.; Li, Z.; Shi, S.; Wang, Y.; Ye, H.; Tuo, P.; Yang, J.; Ding, Y.; Li, Y.; Tisi, D.; Zeng, Q.; Bao, H.; Xia, Y.; Huang, J.; Muraoka, K.; Wang, Y.; Chang, J.; Yuan, F.; Bore, S. L.; Cai, C.; Lin, Y.; Wang, B.; Xu, J.; Zhu, J.-X.; Luo, C.; Zhang, Y.; Goodall, R. E. A.; Liang, W.; Singh, A. K.; Yao, S.; Zhang, J.; Wentzcovitch, R.; Han, J.; Liu, J.; Jia, W.; York, D. M.; E, W.; Car, R.; Zhang, L.; Wang, H. DeePMD-Kit v2: A Software Package for Deep Potential Models. J. Chem. Phys. 2023, 159 (5), 054801. https://doi.org/10.1103/PhysRevMaterials.3.023804.
  • Wang, H.; Zhang, L.; Han, J.; E, W. DeePMD-Kit: A Deep Learning Package for Many-Body Potential Energy Representation and Molecular Dynamics. Comput. Phys. Commun. 2018, 228, 178–184. https://doi.org/10.1016/j.cpc.2018.03.016.

DP-Compress

  • Lu, D.; Jiang, W.; Chen, Y.; Zhang, L.; Jia, W.; Wang, H.; Chen, M. DP Compress: A Model Compression Scheme for Generating Efficient Deep Potential Models. J. Chem. Theory Comput. 2022, 18 (9), 5559–5567. https://doi.org/10.1021/acs.jctc.2c00102.

Concurrent Learning

  • Zhang, L.; Lin, D.-Y.; Wang, H.; Car, R.; E, W. Active Learning of Uniformly Accurate Interatomic Potentials for Materials Simulation. Phys. Rev. Materials 2019, 3 (2), 023804. https://doi.org/10.1103/PhysRevMaterials.3.023804
  • Zhang, Y.; Wang, H.; Chen, W.; Zeng, J.; Zhang, L.; Wang, H.; E, W. DP-GEN: A Concurrent Learning Platform for the Generation of Reliable Deep Learning Based Potential Energy Models. Comput. Phys. Commun. 2020, 253, 107206. https://doi.org/10.1016/j.cpc.2020.107206.

LAMMPS

  • Thompson, A. P.; Aktulga, H. M.; Berger, R.; Bolintineanu, D. S.; Brown, W. M.; Crozier, P. S.; In ’T Veld, P. J.; Kohlmeyer, A.; Moore, S. G.; Nguyen, T. D.; Shan, R.; Stevens, M. J.; Tranchida, J.; Trott, C.; Plimpton, S. J. LAMMPS - a Flexible Simulation Tool for Particle-Based Materials Modeling at the Atomic, Meso, and Continuum Scales. Comput. Phys. Commun. 2022, 271, 108171. https://doi.org/10.1016/j.cpc.2021.108171.

i-PI

  • Kapil, V.; Rossi, M.; Marsalek, O.; Petraglia, R.; Litman, Y.; Spura, T.; Cheng, B.; Cuzzocrea, A.; Meißner, R. H.; Wilkins, D. M.; Helfrecht, B. A.; Juda, P.; Bienvenue, S. P.; Fang, W.; Kessler, J.; Poltavsky, I.; Vandenbrande, S.; Wieme, J.; Corminboeuf, C.; Kühne, T. D.; Manolopoulos, D. E.; Markland, T. E.; Richardson, J. O.; Tkatchenko, A.; Tribello, G. A.; Van Speybroeck, V.; Ceriotti, M. I-PI 2.0: A Universal Force Engine for Advanced Molecular Simulations. Comput. Phys. Commun. 2019, 236, 214–223. https://doi.org/10.1016/j.cpc.2018.09.020.

CP2K

  • Kühne, T. D.; Iannuzzi, M.; Del Ben, M.; Rybkin, V. V.; Seewald, P.; Stein, F.; Laino, T.; Khaliullin, R. Z.; Schütt, O.; Schiffmann, F.; Golze, D.; Wilhelm, J.; Chulkov, S.; Bani-Hashemian, M. H.; Weber, V.; Borštnik, U.; Taillefumier, M.; Jakobovits, A. S.; Lazzaro, A.; Pabst, H.; Müller, T.; Schade, R.; Guidon, M.; Andermatt, S.; Holmberg, N.; Schenter, G. K.; Hehn, A.; Bussy, A.; Belleflamme, F.; Tabacchi, G.; Glöß, A.; Lass, M.; Bethune, I.; Mundy, C. J.; Plessl, C.; Watkins, M.; VandeVondele, J.; Krack, M.; Hutter, J. CP2K: An Electronic Structure and Molecular Dynamics Software Package - Quickstep: Efficient and Accurate Electronic Structure Calculations. J. Chem. Phys. 2020, 152 (19), 194103. https://doi.org/10.1063/5.0007045.