Publications using pyscal

• Laurens, Gaétan, Jacek Goniakowski, and Julien Lam. “Non-Classical Nucleation of Zinc Oxide from a Physically-Motivated Machine-Learning Approach.” ArXiv:2108.10601 [Cond-Mat, Physics:Physics], August 24, 2021.

• Menon, Sarath, Yury Lysogorskiy, Jutta Rogal, and Ralf Drautz. “Automated Free Energy Calculation from Atomistic Simulations.” ArXiv:2107.08980 [Cond-Mat], July 19, 2021..

• Quentino, J. V., and P. A. F. P. Moreira. “Determining Neighborhood Phases in Hard-Sphere Systems Using Machine Learning.” The European Physical Journal B 94, no. 6 (June 2021): 130..

• Casillas-Trujillo, Luis, Ulf Jansson, Martin Sahlberg, Gustav Ek, Magnus M. Nygård, Magnus H. Sørby, Bjørn C. Hauback, Igor A. Abrikosov, and Björn Alling. “Interstitial Carbon in Bcc HfNbTiVZr High-Entropy Alloy from First Principles.” Physical Review Materials 4, no. 12 (December 2, 2020): 123601..

• Menon, Sarath, Grisell Díaz Leines, Ralf Drautz, and Jutta Rogal. “Role of Pre-Ordered Liquid in the Selection Mechanism of Crystal Polymorphs during Nucleation.” The Journal of Chemical Physics 153, no. 10 (September 14, 2020): 104508..

• Gao, Xueyun, Haiyan Wang, Lei Xing, Cainv Ma, and Huiping Ren. “Evolution of Local Atomic Structure during Solidification of Fe-RE (RE=La, Ce) Alloy.” Journal of Non-Crystalline Solids 542 (August 2020): 120109..

• Menon, Sarath, Grisell Leines, and Jutta Rogal. “Pyscal: A Python Module for Structural Analysis of Atomic Environments.” Journal of Open Source Software 4, no. 43 (November 1, 2019): 1824..