Fig. 4: Exploring the performance and scalability of CASTING framework using an example metal polymorph.
From: A Continuous Action Space Tree search for INverse desiGn (CASTING) framework for materials discovery
a Comparison of the speed of convergence and difference in energy from the best available solution (Agfcc) between random sampling and MCTS optimizer for four atom system of Ag. b Performance of the MCTS optimizer (for different sizes of tree) for the problem in (a) as the area of the search space changes. c Effect of dimensionality on the predicted crystal structure for different system sizes. d Distribution energy difference (from fcc) (meV/atom) of the best solution obtained (in 20,000 iterations) for six independent trials on different sizes of the system with increasing lattice parameter bounds (δ) from a relaxed orthogonal supercell Ag (fcc). e Structural variation for the different minima obtained from the independent trials (as in (d)) in terms of changes in lattice parameters (from a relaxed orthogonal fcc supercell) and atomic stacking (difference from a pure fcc) for different sizes and lattice parameter bounds (δ).
