. 2021 May 10;6(20):13341–13364. doi: 10.1021/acsomega.1c01300

Table 1. Computational Cost of PSO Calculations as a Function of the Number of Components c and Maximum Possible Number of Phases in the Mixture of Interest^a.

c = 1

1.00

1.35

c = 2

1.79

2.72

3.66

c = 3

2.89

4.32

5.82

c = 4

3.63

5.42

7.50

Each entry indicates the average time it takes to perform a Gibbs-energy minimization for a given Inline graphic relative to the simplest case of . Each listed time is an average over 20 PSO runs carried out with a fixed number of N_p = 60 particles in the swarm. The case is not examined because it is forbidden by the Gibbs phase rule.^35−39,95

Table 1. Computational Cost of PSO Calculations as a Function of the Number of Components c and Maximum Possible Number of Phases in the Mixture of Interesta.

Table 1. Computational Cost of PSO Calculations as a Function of the Number of Components c and Maximum Possible Number of Phases in the Mixture of Interest^a.