General application of the genetic algorithm to the estimation of the Liquid Crystal Director in PA-LC devices

Abstract

The study of liquid crystal (LC) director distribution is an important area of research in materials science and technology. Parallel-aligned liquid crystal (PA-LC) devices have been extensively studied due to their applications in liquid crystal displays, optical devices, and sensors. Estimating the LC director distribution is a critical step in designing and optimising PA-LC devices. This work shows the results derived from apply-ing novel optimisation techniques to estimate the liquid crystal (LC) director distribution in parallel-aligned liquid crystal (PA-LC) devices. Moreover, the genetic algorithm (GA) has been applied and compared with the minimisation of the Frank-Oseen free energy through the Euler-Lagrange equations. The GA is a stochastic optimisation technique that can effectively explore the search space and find the global optimum. Overall, this study’s results demonstrate the GA’s effectiveness in estimating the LC director distribution in PA-LC devices. This approach can improve the performance and design of liquid crystal displays, optical devices, and sensors. Furthermore, it can be extended to other fields where the optimisation of complex systems is required. Further research is needed to optimise the GA parameters and to explore its potential in other applications.