Genetic Algorithm-Accelerated Computational Discovery of Liquid Crystal Polymers with Enhanced Optical Properties
Note: We don't have the ability to review paper
PubDate: May 2025
Teams:Meta
Writers:Jianing Zhou, Yuge Huang, Arman Boromand, Keian Noori, Lafe Purvis, Chulwoo Oh,Lu Lu, Zachary W. Ulissi, Vahe Gharakhanyan, Xinyue Zhang
Abstract
virtual, augmented, and mixed reality (VR/AR/MR) technologies, serving as high-performance,
compact, lightweight, and cost-effective optical components. However, the growing demands for optical
transparency and high refractive index in advanced optical devices present a challenge for material
discovery. In this study, we develop a novel approach that integrates first-principles calculations with
genetic algorithms to accelerate the discovery of liquid crystal polymers with low visible absorption
and high refractive index. By iterating within a predefined space of molecular building blocks, our
approach rapidly identifies reactive mesogens that meet target specifications. Additionally, it provides
valuable insights into the relationships between molecular structure and properties. This strategy
not only accelerates material screening but also uncovers key molecular design principles, offering a
systematic and scalable alternative to traditional trial-and-error methods.
