MesoScreen: A Computational Platform Providing Unified Data for Liquid-Crystal Research

Abstract

The development of advanced liquid-crystal (LC) materials requires reliable and standardized structure–property data, yet generating such data through molecular simulation remains time-consuming and technically demanding. Here, we present MesoScreen, an online computational platform that converts SMILES-encoded molecular structures into standardized simulation workflows. Under consistent conditions, MesoScreen generates unified multi-property profiles including molecular polarizability, orientational order and phase, density, birefringence, and a director mean-square-displacement-based estimator of rotational viscosity. The platform was evaluated on 36 rod-like LC compounds. PCH5 at 313 K serves as a temperature- and phase-matched experimental anchor. Across three chemically distinct molecular cores, lateral substitution consistently reduces orientational order while leaving polarizability anisotropy relatively unchanged, leading to lower calculated birefringence within the Vuks framework. MesoScreen thus provides a scalable and reproducible framework for standardized LC property screening and cumulative dataset construction, supporting virtual screening and future data-driven materials research.