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Peer-reviewedCC BY 4.0Molecules

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

  • Keda Yang1
  • Longkun Du2
  • Zirui Lv2
  • Wangshi Ning2
  • Jun Li2
  • Qiongyan Shao1
  • Jie Qu1
  • Lihui Hong1
  • Teng Lu3
  • Xiaoling Xu1
  • Denghui Li2
  1. 1Key Laboratory of Artificial Organs and Computational Medicine of Zhejiang Province, Shulan International Medical College, Zhejiang Shuren University, Hangzhou 310015, China
  2. 2State Key Laboratory of Chemistry for NBC Hazards Protection, Beijing 102205, China
  3. 3Computer Network Information Center, Chinese Academy of Sciences, Beijing 100190, China
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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.

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Cite

BibTeXRIS
BibTeX
@article{yang2026mesoscreen,
  title = {{MesoScreen: A Computational Platform Providing Unified Data for Liquid-Crystal Research}},
  author = {Keda Yang and Longkun Du and Zirui Lv and Wangshi Ning and Jun Li and Qiongyan Shao and Jie Qu and Lihui Hong and Teng Lu and Xiaoling Xu and Denghui Li},
  journal = {Molecules},
  year = {2026},
  month = oct,
  doi = {10.3390/molecules31203602},
  url = {https://www.mdpi.com/1420-3049/31/20/3602},
  note = {CC BY 4.0},
}
RIS
TY  - JOUR
TI  - MesoScreen: A Computational Platform Providing Unified Data for Liquid-Crystal Research
AU  - Keda Yang
AU  - Longkun Du
AU  - Zirui Lv
AU  - Wangshi Ning
AU  - Jun Li
AU  - Qiongyan Shao
AU  - Jie Qu
AU  - Lihui Hong
AU  - Teng Lu
AU  - Xiaoling Xu
AU  - Denghui Li
PY  - 2026
DA  - 2026/10/01
JO  - Molecules
DO  - 10.3390/molecules31203602
UR  - https://www.mdpi.com/1420-3049/31/20/3602
AB  - 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.
SN  - 1420-3049
ER  -