Artificial Intelligence as the Next Visionary in Liquid Crystal Research

ABSTRACT Artificial intelligence (AI) is transforming the world of research with methods that condense months of empirical experiments into hours of computation and automation. Hence, applying AI in more specialized fields, namely liquid crystals (LCs) and liquid crystal polymers (LCPs), is of major interest to the scientific community. Therefore, in this perspective paper, we explore the use of AI in molecular and polymer property prediction and generative design, chemical reaction prediction, and synthesis route design; we will also review the use of AI to automate lab operations and analyze scientific literature. By dissecting the reviewed AI functions and inspecting their current limitations, such as hallucinations, we provide an outlook on the potential uses of AI for LC research, supplemented with a description of a fully automated LCP development process. We envision that AI‐driven assistants will facilitate the on‐demand design of LCs and LCPs for desired anisotropic responsive properties, accelerating both theoretical and application‐oriented research.

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Publication Details

Journal
Advanced Functional Materials
Published
2026-01-29
DOI
https://doi.org/10.1002/adfm.202529976
Primary Topic
Liquid Crystal Research Advancements
Type
article
Field-Weighted Citation Impact
0.00

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article

Artificial Intelligence as the Next Visionary in Liquid Crystal Research

Mert O. Astam, Danqing Liu, Ouassim L'Karkouri
Advanced Functional Materials
Liquid Crystal Research Advancements
article

Artificial Intelligence as the Next Visionary in Liquid Crystal Research

Mert O. Astam, Danqing Liu, Ouassim L'Karkouri
article en

Abstract

ABSTRACT Artificial intelligence (AI) is transforming the world of research with methods that condense months of empirical experiments into hours of computation and automation. Hence, applying AI in more specialized fields, namely liquid crystals (LCs) and liquid crystal polymers (LCPs), is of major interest to the scientific community. Therefore, in this perspective paper, we explore the use of AI in molecular and polymer property prediction and generative design, chemical reaction prediction, and synthesis route design; we will also review the use of AI to automate lab operations and analyze scientific literature. By dissecting the reviewed AI functions and inspecting their current limitations, such as hallucinations, we provide an outlook on the potential uses of AI for LC research, supplemented with a description of a fully automated LCP development process. We envision that AI‐driven assistants will facilitate the on‐demand design of LCs and LCPs for desired anisotropic responsive properties, accelerating both theoretical and application‐oriented research.

Advanced Functional Materials
NXP (Netherlands) (NL), Hiroshima International University (JP), Eindhoven University of Technology (NL)
Nederlandse Organisatie voor Wetenschappelijk Onderzoek
Industry, innovation and infrastructure
Openalex Percentile: Top 72%
Liquid Crystal Research Advancements
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