Chiral Intelligence: The Artificial Intelligence‐Driven Future of Chiroptical Properties

人工智能 认知科学 计算机科学 纳米技术 材料科学 心理学
作者
Rafael G. Uceda,Alfonso Gijón,Sandra Míguez‐Lago,Carlos M. Cruz,Luı́s Álvarez de Cienfuegos,Antonio J. Mota,D. Miguel,Juan M. Cuerva
出处
期刊:ChemPhotoChem [Wiley]
标识
DOI:10.1002/cptc.202500079
摘要

Chirality plays a fundamental role in molecular sciences, with chiroptical properties offering valuable insights into the interaction between chiral molecules and polarized light. Designing chiral materials with enhanced properties requires a deep understanding of underlying physical principles, often revealed only through large datasets. In this context, artificial intelligence (AI) emerges as a powerful tool for accelerating discovery and optimization, efficiently exploring vast chemical spaces. This work explores the synergy between AI and chiroptical properties, highlighting recent advances in data‐driven approaches for circular dichroism and circularly polarized luminescence. AI has demonstrated its ability to predict these phenomena accurately while uncovering structure–property relationships that can remain hidden under traditional methods. Various strategies are examined for integrating AI into chiroptical properties and the challenges and future directions of this field are discussed. In conclusion, combining chemical intuition with AI offers great potential for the rational design of next‐generation chiral materials. This integration not only promises to unlock novel compounds with enhanced chiroptical properties but also provides new opportunities to deepen our understanding of chiroptical phenomena.
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