Pushing the Frontiers: Artificial Intelligence (AI)‐Guided Programmable Concepts in Binary Self‐Assembly of Colloidal Nanoparticles - Cancan Li; Lindong Ma; Zhenjie Xue; Xiao Li; Shan Zhu; Tie Wang (Advanced Science, 2025)
Abstract Colloidal nanoparticle self‐assembly is a key area in nanomaterials science, renowned for its ability to design metamaterials with tailored functionalities through a bottom‐up approach. Over the past three decades, advancements in nanoparticle synthesis and assembly control methods have propelled the transition from single‐component to binary assemblies. While binary assembly has been recognized as a significant concept in materials design, its potential for intelligent and customized assembly has often been overlooked. It is argued that the future trend in the assembly of binary nanocrystalline superlattices (BNLSs) can be analogous to the ‘0s’ and ‘1s’ in computer programming, and customizing their assembly through precise control of these basic units could significantly expand their application scope. This review briefly recaps the developmental trajectory of nanoparticle assembly, tracing its evolution from simple single‐component assemblies to complex binary co‐assemblies and the unique property changes they induce. Of particular significance, this review explores the future prospects of binary co‐assembly, viewed through the lens of ‘AI‐guided programmable assembly’. Such an approach has the potential to shift the paradigm from passive assembly to active, intelligent design, leading to the creation of new materials with disruptive properties and functionalities and driving profound changes across multiple high‐tech fields.