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Intelligent Magnetic Nanomaterials: A Trinity Framework of Programmability; Field-Driven Actuation; and Data-Guided Intelligence
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DOI：10.1039/D5NR05291B.png)
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Abstract
En 中文
AbstratIntelligent magnetic nanomaterials (I-MNMs) represent a new generation of functional materials capable of sensing; learning; and adapting to dynamic environments. This work proposes a unified design framework that integrates structural programmability; field-driven actuation; and data-guided optimization to realize intelligent behavior in I-MNMs. By combining modular functional architectures with multi-field coupling; the study elucidates how programmable control of composition; morphology; and interfacial chemistry enables adaptive responses to magnetic; electric; or optical stimuli. Machine learning approaches are further introduced to map structure-performance relationships and achieve closed-loop optimization of dynamic functionality. The proposed framework bridges the gap between conventional material design and autonomous adaptability; paving the way for next-generation systems applicable to environmental remediation; catalysis; and biomedicine.
Keywords:
Intelligent magnetic nanomaterials
Programmability
Field-driven actuation
Data-guided optimization
Adaptive responses