DOI: 10.1002/adma.75219 ISSN: 0935-9648

From Phosphor Ceramics to Intelligent Light‐Conversion Materials: High‐Flux Luminescence, Glassy Composite Interface, and Machine‐Learning‐Guided Design

Xiaoqing Pei, Tao Pang, Lingwei Zeng, Daqin Chen

ABSTRACT

High‐power LED/LD and NIR applications demand phosphors that remain efficient and stable under high‐flux excitation, whereas conventional phosphor/organic systems are limited by heat buildup, interfacial degradation, and luminescence saturation. Phosphor ceramics provide a robust all‐inorganic alternative, but their photothermal coupling mechanisms and cross‐scale design principles remain insufficiently summarized. Here, we review recent advances in phosphor ceramics with a particular focus on photothermal coupling in high‐flux light conversion. We establish a composition‐structure‐photothermal behavior‐device performance framework that connects activator ions, host chemistry, defects and grain boundaries with light absorption, scattering regulation, thermal‐transport pathways, and device‐level output. Recent advances in garnet‐based, multiphase, multicolor visible, and NIR phosphor ceramics are discussed, with emphasis on compositional regulation, ceramic processing, microstructure engineering, and LED/LD integration. We clarify key relationships among transparency, absorption efficiency, scattering strength, thermal conductivity, interfacial thermal resistance, and luminescence saturation thresholds, which collectively determine high‐brightness reliability under extreme photon and heat loads. Emerging glassy composite interfaces are further highlighted for low‐temperature integration, heterogeneous packaging, and multimaterial coupling. Finally, we discuss machine learning as an enabling tool for candidate screening, processing‐window optimization, property prediction, and multi‐objective device design, offering guidance for next‐generation stable, intelligent light‐conversion materials.