Electromagnetic field‐charge transfer synergy boosted SERS in noble metal–semiconductor nanohybrids for environmental and bio‐detection

Abstract Noble metal–semiconductor nanohybrids synergistically integrate the merits of electromagnetic field and chemical enhancement mechanisms, endowing exceptional surface‐enhanced Raman scattering (SERS) performance through the electromagnetic field‐charge transfer synergy. This review systematically outlines recent advancements in the design and application of noble metal–semiconductor nanohybrid systems, emphasizing the distinct roles of diverse semiconductors in enhancing SERS activity and applications. Specifically, metal oxides contribute abundant oxygen vacancies for charge transfer, metal sulfides exhibit narrow band gaps to broaden light‐harvesting capacity, and metal–organic frameworks (MOFs) offer ultrahigh surface areas to enhance analyte adsorption. Through tailored interface engineering, semiconductor substrates enable band alignment to facilitate photo‐induced charge transfer (PICT), providing structural support to improve stability and supply uniform anchoring sites for the homogeneous dispersion of noble metal nanoparticles. Such advanced nanocomposites exhibit transformative potential in interdisciplinary fields, spanning fundamental molecular‐level interfacial studies to practical applications in environmental pollutant monitoring and ultrasensitive biosensing platforms. Especially in the field of bio‐detection, SERS provides a revolutionary tool for cell detection and real‐time diagnosis due to its ultrahigh sensitivity, molecular fingerprint characteristics, and multichannel detection advantages. With the development of nanotechnology and intelligence, SERS is expected to become an important technology for early detection and treatment monitoring of diseases. Furthermore, this review critically puts forward the future challenges in SERS technology, particularly selectivity and long‐term stability in complex environments, and proposes that integrating SERS with various techniques such as optical imaging, magnetic resonance imaging, and machine learning is the key to further promoting its development in bio‐detection.