MOF-based nanosensor arrays for trace-level VOC detection: Advancing non-invasive health and environmental monitoring
TrAC - Trends in Analytical Chemistry, cilt.204, 2026 (SCI-Expanded, Scopus)
- Yayın Türü: Makale / Derleme
- Cilt numarası: 204
- Basım Tarihi: 2026
- Doi Numarası: 10.1016/j.trac.2026.119054
- Dergi Adı: TrAC - Trends in Analytical Chemistry
- Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Chemical Abstracts Core, Chimica, Compendex, EMBASE, DIALNET, Academic Search Ultimate (EBSCO), Engineering Source (EBSCO)
- Anahtar Kelimeler: Metal–organic frameworks, Nanosensor arrays, Non-invasive diagnostics and environmental monitoring, Volatile organic compounds
- Ankara Üniversitesi Adresli: Evet
Özet
Volatile organic compounds are important biomarkers for disease diagnosis and major environmental pollutants, creating a strong demand for sensitive, selective, and real-time sensing technologies. Although conventional techniques such as gas chromatography and mass spectrometry provide high analytical accuracy, their high cost, complex operation, and limited portability restrict practical applications. Metal–organic frameworks (MOFs) have emerged as promising nanosensing materials because of their ultrahigh porosity, tunable pore structures, large surface areas, and versatile surface chemistry, enabling efficient adsorption and selective detection of trace-level VOCs. This review summarizes recent advances in MOF-based nanosensor arrays for healthcare and environmental monitoring applications. Unlike previous reviews, this review focuses on MOF-based hybrid sensing platforms, sensor arrays, and machine-learning-assisted VOC detection. It connects MOF material design, array-based sensing, and intelligent data analysis for healthcare and environmental monitoring applications. Fundamental MOF properties, fabrication methods, surface functionalization strategies, and major sensing mechanisms including chemiresistive, electrochemical, optical, fluorescence, SERS, and QCM-based detection are discussed. Particular emphasis is placed on disease-related VOC biomarkers associated with lung cancer, diabetes, and liver disorders, together with environmentally hazardous VOCs. Emerging hybrid sensing platforms integrating MOFs with graphene, MXenes, noble metal nanoparticles, and ionic liquids are also highlighted. In addition, the growing role of artificial intelligence and machine learning in VOC pattern recognition and intelligent sensing systems is discussed. Finally, current challenges and future perspectives for wearable healthcare devices and next-generation environmental monitoring technologies are outlined.