Spectral Detection: Advancing Sensing Tools for Global Challenges
A special issue of Chemosensors (ISSN 2227-9040). This special issue belongs to the section "Analytical Methods, Instrumentation and Miniaturization".
Deadline for manuscript submissions: 15 April 2026 | Viewed by 12
Special Issue Editor
Special Issue Information
Dear Colleagues,
Spectral detection technologies are revolutionizing our ability to monitor and analyze complex chemical and biological systems with unparalleled precision. As global challenges such as environmental pollution, disease outbreaks, industrial safety, and food quality control escalate, there is an urgent need to advance sensing tools that offer real-time, non-invasive, and high-sensitivity detection capabilities. Innovations in spectral sensors—spanning ultraviolet–visible, infrared, Raman, fluorescence, and hyperspectral imaging—are paving the way for breakthroughs in early disease diagnosis, air/water contaminant tracking, hazardous material identification, and industrial process optimization.
This Special Issue focuses on cutting-edge advancements in spectral detection technologies, including novel sensor designs, miniaturized instrumentation, AI-driven spectral data processing, and multi-spectral fusion techniques. We welcome contributions addressing fundamental research, device engineering, and real-world applications, such as portable spectrometers for field analysis, wearable sensors for health monitoring, and satellite-based spectral systems for environmental surveillance. Submissions on interdisciplinary approaches integrating nanotechnology, machine learning, or IoT platforms to enhance spectral sensitivity, selectivity, and cost-efficiency are particularly encouraged. By showcasing the latest innovations in this field, we aim to foster collaboration between researchers and industries to accelerate the transition of spectral technologies from laboratories to global markets.
Dr. Renzhi Hu
Guest Editor
Manuscript Submission Information
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Keywords
- spectral detection technology
- sensors
- instruments
- real-time monitoring
- non-invasive detection
- portable spectrometers
- wearable sensors
- environmental surveillance
- early disease diagnosis
- machine learning
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