SUrface enhanced Raman spectroscopy for PatHogen sensing and Anti-pathogenic Coating devElopment
The contamination of surfaces, medical equipment and devices, and air in sensitive areas poses significant risk to exposed individuals, in specific, those at compromised health, contributing to over 13.7 million deaths worldwide caused by infectious diseases in 2019. It is imperative to explore alternative approaches to combat the increasing resistance to commonly used broad-spectrum antibiotics. Consequently, there is a strong emphasis on the development of antimicrobial surfaces utilizing engineered nanomaterials. Pathogen detection technologies are complex, expensive and they have sensitivity limitations. It is essential to develop sensing technologies that overcome existing sensitivity limitations and enable rapid, on-site analysis in various environmental and clinical settings.
- Innovation Objectives
SURPHACE focuses on early stage, safe and sustainable development of innovative advanced materials (IAMs) for smart surfaces that exhibit sanitizing & sensing capacity to reduce the pathogenic load at several interfaces employing green & circular processes and data-driven strategies for function, safety, and sustainability optimization.
- Key Results & Applications
This technology could be applied in air filters & tangible surfaces avoiding respiratory disease transmission and can be combined with biosensing capabilities to help the monitoring of transmissive pathogens.
- Impact & Benefits
SURPHACE adopts Safe-and-Sustainable-by-Design guidance for the development of smart surfaces and pathogen-monitoring sensors by bridging experimental & computational technologies.These technologies will enhance infection control, reduce disease transmission, enable rapid detection, and support sustainable healthcare practices, leading to better health outcomes and economic benefits. Dedicated activities towards industry through their global early adopter network will help fully exploit its achievements.
The partners:
SURPHACE is funded via M-ERA.net, grant number 12319: 
