Affiliation:
1. School of Biomedical Engineering McMaster University 1280 Main Street West Hamilton ON L8S 4K1 Canada
2. Department of Chemical Engineering McMaster University 1280 Main Street West Hamilton ON L8S 4K1 Canada
3. Michael G. DeGroote Institute for Infectious Disease Research McMaster University 1280 Main Street West Hamilton ON L8S 4L7 Canada
Abstract
AbstractHealthcare textiles serve as key reservoirs for pathogen proliferation, demanding an urgent call for innovative interventions. Here, a new class of Smart Fabrics (SF) is introduced with integrated “Repel, Kill, and Detect” functionalities, achieved through a blend of hierarchically structured microparticles, modified nanoparticles, and an acidity‐responsive sensor. SF exhibit remarkable resilience against aerosol and droplet‐based pathogen transmission, showcasing a reduction exceeding 99.90% compared to uncoated fabrics across various drug‐resistant bacteria, Candida albicans, and Phi6 virus. Experiments involving bodily fluids from healthy and infected individuals reveal a significant reduction of 99.88% and 99.79% in clinical urine and feces samples, respectively, compared to uncoated fabrics. The SF's colorimetric detection capability coupled with machine learning (96.67% accuracy) ensures reliable pathogen identification, facilitating accurate differentiation between healthy and infected urine and fecal contaminated samples. SF holds promise for revolutionizing infection prevention and control in healthcare facilities, providing protection through early contamination detection.