Noor Abu Jarad, Akansha Prasad, Sara Rahmani, Fereshteh Bayat, Mathura Thirugnanasampanthar, Zeinab Hosseinidoust, Leyla Soleymani, Tohid F. Didar
{"title":"Smart Fabrics with Integrated Pathogen Detection, Repellency, and Antimicrobial Properties for Healthcare Applications","authors":"Noor Abu Jarad, Akansha Prasad, Sara Rahmani, Fereshteh Bayat, Mathura Thirugnanasampanthar, Zeinab Hosseinidoust, Leyla Soleymani, Tohid F. Didar","doi":"10.1002/adfm.202403157","DOIUrl":null,"url":null,"abstract":"<p>Healthcare 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, <i>Candida albicans</i>, 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.</p>","PeriodicalId":112,"journal":{"name":"Advanced Functional Materials","volume":null,"pages":null},"PeriodicalIF":18.5000,"publicationDate":"2024-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/adfm.202403157","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Advanced Functional Materials","FirstCategoryId":"88","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/adfm.202403157","RegionNum":1,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CHEMISTRY, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0
Abstract
Healthcare 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.
期刊介绍:
Firmly established as a top-tier materials science journal, Advanced Functional Materials reports breakthrough research in all aspects of materials science, including nanotechnology, chemistry, physics, and biology every week.
Advanced Functional Materials is known for its rapid and fair peer review, quality content, and high impact, making it the first choice of the international materials science community.