Oxygen-deficient TiO/WO constructed via the controllable temperature of hydrogen annealing is designed in view of combining the broad visible spectrum absorption with the prominent coupled semiconductor properties. Surface lattice disorder of TiO/WO arises at hydrogen annealing temperature of 200 and 300°C, while critical phase transition from TiO/WO to TiO/WO occurs at 400°C, both of which can introduce oxygen vacancies. The hydrogenated TiO/WO with rich surface-oxygen-vacancies exhibits much higher photocatalytic activity for decomposition of gaseous toluene than pristine TiO/WO under visible-light illumination (λ>420nm). The photoelectrochemical analysis shows that the improved electronic properties of oxygen-deficient TiO/WO enable dramatically efficient promotion of photoinduced charge transfer and separation, which is the key factor for the improved photocatalytic activity. It is hoped that the present work could boost ongoing interest for preparing various hydrogenated coupled semiconductors with enhanced activity for diverse photocatalytic applications.
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http://dx.doi.org/10.1016/j.jhazmat.2017.08.077 | DOI Listing |
East Mediterr Health J
December 2024
Department of Basic Sciences, Faculty of Civil Engineering, University of Aleppo, Aleppo, Syria.
Background: Hospital wastewater poses a significant threat to human health due to the presence of difficult-to-degrade organic compounds, active pharmaceutical ingredients and multiple inorganic substances that can pollute water resources and ecosystems.
Aim: To compare the effectiveness of different techniques for removing organic load from hospital laboratory wastewater in Aleppo, Syria.
Methods: We treated wastewater samples from hospital laboratories at Aleppo University Hospital, Syria, using several techniques, including biological treatment with the rotating biological contactor, adsorption with Syrian natural clay, coagulation with aluminium sulphate, advanced oxidation with ultrasound, and a combined treatment using natural clay and ultrasound.
ACS Nano
January 2025
State Key Laboratory of Fine Chemicals, College of Materials Science and Engineering, Shenzhen University, Shenzhen 518055, China.
Biofilm-induced chronic bacterial infections represent a significant challenge in modern medicine due to their resistance to conventional antibiotic treatments. Although photodynamic therapy (PDT) has emerged as a promising antibiotic-free antibacterial strategy, the hypoxic condition within biofilms and the lack of an effective local drug delivery system have limited the clinical effectiveness of photosensitizer (PS) agents. Herein, we propose a type of charge regulation-enhanced type I PS-loaded hydrogel dressing for treating biofilm infection.
View Article and Find Full Text PDFJ Intensive Care Soc
January 2025
Department of Physiotherapy, Faculty of Medicine, Dentistry and Health Sciences, School of Health Sciences, The University of Melbourne, Melbourne, VIC, Australia.
Digital health refers to the field of using and developing technology to improve health outcomes. Digital health and digital health interventions (DHIs) within the area of intensive care and critical illness survivorship are rapidly evolving. Digital health interventions refer to technologies in clinical interventional format.
View Article and Find Full Text PDFInternet Interv
December 2024
Bournemouth University, Poole, United Kingdom.
Gambling, though a popular social activity, can lead to addiction and cause significant harm. This study aimed to explore the experiences of 36 low-to-moderate risk gamblers (PGSI score 0-7; 31 male, 5 female; 10 per each intervention arm, 6 per control group) in the 'EROGamb 2.0' feasibility trial ( = 168).
View Article and Find Full Text PDFMetal-organic frameworks (MOFs) are porous, crystalline materials with high surface area, adjustable porosity, and structural tunability, making them ideal for diverse applications. However, traditional experimental and computational methods have limited scalability and interpretability, hindering effective exploration of MOF structure-property relationships. To address these challenges, we introduce, for the first time, a category-specific topological learning (CSTL), which combines algebraic topology with chemical insights for robust property prediction.
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