Irini Furxhi , Massimo Perucca , Giovanni Baldi , Valentina Dami , Andrea Cioni , Antti Joonas Koivisto , Rossella Bengalli , Paride Mantecca , Giulia Motta , Marie Carriere , Alessia Nicosia , Fabrizio Ravegnani , David Burrueco-Subirà , Socorro Vázquez-Campos , Elma Lahive , Jesús Lopez de Ipiña , Juliana Oliveira , Patrick Cronin , Magda Blosi , Anna Costa
{"title":"推进二氧化钛涂层光催化污染表面:利用 ASINA 路线图实现更安全和可持续的解决方案","authors":"Irini Furxhi , Massimo Perucca , Giovanni Baldi , Valentina Dami , Andrea Cioni , Antti Joonas Koivisto , Rossella Bengalli , Paride Mantecca , Giulia Motta , Marie Carriere , Alessia Nicosia , Fabrizio Ravegnani , David Burrueco-Subirà , Socorro Vázquez-Campos , Elma Lahive , Jesús Lopez de Ipiña , Juliana Oliveira , Patrick Cronin , Magda Blosi , Anna Costa","doi":"10.1016/j.csbj.2024.10.001","DOIUrl":null,"url":null,"abstract":"<div><div>This report, the second of its kind from ASINA project, aims at providing a roadmap with quantitative metrics for Safe(r) and (more) Sustainable by Design (SSbD) solutions for titanium dioxide (TiO<sub>2</sub>) nanomaterials (NMs). We begin with a brief description of ASINA’s methodology across the product lifecycle, highlighting the quantitative elements, such as the Key Performance Indicators (KPIs). We then propose a decision support tool for implementing SSbD objectives across various dimensions—functionality, cost, environment, and human health safety. This is followed by the main innovative findings, a consolidation of the technical processes involved, design rationales, experimental procedures, tools and models, used and developed, to deliver photocatalytic depolluting surfaces by spray- finishing techniques based on TiO<sub>2</sub> NMs formulations. The roadmap is thoroughly described to inform similar projects through the integration of KPIs into SSbD methodologies, fostering data-driven decision-making. While specific results are beyond this report's scope, its primary aim is to demonstrate the roadmap (SSbD know-how) and promote SSbD-oriented innovation in nanotechnology. Finally, we provide a comparison of the approaches followed in two case studies that target different industrial sectors. 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Advancing titanium dioxide coated photocatalytic depolluting surfaces: Leveraging ASINA's roadmap for safer and sustainable solutions
This report, the second of its kind from ASINA project, aims at providing a roadmap with quantitative metrics for Safe(r) and (more) Sustainable by Design (SSbD) solutions for titanium dioxide (TiO2) nanomaterials (NMs). We begin with a brief description of ASINA’s methodology across the product lifecycle, highlighting the quantitative elements, such as the Key Performance Indicators (KPIs). We then propose a decision support tool for implementing SSbD objectives across various dimensions—functionality, cost, environment, and human health safety. This is followed by the main innovative findings, a consolidation of the technical processes involved, design rationales, experimental procedures, tools and models, used and developed, to deliver photocatalytic depolluting surfaces by spray- finishing techniques based on TiO2 NMs formulations. The roadmap is thoroughly described to inform similar projects through the integration of KPIs into SSbD methodologies, fostering data-driven decision-making. While specific results are beyond this report's scope, its primary aim is to demonstrate the roadmap (SSbD know-how) and promote SSbD-oriented innovation in nanotechnology. Finally, we provide a comparison of the approaches followed in two case studies that target different industrial sectors. This case-specific SSbD assessments provide a concrete exemplification of the addressed methodology that contributes to the efforts towards attaining a common roadmap for implementing SSbD solutions aligned with the EU’s Green Deal objectives.
期刊介绍:
Computational and Structural Biotechnology Journal (CSBJ) is an online gold open access journal publishing research articles and reviews after full peer review. All articles are published, without barriers to access, immediately upon acceptance. The journal places a strong emphasis on functional and mechanistic understanding of how molecular components in a biological process work together through the application of computational methods. Structural data may provide such insights, but they are not a pre-requisite for publication in the journal. Specific areas of interest include, but are not limited to:
Structure and function of proteins, nucleic acids and other macromolecules
Structure and function of multi-component complexes
Protein folding, processing and degradation
Enzymology
Computational and structural studies of plant systems
Microbial Informatics
Genomics
Proteomics
Metabolomics
Algorithms and Hypothesis in Bioinformatics
Mathematical and Theoretical Biology
Computational Chemistry and Drug Discovery
Microscopy and Molecular Imaging
Nanotechnology
Systems and Synthetic Biology