A framework for sustainable nanomaterial selection and design based on performance, hazard, and economic considerations
Autor: | Shauhrat S. Chopra, Julie B. Zimmerman, Leanne M. Gilbertson, Mark M. Falinski, Thomas L. Theis, Desiree L. Plata |
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Rok vydání: | 2018 |
Předmět: |
Computer science
Scale (chemistry) Engineered nanomaterials Biomedical Engineering Bioengineering 02 engineering and technology 010501 environmental sciences 021001 nanoscience & nanotechnology Condensed Matter Physics 01 natural sciences Hazard Atomic and Molecular Physics and Optics Human health Risk analysis (engineering) Material selection Design process General Materials Science Environmental impact assessment Electrical and Electronic Engineering 0210 nano-technology Selection (genetic algorithm) 0105 earth and related environmental sciences |
Zdroj: | Nature Nanotechnology. 13:708-714 |
ISSN: | 1748-3395 1748-3387 |
DOI: | 10.1038/s41565-018-0120-4 |
Popis: | Engineered nanomaterials (ENMs) and ENM-enabled products have emerged as potentially high-performance replacements to conventional materials and chemicals. As such, there is an urgent need to incorporate environmental and human health objectives into ENM selection and design processes. Here, an adapted framework based on the Ashby material selection strategy is presented as an enhanced selection and design process, which includes functional performance as well as environmental and human health considerations. The utility of this framework is demonstrated through two case studies, the design and selection of antimicrobial substances and conductive polymers, including ENMs, ENM-enabled products and their alternatives. Further, these case studies consider both the comparative efficacy and impacts at two scales: (i) a broad scale, where chemical/material classes are readily compared for primary decision-making, and (ii) within a chemical/material class, where physicochemical properties are manipulated to tailor the desired performance and environmental impact profile. Development and implementation of this framework can inform decision-making for the implementation of ENMs to facilitate promising applications and prevent unintended consequences. |
Databáze: | OpenAIRE |
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