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DOI | 10.1016/j.jclepro.2017.06.113 |
Robustness analysis of a green chemistry-based model for the classification of silver nanoparticles synthesis processes | |
Cinelli, Marco1,2,6; Coles, Stuart R.2; Nadagouda, Mallikarjuna N.3; Biaszczynski, Jerzy4; Slowinski, Roman4,5; Varma, Rajender S.3; Kirwan, Kerry2 | |
发表日期 | 2017-09-20 |
ISSN | 0959-6526 |
卷号 | 162页码:938-948 |
英文摘要 | This paper proposes a robustness analysis based on Multiple Criteria Decision Aiding (MCDA). The ensuing model was used to assess the implementation of green chemistry principles in the synthesis of silver nanoparticles. Its recommendations were also compared to an earlier developed model for the same purpose to investigate concordance between the models and potential decision support synergies. A three-phase procedure was adopted to achieve the research objectives. Firstly, an ordinal ranking of the evaluation criteria used to characterize the implementation of green chemistry principles was identified through relative ranking analysis. Secondly, a structured selection process for an MCDA classification method was conducted, which ensued in the identification of Stochastic Multi-Criteria Acceptability Analysis (SMAA). Lastly, the agreement of the classifications by the two MCDA models and the resulting synergistic role of decision recommendations were studied. This comparison showed that the results of the two models agree between 76% and 93% of the simulation set-ups and it confirmed that different MCDA models provide a more inclusive and transparent set of recommendations. This integrative research confirmed the beneficial complementary use of MCDA methods to aid responsible development of nanosynthesis, by accounting for multiple objectives and helping communication of complex information in a comprehensive and traceable format, suitable for stakeholders and/or decision-makers with diverse backgrounds. (C) 2017 The Authors. Published by Elsevier Ltd. |
英文关键词 | Multiple Criteria Decision Aiding;Robustness analysis;Green nanotechnology;Dominance-based Rough Set Approach;ELECTRE |
语种 | 英语 |
WOS记录号 | WOS:000407185500082 |
来源期刊 | JOURNAL OF CLEANER PRODUCTION
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来源机构 | 美国环保署 |
文献类型 | 期刊论文 |
条目标识符 | http://gcip.llas.ac.cn/handle/2XKMVOVA/60642 |
作者单位 | 1.Univ Warwick, Inst Adv Study, Coventry CV4 7HS, W Midlands, England; 2.Univ Warwick, WMG, Coventry CV4 7AL, W Midlands, England; 3.US EPA, ORD Natl Risk Management Res Lab, Water Syst Div, Water Resources Recovery Branch, Cincinnati, OH 45268 USA; 4.Poznan Univ Tech, Inst Comp Sci, PL-60965 Poznan, Poland; 5.Polish Acad Sci, Syst Res Inst, PL-01447 Warsaw, Poland; 6.Swiss Fed Inst Technol, Singapore ETH Ctr SEC, FRS, Swiss Fed Inst Technol, Singapore, Singapore |
推荐引用方式 GB/T 7714 | Cinelli, Marco,Coles, Stuart R.,Nadagouda, Mallikarjuna N.,et al. Robustness analysis of a green chemistry-based model for the classification of silver nanoparticles synthesis processes[J]. 美国环保署,2017,162:938-948. |
APA | Cinelli, Marco.,Coles, Stuart R..,Nadagouda, Mallikarjuna N..,Biaszczynski, Jerzy.,Slowinski, Roman.,...&Kirwan, Kerry.(2017).Robustness analysis of a green chemistry-based model for the classification of silver nanoparticles synthesis processes.JOURNAL OF CLEANER PRODUCTION,162,938-948. |
MLA | Cinelli, Marco,et al."Robustness analysis of a green chemistry-based model for the classification of silver nanoparticles synthesis processes".JOURNAL OF CLEANER PRODUCTION 162(2017):938-948. |
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