IMPLEMENTING INNOVATIVE METHODS FOR SAFETY AND SUSTAINABILITY ASSESSMENTS OF CHEMICALS AND MATERIALS PARTICULARLY AT NANO LEVEL IN THE EUROPEAN UNION
IMPLEMENTING INNOVATIVE METHODS FOR SAFETY AND SUSTAINABILITY ASSESSMENTS OF CHEMICALS AND MATERIALS PARTICULARLY AT NANO LEVEL IN THE EUROPEAN UNION
批准号:
10109804
负责人:
金额:
$49.72万
依托单位国家:
英国
项目类别:
EU-Funded
财政年份:
2024
资助国家:
英国
项目状态:
未结题
起止时间:
2024 至 --
中文摘要
点击翻译按钮获取中文摘要
英文摘要
The Chemicals Strategy for Sustainability (CSS) has been adopted, which aims to tackle the challenge of producing and using chemicals to address societal needs while respecting the planetary boundaries and safeguarding people and ecosystems, by dealing with pollution from all sources (EC, 2019 or COM(2019)640final, COM(2020)667 final, JRC report). This CSS challenge gets operationalised through the development/implementation of two key R&I actions: 1) the Strategic Research and Innovation Plan (SRIP), and 2) the Safe and Sustainable by Design (SSbD) framework. Consistent with the aims of the Call HORIZON-CL4-2023- RESILIENCE-01-21 and bearing in the mind the pressing need to develop new methods or improve current ones, to support the improvement of safety and sustainability assessments of chemicals, the project “IMPLEMENTING INNOVATIVE METHODS FOR SAFETY AND SUSTAINABILITY ASSESSMENTS OF CHEMICALS AND MATERIALS PARTICULARLY AT NANO LEVEL IN THE EUROPEAN UNION (CheMatSustain)” will not only study the quantum effects from a fundamental point-of-view (by DFT means) but also by identifying and measuring them through experimental techniques (high-resolution analysis, XPS and UPS), and determining the specific molecular recognition through their interaction with the environment, which is a quantum mechanical effect (in vitro, microfluidic in-vitro, and in-vivo models and proteomics and transcriptomics and methods). The obtained information on these descriptors will then be integrated for the development of novel in silico models for prediction (eco)toxicity properties of advanced materials. Finally, in-silico model prediction results will be combined to develop a new methodology for the complementary use of Risk Assessment and LCA to improve criteria for the SSbD implementation framework. The work has been divided in eight work packages and the duration of the project is 48 months.
期刊论文(0)
专著(0)
科研奖励(0)
会议论文
海外基金