CAREER: Building Chemical Synthesis Networks for Life Cycle Hazard Modeling

职业：构建用于生命周期危害建模的化学合成网络

• 批准号: 1454414
• 负责人: Matthew Eckelman
• 金额: $ 50.27万
• 依托单位: Northeastern University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-05-01 至 2022-04-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1454414&HistoricalAwards=false
• 关键词: CAREER; Building; Chemical; Synthesis; Networks

1454414 (Eckelman). Industrial chemicals are fundamental to nearly every aspect of modern society and technology but also present potential hazards to the environment and public health. Robust data on both direct and indirect impacts from chemical production and transport are essential for reliable sustainability assessment of products and policies. Current practices suffer from generic empirical data, lack of statistically validated estimation tools, and poor integration with standard industry and government practices in tracking chemical hazards. This research will enable the next generation of chemicals life cycle assessment (LCA) while providing educational experiences to inspire the next generation of interdisciplinary chemical and environmental scientists. Through carefully structured project tasks, this effort will (1) Create a chemical synthesis network for environmental analysis and data generation, (2) Integrate green chemistry principles into a new computational structure for LCA, and (3) Apply LCA's network structure to inform national assessments of chemical supply chain resilience and vulnerability of critical water and wastewater infrastructure. The associated integrated education and outreach program will provide cutting-edge research opportunities, new courses, online educational materials, and demonstrations. Video modules will connect participants to the physical logistics of our chemical infrastructure, providing a bridge between traditional chemistry instruction and chemical and environmental engineering. Project research will be integrated into the PI's teaching, while new courses will include group projects relevant to research objectives.The proposed research will create a science-based, spatial, and dynamic modeling platform to enable next-generation sustainability assessment of chemicals. High-quality inventory data for hundreds of chemicals and validated estimation tools for thousands more will constitute an open toolkit for the global modeling community. Mechanistic process models will offer unprecedented accuracy in modeling chemical unit processes for LCA while still maintaining a conserved, network structure of energy and material flows upstream to resource extraction. New algorithms and metrics will integrate the inherent hazard approach of green chemistry with the systems approach of LCA. Research activities will leverage existing computational and modeling facilities at Northeastern and Sandia National Laboratory. The research tasks are anticipated to advance modeling and assessment capabilities in evaluating chemical technologies for public and private decision-making. Data, models, and results will be disseminated widely and structured to enable interoperability with existing modeling platforms. The integrated research and education plan will directly engage local students, teachers, and the public, potentially affecting thousands of students and citizens. The project will broaden participation in science and engineering by recruiting and mentoring student researchers from under-represented groups for high school (Young Scholars, Step-Up Programs), college (REU), and science teachers (RET). Design, delivery, and assessment of education and outreach activities will leverage existing capabilities and expertise from Northeastern's highly successful Center for STEM Education, the Graduate School of Engineering, and the Center for Teaching and Learning through Research and will build on the PI's experience in K-12 science instruction, teacher training, and online education.

1454414（Eckelman）。工业化学品几乎对现代社会和技术的各个方面都是至关重要的，但也对环境和公共卫生构成潜在危害。关于化学生产和运输的直接和间接影响的强大数据对于可靠的可持续性评估产品和政策至关重要。当前的做法遭受了通用的经验数据，缺乏统计验证的估计工具以及与标准行业和政府实践在跟踪化学危害方面的不良融合。这项研究将使下一代化学生命周期评估（LCA）能够提供教育经验，以激发下一代跨学科的化学和环境科学家。通过精心结构化的项目任务，（1）创建一个化学综合网络，用于环境分析和数据生成，（2）将绿色化学原理整合到LCA的新计算结构中，以及（3）应用LCA的网络结构来告知国家国家评估化学供应链的弹性以及关键水和废水基础设施的脆弱性。相关的综合教育和外展计划将提供尖端的研究机会，新课程，在线教育材料和示范。视频模块将将参与者与我们化学基础设施的物理物流联系起来，从而在传统的化学教学与化学和环境工程之间提供桥梁。项目研究将集成到PI的教学中，而新课程将包括与研究目标相关的小组项目。拟议的研究将创建一个基于科学的，空间和动态的建模平台，以实现化学物质的下一代可持续性评估。数百种化学品和数以千计的估算工具的高质量库存数据将构成全球建模社区的开放工具包。机械过程模型将在为LCA建模化学单元过程时提供前所未有的准确性，同时仍保持保守的，能量和材料的网络结构，并在资源提取上游以上流动。新的算法和指标将将绿色化学的固有危害方法与LCA的系统方法相结合。研究活动将利用东北和桑迪亚国家实验室的现有计算和建模设施。预计研究任务将提高建模和评估能力，以评估公共和私人决策的化学技术。数据，模型和结果将被广泛传播并结构化，以启用与现有建模平台的互操作性。综合研究和教育计划将直接吸引当地学生，教师和公众，可能会影响成千上万的学生和公民。该项目将通过招募和指导学生研究人员的高中（年轻学者，升级课程），学院（REU）和科学老师（RET）的招募和指导学生研究人员（RET）来扩大对科学和工程的参与。设计，交付和评估教育和外展活动将利用东北非常成功的STEM教育中心，工程研究生院以及通过研究的教学和学习中心的现有能力和专业知识，并将基于PI在K中的经验。 -12科学教学，教师培训和在线教育。