GOALI: Molecular simulation studies of structure and retention in liquid chromatography systems

GOALI：液相色谱系统结构和保留的分子模拟研究

• 批准号: 0718383
• 负责人: Joern Ilja Siepmann
• 金额: $ 34.7万
• 依托单位: University of Minnesota-Twin Cities
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-08-01 至 2011-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0718383&HistoricalAwards=false
• 关键词: GOALI; Molecular; simulation; studies; structure

Professor J. Ilja Siepmann at the University of Minnesota and his collaborator Dr. Mark Schure at Rohm & Haas Corporation are supported by the Analytical and Surface Chemistry Program (with co-funding from the GOALI Program in the Engineering Directorate) to use molecular simulations to predict chromatographic retention times and to advance understanding of the molecular-level processes that govern retention in liquid chromatography. Efficient Monte Carlo simulation techniques and transferable force fields allow for calculations with the precision and accuracy required for chromatographic applications. Studies address retention in a wide range of reversed-phase liquid chromatography systems and at the solvent/matrix interface of porous polymeric monoliths.Chromatographic separation and the analysis of complex samples play pivotal roles for research and development in the chemical, pharmaceutical, food, and environmental sciences and industries. The molecular-level knowledge gained from this project will greatly aid the development of "next-generation" chromatographic separation technologies. The project also contributes to cyberinfrastructure through the development of freely distributed web-based molecular simulation packages. Close university-industry partnership affords unique training of participating students and postdoctoral associates.

明尼苏达大学的J. Ilja Siepmann教授和他的合作者Rohm哈斯公司的Mark Schure博士得到了分析和表面化学项目的支持（工程理事会的GOALI项目共同资助），使用分子模拟来预测色谱保留时间，并促进对液相色谱中控制保留的分子水平过程的理解。 高效的Monte Carlo模拟技术和可转移力场允许计算色谱应用所需的精度和准确度。 色谱分离和复杂样品的分析在化学、制药、食品和环境科学和工业的研究和开发中起着关键作用。 从这个项目中获得的分子水平的知识将大大有助于“下一代”色谱分离技术的发展。 该项目还通过开发免费分发的网络分子模拟软件包，为网络基础设施作出贡献。 紧密的大学-行业伙伴关系为参与的学生和博士后提供了独特的培训。