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GOALI: Collaborative Research: Next generation 2D-LC with greatly improved quantitative performance: Innovations in hardware, software, and methodology

GOALI: Collaborative Research: Next generation 2D-LC with greatly improved quantitative performance: Innovations in hardware, software, and methodology
目标:协作研究:定量性能大幅提高的下一代 2D-LC:硬件、软件和方法方面的创新
批准号:
1507332
负责人:
Maryanne Collinson
金额:
$40.67万
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
项目状态:
已结题
起止时间:
2015-08-01 至 2021-06-30

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中文摘要
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英文摘要
In this project funded by the Chemical Measurement and Imaging program of the Chemistry Division, Professors Dwight Stoll of Gustavus Adolphus College and Sarah Rutan of Virginia Commonwealth University are studying fundamental aspects of the quantitative performance of two-dimensional liquid chromatography (2D-LC). 2D-LC is an analytical methodology used for separation of inherently complex materials including urine, blood, urban wastewater, and the products of chemical and biological synthesis. The separation power of 2D-LC is well suited to better understand such complex samples in fields ranging from medicine and pharmaceutical development to environmental chemistry. However, state-of-the-art 2D-LC currently suffers from poorer sensitivity and precision compared to more conventional methods, and this limits its scope of application. This academic/industrial collaboration between Gustavus Adolphus College, Virginia Commonwealth University, and Agilent Technologies will enable a deeper fundamental understanding of these limitations and support the development of novel technologies to improve the quantitative performance of 2D-LC.This project will leverage the strengths of the collaboration partners to address the limitations in quantitative performance of 2D-LC through a combination of complementary strategies. Simulations will be developed to better understand the underlying fundamental limitations of coupling the two dimensions in 2D-LC, novel valve technology will be developed and its performance characterized experimentally, and computer-based data analysis methods will be developed that enable better utilization of the multi-dimensional structure of data produced by 2D-LC methods. It is expected that the detection limits of 2D-LC will be improved at least five-fold, and that the quantitative precision will be improved so that it is competitive with conventional liquid chromatography. The broader impacts of the work include: wider application of 2D-LC as a high resolution separation technique across the life sciences and chemical industries; engagement of students at the high school, undergraduate, and graduate levels in cutting-edge research; and development of simulations that will facilitate more efficient and deeper learning about critical concepts in liquid chromatography.
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Improving the LC Separation of Biomolecule Mixtures using Novel Mixed-Mode Gradient Stationary Phases
  • 批准号:
    2305102
  • 项目类别:
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  • 资助金额:
    $48.0万
  • 财政年份:
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  • 负责人:
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  • 资助金额:
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  • 财政年份:
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  • 批准号:
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  • 项目类别:
    Continuing Grant
  • 资助金额:
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    2014
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  • 资助金额:
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  • 负责人:
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  • 依托单位:
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