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Fourier Transform NMR for Liquids and Solids in the Undergraduate Curriculum

Fourier Transform NMR for Liquids and Solids in the Undergraduate Curriculum
本科课程中液体和固体的傅里叶变换核磁共振
批准号:
9751497
负责人:
William Shirley
金额:
$10.0万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
1997
资助国家:
美国
项目状态:
已结题
起止时间:
1997-05-15 至 1999-04-30

项目摘要

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中文摘要
翻译
化学系计划将具有固态能力的傅里叶变换核磁共振(FT-NMR)光谱仪纳入其本科课程。 购买这台光谱仪是其不断努力使化学计划现代化的重要组成部分。 有机实验室课程的本科生获得获得质子和碳NMR光谱的第一手经验,作为强调学生规划和合成设计的课程的一部分。 涉及液体样品的高级FT-NMR实验明显影响本科生生物化学、聚合物和物理化学实验室以及本科生研究。 该部门有一个非常活跃的本科研究计划,学生在美国化学学会的区域和国家会议上做演讲。 该项目的一个独特部分是固体的高分辨率NMR将成为本科实验室经验的一部分。 五个新的实验,涉及固态核磁共振提供了本科实验室课程的有机,分析,物理/无机和聚合物化学。 固态NMR是催化表面和聚合物研究的重要工具。 固态核磁共振仪器的最新进展使得将固态核磁共振引入本科课程成为可能。
英文摘要
The Chemistry Department plans to incorporate a Fourier-transform nuclear magnetic resonance (FT-NMR) spectrometer with solid-state capabilities into its undergraduate curriculum. The purchase of this spectrometer is a major part of its continuing effort to modernize the chemistry program. Undergraduates in the organic laboratory program gain first-hand experience in obtaining proton and carbon NMR spectra as part of a course emphasizing student planning and design of syntheses. Advanced FT-NMR experiments involving liquid samples clearly impact the undergraduate biochemistry, polymer, and physical chemistry laboratories as well as undergraduate research. The department has a very active undergraduate research program, with students making presentations at regional and national meetings of the American Chemical Society. A unique part of the project is that high-resolution NMR of solids is to be part of the undergraduate laboratory experience. Five new experiments involving solid-state NMR are provided for undergraduate laboratory courses in organic, analytical, physical/inorganic, and polymer chemistry. Solid-state NMR is an important tool for undergraduate research in catalytic surfaces and polymers. Recent advances in solid-state NMR instrumentation make it possible to bring solid-state NMR to an undergraduate program.
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视觉智能Shapelet Transform驱动的SHM数据关联分析与域自适应迁移机制深度学习
  • 批准号:
    52108276
  • 项目类别:
    青年科学基金项目(C类)
  • 资助金额:
    30.0万元
  • 批准年份:
    2021
  • 负责人:
    陈柳洁
  • 依托单位: